Title: Calculus Made Easy
Author: Silvanus P. Thompson
Release date: July 28, 2010 [eBook #33283]
Most recently updated: August 28, 2026
Language: English
Other information and formats: www.gutenberg.org/ebooks/33283
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CALCULUS MADE EASY
Author: Silvanus Thompson
MACMILLAN AND CO., Limited
LONDON : BOMBAY : CALCUTTA
MELBOURNE
THE MACMILLAN COMPANY
NEW YORK : BOSTON : CHICAGO
DALLAS : SAN FRANCISCO
THE MACMILLAN CO. OF CANADA, Ltd.
TORONTO
Being a very-simplest introduction to those beautiful methods of reckoning which are generally called by the terrifying names of the
DIFFERENTIAL CALCULUS
AND THE
INTEGRAL CALCULUS
By
F. R. S.
SECOND EDITION, ENLARGED
MACMILLAN AND CO., LIMITED
ST. MARTIN'S STREET, LONDON
1914
COPYRIGHT.
First Edition 1910.
Reprinted 1911 (twice), 1912, 1913.
Second Edition 1914.
What one fool can do, another can.
(Ancient Simian Proverb.)
PREFACE TO THE SECOND EDITION.
THE surprising success of this work has led the author to add a considerable number of worked examples and exercises. Advantage has also been taken to enlarge certain parts where experience showed that further explanations would be useful.
The author acknowledges with gratitude many valuable suggestions and letters received from teachers, students, and-critics.
October, 1914.
| Chapter | PAGE |
| Prologue | viii |
| I. To deliver you from the Preliminary Terrors | 1 |
| II. On Different Degrees of Smallness | 3 |
| III. On Relative Growings | 9 |
| IV. Simplest Cases | 17 |
| V. Next Stage. What to do with Constants | 25 |
| VI. Sums, Differences, Products and Quotients | 34 |
| VII. Successive Differentiation | 48 |
| VIII. When Time Varies | 52 |
| IX. Introducing a Useful Dodge | 66 |
| X. Geometrical Meaning of Differentiation | 75 |
| XI. Maxima and Minima | 91 |
| XII. Curvature of Curves | 109 |
| XIII. Other Useful Dodges | 118 |
| XIV. On true Compound Interest and the Law of Organic Growth |
131 |
| XV. How to deal with Sines and Cosines | 162 |
| XVI. Partial Differentiation | 172 |
| XVII. Integration | 180 |
| XVIII. Integrating as the Reverse of Differentiating | 189 |
| XIX. On Finding Areas by Integrating | 204 |
| XX. Dodges, Pitfalls, and Triumphs | 224 |
| XXI. Finding some Solutions | 232 |
| Table of Standard Forms | 249 |
| Answers to Exercises | 252 |
[Pg viii]
CONSIDERING how many fools can calculate, it is surprising that it should be thought either a difficult or a tedious task for any other fool to learn how to master the same tricks.
Some calculus-tricks are quite easy. Some are enormously difficult. The fools who write the textbooks of advanced mathematics—and they are mostly clever fools-seldom take the trouble to show you how easy the easy calculations are. On the contrary, they seem to desire to impress you with their tremendous cleverness by going about it in the most difficult way.
Being myself a remarkably stupid fellow, I have had to unteach myself the difficulties, and now beg to present to my fellow fools the parts that are not hard. Master these thoroughly, and the rest will follow. What one fool can do, another can.
[Pg 1]
THE preliminary terror, which chokes off most fifth-form boys from even attempting to learn how to calculate, can be abolished once for all by simply stating what is the meaning-in common-sense terms-of the two principal symbols that are used in calculating.
These dreadful symbols are:
(1) which merely means "a little bit of."
Thus means a little bit of
; or
means a little
bit of
. Ordinary mathematicians think it more polite to say "an
element of," instead of "a little bit of." Just as you please. But you
will find that these little bits (or elements) may be considered to be
indefinitely small.
(2) which is merely a long
, and may be called (if you
like) "the sum of."
Thus means the sum of all the little bits of
; or
means the sum of all the little bits of
. Ordinary
mathematicians call this symbol "the integral of." Now any fool can see
that if
is considered as made up of a lot of little bits, each of
which is called
, if you add them all up together you get the
sum of all the
's, (which is the[Pg 2]
same thing as the whole of
). The word "integral" simply means
"the whole." If you think of the duration of time for one hour, you
may (if you like) think of it as cut up into 3600 little bits called
seconds. The whole of the 3600 little bits added up together make one
hour.
When you see an expression that begins with this terrifying symbol, you will henceforth know that it is put there merely to give you instructions that you are now to perform the operation (if you can) of totalling up all the little bits that are indicated by the symbols that follow.
That's all.
[Pg 3]
WE shall find that in our processes of calculation we have to deal with small quantities of various degrees of smallness.
We shall have also to learn under what circumstances we may consider small quantities to be so minute that we may omit them from consideration. Everything depends upon relative minuteness.
Before we fix any rules let us think of some familiar cases. There are 60 minutes in the hour, 24 hours in the day, 7 days in the week. There are therefore 1440 minutes in the day and 10080 minutes in the week.
Obviously 1 minute is a very small quantity of time compared with a whole week. Indeed, our forefathers considered it small as compared with an hour, and called it "one minùte," meaning a minute fraction —namely one sixtieth—of an hour. When they came to require still smaller subdivisions of time, they divided each minute into 60 still smaller parts, which, in Queen Elizabeth's days, they called "second minùtes" (i.e. small quantities of the second order of minuteness). Nowadays we call these small quantities of the second order of smallness "seconds." But few people know why they are so called.
Now if one minute is so small as compared with a whole day, how [Pg 4] much smaller by comparison is one second!
Again, think of a farthing as compared with a sovereign: it is barely
worth more than part. A farthing more or less is of
precious little importance compared with a sovereign: it may certainly
be regarded as a small quantity. But compare a farthing with
:
relatively to this greater sum, the farthing is of no more importance
than
of a farthing would be to a sovereign. Even a
golden sovereign is relatively a negligible quantity in the wealth of a
millionaire.
Now if we fix upon any numerical fraction as constituting the
proportion which for any purpose we call relatively small, we can
easily state other fractions of a higher degree of smallness. Thus if,
for the purpose of time, be called a small
fraction, then
of
(being a
small fraction of a small fraction) may be regarded as a
small quantity of the second order of smallness.[1]
Or, if for any purpose we were to take 1 per
cent.
as a small fraction, then 1 per cent. of 1 per cent.
would be a small
fraction of the second order of smallness; and
would be a small fraction of the third order of smallness, being 1 per
cent. of 1 per cent. of 1 per cent.
Lastly, suppose that for some very precise purpose we should regard
as "small." Thus, if a first-rate chronometer
is not to lose or gain more than half a minute in a year, it must keep
time with an accuracy of 1 part in
. Now if, for such a
purpose, we[Pg 5]
regard
(or one millionth) as a small quantity,
then
of
, that
is
(or one trillionth) will be a
small quantity of the second order of smallness, and may be utterly
disregarded, by comparison.
Then we see that the smaller a small quantity itself is, the more negligible does the corresponding small quantity of the second order become. Hence we know that in all cases we are justified in neglecting the small quantities of the second-or third (or higher)—orders, if only we take the small quantity of the first order small enough in itself.
But, it must be remembered, that small quantities if they occur in our expressions as factors multiplied by some other factor, may become important if the other factor is itself large. Even a farthing becomes important if only it is multiplied by a few hundred.
Now in the calculus we write for a little bit of
.
These things such as
, and
, and
, are called
"differentials," the differential of
, or of
, or of
, as the case may be. [You read them as dee-eks, or
dee-you, or dee-wy.] If
be a small bit of
,
and relatively small of itself, it does not follow that such quantities
as
, or
, or
are negligible.
But
would be negligible, being a small quantity of
the second order.
A very simple example will serve as illustration.
Let us think of as a quantity that can grow by a small amount so
as to become
, where
is the small increment added by
growth. The square of this is
. The
second term is not negligible because it is a first-order quantity;
while the third term is of the second order of smallness, being a bit
of, a bit of
. Thus if we[Pg 6]
took
to mean numerically, say,
of
, then
the second term would be
of
, whereas the
third term would be
of
. This last term is
clearly less important than the second. But if we go further and take
to mean only
of
, then the second term
will be
of
, while the third term will be
only
of
.
Fig. 1.
Geometrically this may be depicted as follows: Draw a square (Fig. 1)
the side of which we will take to represent . Now suppose the
square to grow by having a bit
added to its size each way. The
enlarged square is made up of the original square
, the two
rectangles at the top and on the right, each of which is of area
(or together
), and the little square at
the top right-hand corner which is
. In Fig. 2 we have
taken
as quite a big fraction of
—about
.
But suppose we had taken it only
—about the thickness
of an inked line drawn with a fine pen. Then the little corner square
will have an area of only
of
, and be
practically invisible. Clearly
is negligible if only we
consider the increment
to be itself small enough.
Let us consider a simile.
[Pg 7]
Fig. 2.
Fig. 3.
Suppose a millionaire were to say to his secretary: next week I will
give you a small fraction of any money that comes in to me. Suppose
that the secretary were to say to his boy: I will give you a small
fraction of what I get. Suppose the fraction in each case to be
part. Now if Mr. Millionaire received during the
next week
, the secretary would receive
and the
boy 2 shillings. Ten pounds would be a small quantity compared with
; but two shillings is a small small quantity indeed, of
a very secondary order. But what would be the disproportion if the
fraction, instead of being
, had been settled at
part? Then, while Mr. Millionaire got his
, Mr. Secretary would get only
, and the boy less than one
farthing!
The witty Dean Swift[2] once wrote:
[Pg 8]
An ox might worry about a flea of ordinary size—a small creature of the first order of smallness. But he would probably not trouble himself about a flea's flea; being of the second order of smallness, it would be negligible. Even a gross of fleas' fleas would not be of much account to the ox.
[1] The mathematicians talk about the second order of "magnitude" (i.e. greatness) when they really mean second order of smallness. This is very confusing to beginners.
[2] On Poetry: a Rhapsody (p. 20), printed 1733—usually misquoted.
[Pg 9]
ALL through the calculus we are dealing with quantities that
are growing, and with rates of growth. We classify all quantities
into two classes: constants and variables. Those which
we regard as of fixed value, and call constants, we generally
denote algebraically by letters from the beginning of the alphabet,
such as ,
, or
; while those which we consider as capable
of growing, or (as mathematicians say) of "varying," we denote by
letters from the end of the alphabet, such as
, or
sometimes
.
Moreover, we are usually dealing with more than one variable at once, and thinking of the way in which one variable depends on the other: for instance, we think of the way in which the height reached by a projectile depends on the time of attaining that height. Or we are asked to consider a rectangle of given area, and to enquire how any increase in the length of it will compel a corresponding decrease in the breadth of it. Or we think of the way in which any variation in the slope of a ladder will cause the height that it reaches, to vary.
Suppose we have got two such variables that depend one on the other. An
alteration in one will bring about an alteration in the other, because
of this dependence. Let us call one of the variables , and the[Pg 10]
other that depends on it
.
Suppose we make to vary, that is to say, we either alter it or
imagine it to be altered, by adding to it a bit which we call
.
We are thus causing
to become
. Then, because
has
been altered,
will have altered also, and will have become
.
Here the bit
may be in some cases positive, in others
negative; and it won't (except by a miracle) be the same size as
.
Take two examples.
Fig. 4.
(1) Let and
be respectively the base and the height of a
right-angled triangle (Fig. 4), of which the slope of the other side
is fixed at
. If we suppose this triangle to expand and
yet keep its angles the same as at first, then, when the base grows so
as to become
, the height becomes
. Here, increasing
results in an increase of
. The little triangle, the height
of which is
, and the base of which is
, is similar to
the original triangle; and it is obvious that the value of the ratio
is the same as that of the ratio
.
As the angle is
it will be seen that here
[Pg 11]
Fig. 5.
(2) Let represent, in Fig. 5, the horizontal distance, from a
wall, of the bottom end of a ladder,
, of fixed length; and let
be the height it reaches up the wall. Now
clearly depends
on
. It is easy to see that, if we pull the bottom end
a bit
further from the wall, the top end
will come down a little lower.
Let us state this in scientific language. If we increase
to
,
then
will become
; that is, when
receives a
positive increment, the increment which results to
is negative.
Yes, but how much? Suppose the ladder was so long that when the bottom
end was 19 inches from the wall the top end
reached just
15 feet from the ground. Now, if you were to pull the bottom end out
1 inch more, how much would the top end come down? Put it all into
inches:
inches,
inches. Now the increment of
which we call
, is 1 inch: or
inches.
[Pg 12]
How much will be diminished? The new height will be
. If
we work out the height by Euclid I. 47, then we shall be able to find
how much
will be. The length of the ladder is
Clearly then, the new height, which is , will be such that
Now
is 180, so that
is
inch.
So we see that making an increase of 1 inch has resulted in
making
a decrease of 0.11 inch.
And the ratio of to
may be stated thus:
It is also easy to see that (except in one particular position)
will be of a different size from
.
Now right through the differential calculus we are hunting, hunting,
hunting for a curious thing, a mere ratio, namely, the proportion which
bears to
when both of them are indefinitely small.
It should be noted here that we can only find this ratio
when
and
are related to each other in some way,
so that whenever
varies
does vary also. For instance, in
the first example just taken, if the base
of the triangle be made
longer, the height
of the triangle becomes greater also, and in
the second example, if the distance
of the foot of the ladder
from the wall be made to increase, the height
[Pg 13]
reached by the ladder decreases in a corresponding manner, slowly at
first, but more and more rapidly as
becomes greater. In these
cases the relation between
and
is perfectly definite, it
can be expressed mathematically, being
and
(where
is the length of the ladder)
respectively, and
has the meaning we found in each
case.
If, while is, as before, the distance of the foot of the
ladder from the wall,
is, instead of the height reached, the
horizontal length of the wall, or the number of bricks in it, or
the number of years since it was built, any change in
would
naturally cause no change whatever in
; in this case
has no meaning whatever, and it is not possible to find an
expression for it. Whenever we use differentials
,
,
, etc., the existence of some kind of relation between
,
etc., is implied, and this relation is called a "function" in
, etc.; the two expressions given above, for instance,
namely
and
, are
functions of
and
. Such expressions contain implicitly (that
is, contain without distinctly showing it) the means of expressing
either
in terms of
or
in terms of
, and for this
reason they are called implicit functions in
and
; they can
be respectively put into the forms
These last expressions state explicitly (that is, distinctly) the value
of in terms of
, or of
in terms of
, and they
are for this reason called explicit functions of
or
. For
example
is an[Pg 14]
implicit function in
and
; it may be written
(explicit function of
) or
(explicit function of
). We see that an explicit function
in
,
,
, etc., is simply something the value of which
changes when
,
,
, etc., are changing, either one at the
time or several together. Because of this, the value of the explicit
function is called the dependent variable, as it depends on
the value of the other variable quantities in the function; these
other variables are called the independent variables because
their value is not determined from the value assumed by the function.
For example, if
,
and
are the
independent variables, and
is the dependent variable.
Sometimes the exact relation between several quantities ,
,
either is not known or it is not convenient to state it; it is
only known, or convenient to state, that there is some sort of relation
between these variables, so that one cannot alter either
or
or
singly without affecting the other quantities; the existence
of a function in
,
,
is then indicated by the notation
(implicit function) or by
,
or
(explicit function). Sometimes the letter
or
is used instead of
, so that
,
and
all mean the same thing, namely, that the value of
depends on the value of
in some way which is not stated.
We call the ratio "the differential
coefficient of
with respect to
." It is a solemn
scientific name for this very simple thing. But we are not going to be
frightened by solemn names, when the things themselves are so easy.
Instead of being frightened we will simply pronounce a brief curse on
the stupidity of giving long crack-jaw names; and, having relieved our
minds, will go on to the simple thing itself,[Pg 15]
namely the ratio
.
In ordinary algebra which you learned at school, you were always
hunting after some unknown quantity which you called or
;
or sometimes there were two unknown quantities to be hunted for
simultaneously. You have now to learn to go hunting in a new way; the
fox being now neither
nor
. Instead of this you have to
hunt for this curious cub called
. The process of
finding the value of
is called "differentiating."
But, remember, what is wanted is the value of this ratio when both
and
are themselves indefinitely small. The true value of
the differential coefficient is that to which it approximates in the
limiting case when each of them is considered as infinitesimally minute.
Let us now learn how to go in quest of .
[Pg 16]
It will never do to fall into the schoolboy error of thinking that
means
times
, for
is not a factor-it means "an
element of" or "a bit of" whatever follows. One reads
thus:
"dee-eks."
In case the reader has no one to guide him in such matters it may
here be simply said that one reads differential coefficients in the
following way. The differential coefficient
So also is read "dee-you by dee-tee." Second
differential coefficients will be met with later on. They are like this:
and it means that the operation of differentiating
with respect
to
has been (or has to be) performed twice over.
Another way of indicating that a function has been differentiated is by
putting an accent to the symbol of the function. Thus if ,
which means that
is some unspecified function of
(see p.
13), we may write
instead of
.
Similarly,
will mean that the original
function
has been differentiated twice over with respect to
.
[Pg 17]
NOW let us see how, on first principles, we can differentiate some simple algebraical expression.
Case 1.
Let us begin with the simple expression . Now remember
that the fundamental notion about the calculus is the idea of
growing. Mathematicians call it varying. Now as
and
are equal to one another, it is clear that if
grows,
will also grow. And if
grows, then
will
also grow. What we have got to find out is the proportion between the
growing of
and the growing of
. In other words our task is
to find out the ratio between
and
, or, in brief, to
find the value of
.
Let , then, grow a little bit bigger and become
;
similarly,
will grow a bit bigger and will become
.
Then, clearly, it will still be true that the enlarged
will be
equal to the square of the enlarged
. Writing this down, we have:
[Pg 18]
Doing the squaring we get:
What does mean? Remember that
meant a bit-a
little bit-of
. Then
will mean a little bit of
a little bit of
; that is, as explained above (p. 4), it is a
small quantity of the second order of smallness. It may therefore be
discarded as quite inconsiderable in comparison with the other terms.
Leaving it out, we then have:
Now ; so let us subtract this from the equation and we have
left
Dividing across by , we find
Now this[3] is what we set out to find. The ratio of the growing of
to the growing of
is, in the case before us, found to be
.
[Pg 19]
Numerical example.
Suppose and
. Then let
grow till
it becomes 101 (that is, let
). Then the enlarged
will
be
10,201. But if we agree that we may ignore
small quantities of the second order, 1 may be rejected as compared
with 10,000; so we may round off the enlarged
to 10,200.
has grown from 10,000 to 10,200; the bit added on is
, which is
therefore 200.
. According to
the algebra-working of the previous paragraph, we find
. And so it is; for
and
.
But, you will say, we neglected a whole unit.
Well, try again, making a still smaller bit.
Try . Then
, and
Now the last figure 1 is only one-millionth part of the 10,000, and is utterly negligible; so we may take 10,020 without the little decimal at the end.
And this makes ; and
, which is still the same as
.
Case 2.
Try differentiating in the same way.
We let grow to
, while
grows to
.
Then we have
Doing the cubing we obtain
[Pg 20]
Now we know that we may neglect small quantities of the second
and third orders; since, when and
are both made
indefinitely small,
and
will become
indefinitely smaller by comparison. So, regarding them as negligible,
we have left:
But ; and, subtracting this, we have:
Case 3.
Try differentiating . Starting as before by letting both
and
grow a bit, we have:
Working out the raising to the fourth power, we get
Then striking out the terms containing all the higher powers of ,
as being negligible by comparison, we have
Subtracting the original , we have left
[Pg 21]
Now all these cases are quite easy. Let us collect the results to see
if we can infer any general rule. Put them in two columns, the values
of in one and the corresponding values found for
in the other: thus
| y | |
Just look at these results: the operation of differentiating appears to
have had the effect of diminishing the power of by 1 (for example
in the last case reducing
to
), and at the same
time multiplying by a number (the same number in fact which originally
appeared as the power). Now, when you have once seen this, you might
easily conjecture how the others will run. You would expect that
differentiating
would give
, or differentiating
would give
. If you hesitate, try one of these,
and see whether the conjecture comes right.
Try .
Then
Neglecting all the terms containing small quantities of the higher
orders, we have left
[Pg 22]
Following out logically our observation, we should conclude that if we
want to deal with any higher power,—call it —we could tackle it
in the same way.
Let ,
then we should expect to find that
For example, let , then
; and differentiating it would
give
.
And, indeed, the rule that differentiating gives as the result
is true for all cases where
is a whole number and
positive. [Expanding
by the binomial theorem will at
once show this.] But the question whether it is true for cases where
has negative or fractional values requires further consideration.
Case of a negative power.
Let . Then proceed as before:
[Pg 23]
Expanding this by the binomial theorem (see p. 137), we get
So, neglecting the small quantities of higher orders of smallness, we
have:
Subtracting the original
, we find
And this is still in accordance with the rule inferred above.
Case of a fractional power.
Let . Then, as before,
Subtracting the original , and neglecting higher
powers we have left:
[Pg 24]
and
. Agreeing with the
general rule.
Summary. Let us see how far we have got. We have arrived at the
following rule: To differentiate , multiply by the power and
reduce the power by one, so giving us
as the result.
Exercises I. (See p. 252 for Answers.)
Differentiate the following:
(1)
(2)
(3)
(4)
(5)
(6)
(7)
(8)
(9)
(10)
You have now learned how to differentiate powers of . How easy
it is!
[3]
N.B.—This ratio is the
result of differentiating
with respect to
. Differentiating
means finding the differential coefficient. Suppose we had some
other function of
, as, for example,
. Then if
we were told to differentiate this with respect to
, we should
have to find
, or, what is the same thing,
. On the other hand, we
may have a case in which time was the independent variable (see p.
14), such as this:
. Then, if we were
told to differentiate it, that means we must find its differential
coefficient with respect to
. So that then our business
would be to try to find
, that is, to find
.
[Pg 25]
IN our equations we have regarded as growing, and as a
result of
being made to grow
also changed its value and
grew. We usually think of
as a quantity that we can vary; and,
regarding the variation of
as a sort of cause, we consider the
resulting variation of
as an effect. In other words, we
regard the value of
as depending on that of
. Both
and
are variables, but
is the one that we operate upon, and
is the "dependent variable." In all the preceding chapter we have
been trying to find out rules for the proportion which the dependent
variation in
bears to the variation independently made in
.
Our next step is to find out what effect on the process of
differentiating is caused by the presence of constants, that is,
of numbers which don't change when or
change their values.
Added Constants.
Let us begin with some simple case of an added constant, thus:
Let
Just as before, let us suppose
to grow to
and
to
grow to
.
[Pg 26]
Then:
Neglecting the small quantities of higher orders, this becomes
Subtract the original
, and we have left:
So the 5 has quite disappeared. It added nothing to the growth of
, and does not enter into the differential coefficient. If we
had put 7, or 700, or any other number, instead of 5, it would have
disappeared. So if we take the letter
, or
, or
to
represent any constant, it will simply disappear when we differentiate.
If the additional constant had been of negative value, such as -5 or
, it would equally have disappeared.
Multiplied Constants.
Take as a simple experiment this case:
Let .
Then on proceeding as before we get:
[Pg 27]
Then, subtracting the original , and neglecting the last
term, we have
Let us illustrate this example by working out the graphs of the
equations and
, by assigning to
a set of successive values, 0, 1, 2, 3, etc., and finding the
corresponding values of
and of
.
These values we tabulate as follows:
| 0 | 1 | 2 | 3 | 4 | 5 | -1 | -2 | -3 | |
| 0 | 7 | 28 | 63 | 112 | 175 | 7 | 28 | 63 | |
| 0 | 14 | 28 | 42 | 56 | 70 | -14 | -28 | -42 |
Now plot these values to some convenient scale, and we obtain the two curves, Figs. 6 and 6a.
Carefully compare the two figures, and verify by inspection that the
height of the ordinate of the derived curve, Fig. 6a, is proportional
to the slope of the original curve,[4] Fig. 6, at the corresponding
value of . To the left of the origin, where the original
curve slopes negatively (that is, downward from left to right) the
corresponding ordinates of the derived curve are negative.
Fig. 6.—Graph of .
Fig. 6a.—Graph of .
Now if we look back at p. 18, we shall see that simply differentiating
gives us
. So that the differential coefficient of
is just[Pg 28] 7 times as big as that of
. If we had
taken
, the differential coefficient would have come out
eight times as great as that of
. If we put
, we
shall get
If we had begun with , we should have had
. So that any mere multiplication by
a constant reappears as a mere multiplication when the thing is
differentiated. And, what is true about multiplication is equally true
about division: for if, in the example above, we had taken as the
constant
instead of 7, we should have had the same
come out in the result after differentiation.
Some Further Examples.
The following further examples, fully worked out, will enable you to master completely the process of differentiation as applied to ordinary [Pg 29] algebraical expressions, and enable you to work out by yourself the examples given at the end of this chapter.
(1) Differentiate .
is an added constant and vanishes (see p. 25).
We may then write at once
(2) Differentiate .
The term vanishes, being an added
constant; and as
, in the index form, is written
, we have
(3) If ,
find the differential coefficient of with respect
to
.
As a rule an expression of this kind will need a little more knowledge than we have acquired so far; it is, however, always worth while to try whether the expression can be put in a simpler form.
First we must try to bring it into the form some expression
involving
only.
The expression may be written
[Pg 30]
Squaring, we get
which simplifies to
or
that is
hence
(4) The volume of a cylinder of radius and height
is given
by the formula
. Find the rate of variation of volume
with the radius when
. and
.
If
, find the dimensions of the cylinder so that a change of 1
in. in radius causes a change of 400 cub. in. in the volume.
The rate of variation of with regard to
is
If and
this becomes
690.8. It means that a change of radius of 1 inch will cause a change
of volume of 690.8 cub. inch. This can be easily verified, for the
volumes with
and
are 1570 cub. in. and 2260.8 cub. in.
respectively, and
.
Also, if
[Pg 31]
(5) The reading of a Féry's Radiation pyrometer is related
to the Centigrade temperature
of the observed body by the relation
where
is the reading corresponding to a known
temperature
of the observed body.
Compare the sensitiveness of the pyrometer at temperatures
,
given that it read 25 when the temperature was
.
The sensitiveness is the rate of variation of the reading with the
temperature, that is . The formula may be
written
and we have
When and 1200, we get
and 0.1728 respectively.
The sensitiveness is approximately doubled from to
, and becomes three-quarters as great again up to
.
Exercises II. (See p. 252 for Answers.)
Differentiate the following:
(1) .
(2) .
[Pg 32]
(3) .
(4) .
(5) .
(6) .
Make up some other examples for yourself, and try your hand at differentiating them.
(7) If and
be the lengths of a rod of iron at the
temperatures
. and
.
respectively, then
. Find the change of
length of the rod per degree Centigrade.
(8) It has been found that if be the candle power of an
incandescent electric lamp, and
be the voltage,
,
where
and
are constants.
Find the rate of change of the candle power with the voltage, and
calculate the change of candle power per volt at 80,100 and 120 volts
in the case of a lamp for which and
.
(9) The frequency of vibration of a string of diameter
,
length
and specific gravity
, stretched with a force
, is given by
Find the rate of change of the frequency when and
are varied singly.
(10) The greatest external pressure which a tube can support
without collapsing is given by
[Pg 33]
where
and
are constants,
is the thickness of the
tube and
is its diameter. (This formula assumes that
is
small compared to
.)
Compare the rate at which varies for a small change of thickness
and for a small change of diameter taking place separately.
(11) Find, from first principles, the rate at which the following vary with respect to a change in radius:
(a) the circumference of a circle of radius ;
(b) the area of a circle of radius ;
(c) the lateral area of a cone of slant dimension ;
(d) the volume of a cone of radius and height
;
(e) the area of a sphere of radius ;
(f) the volume of a sphere of radius .
(12) The length of an iron rod at the temperature
being
given by
, where
is the length
at the temperature
, find the rate of variation of the diameter
of an iron tyre suitable for being shrunk on a wheel, when the
temperature
varies.
[Pg 34]
WE have learned how to differentiate simple algebraical
functions such as or
, and we have now to
consider how to tackle the sum of two or more functions.
For instance, let
what will its
be? How are we to go to work on this
new job?
The answer to this question is quite simple: just differentiate them,
one after the other, thus:
If you have any doubt whether this is right, try a more general case, working it by first principles. And this is the way.
Let , where
is any function of
, and
any
other function of
. Then, letting
increase to
will increase to
; and
will increase to
; and
to
.
And we shall have:
[Pg 35]
Subtracting the original , we get
and dividing through by
, we get:
This justifies the procedure. You differentiate each function
separately and add the results. So if now we take the example of the
preceding paragraph, and put in the values of the two functions, we
shall have, using the notation shown (p. 16),
exactly as before.
If there were three functions of , which we may call
and
, so that
As for subtraction, it follows at once; for if the function
had itself had a negative sign, its differential coefficient
would also be negative; so that by differentiating
[Pg 36]
But when we come to do with Products, the thing is not quite so simple.
Suppose we were asked to differentiate the expression
what are we to do? The result will certainly not be
;
for it is easy to see that neither
, nor
, would have been taken into that product.
Now there are two ways in which we may go to work.
First way. Do the multiplying first, and, having worked it out, then differentiate.
Accordingly, we multiply together and
.
This gives .
Now differentiate, and we get:
Second way. Go back to first principles, and consider the
equation
where
is one function of
, and
is any other function
of
. Then, if
grows to be
; and
to
;
and
becomes
, and
becomes
, we shall have:
[Pg 37]
Now is a small quantity of the second order of
smallness, and therefore in the limit may be discarded, leaving
Then, subtracting the original , we have left
and, dividing through by
, we get the result:
This shows that our instructions will be as follows: To differentiate the product of two functions, multiply each function by the differential coefficient of the other, and add together the two products so obtained.
You should note that this process amounts to the following: Treat
as constant while you differentiate
; then treat
as constant
while you differentiate
; and the whole differential coefficient
will be the sum of these two treatments.
Now, having found this rule, apply it to the concrete example which was considered above.
We want to differentiate the product
Call and
.
[Pg 38]
Then, by the general rule just established, we may write:
exactly as before.
Lastly, we have to differentiate quotients.
Think of this example, . In such a
case it is no use to try to work out the division beforehand, because
will not divide into
, neither have they any
common factor. So there is nothing for it but to go back to first
principles, and find a rule.
So we will put ;
where and
are two different functions of
the independent variable
. Then, when
becomes
will become
; and
will become
; and
will
become
. So then
[Pg 39]
Now perform the algebraic division, thus:
As both these remainders are small quantities of the second order, they may be neglected, and the division may stop here, since any further remainders would be of still smaller magnitudes.
So we have got:
which may be written
[Pg 40]
Now subtract the original , and we have left:
This gives us our instructions as to how to differentiate a quotient of two functions. Multiply the divisor function by the differential coefficient of the dividend function; then multiply the dividend function by the differential coefficient of the divisor function; and subtract. Lastly divide by the square of the divisor function.
Going back to our example ,
and
Then
The working out of quotients is often tedious, but there is nothing difficult about it.
Some further examples fully worked out are given hereafter.
[Pg 41]
(1) Differentiate .
Being a constant, vanishes, and we have
But ; so we get:
(2) Differentiate .
Putting in the index form, we get
Now
(3) Differentiate .
This may be written: .
The vanishes, and we have
or,
or,
[Pg 42]
(4) Differentiate .
A direct way of doing this will be explained later (see p. 66); but we can nevertheless manage it now without any difficulty.
Developing the cube, we get
hence
(5) Differentiate .
or, more simply, multiply out and then differentiate.
(6) Differentiate .
Same remarks as for preceding example.
(7) Differentiate .
[Pg 43]
This may be written
This, again, could be obtained more simply by multiplying the two factors first, and differentiating afterwards. This is not, however, always possible; see, for instance, p. 170, example 8, in which the rule for differentiating a product must be used.
(8) Differentiate .
(9) Differentiate .
(10) Differentiate .
[Pg 44]
In the indexed form, .
hence
(11) Differentiate
Now
(12) A reservoir of square cross-section has sides sloping at an angle
of with the vertical. The side of the bottom is 200
feet. Find an expression for the quantity pouring in or out when the
depth of water varies by 1 foot; hence find, in gallons, the quantity
withdrawn hourly when the depth is reduced from 14 to 10 feet in 24
hours.
The volume of a frustum of pyramid of height , and of bases
and
, is
. It is easily seen
that, the slope being
, if the depth be
, the length
of the side of the square surface of the water is
feet, so
that the volume of water is
[Pg 45]
cubic feet per foot of depth
variation. The mean level from 14 to 10 feet is 12 feet, when
,
, 176 cubic feet.
Gallons per hour corresponding to a change of depth of 4 ft. in 24
hours gallons.
(13) The absolute pressure, in atmospheres, , of saturated steam
at the temperature
. is given by Dulong as
being
as long as
is above
. Find the rate of variation of the pressure with the
temperature at
.
Expand the numerator by the binomial theorem (see p. 137).
hence
when
this becomes 0.036 atmosphere per degree Centigrade
change of temperature.
Exercises III. (See the Answers on p. 253.)
(1) Differentiate
(a) .
(b) .
(c) .
(d) .
[Pg 46]
(2) If , find
.
(3) Find the differential coefficient of
(4) Differentiate
(5) If , find
.
(6) Differentiate .
Find the differential coefficients of
(7) .
(8) .
(9) .
(10) .
(11) The temperature of the filament of an incandescent electric
lamp is connected to the current passing through the lamp by the
relation
Find an expression giving the variation of the current corresponding to a variation of temperature.
(12) The following formulae have been proposed to express the relation
between the electric resistance of a wire at the temperature
[Pg 47]
, and the resistance
of that same
wire at
Centigrade,
being constants.
Find the rate of variation of the resistance with regard to temperature as given by each of these formulae.
(13) The electromotive-force of a certain type of standard cell
has been found to vary with the temperature
according to the
relation
Find the change of electromotive-force per degree, at ,
and
.
(14) The electromotive-force necessary to maintain an electric arc of
length with a current of intensity
has been found by Mrs.
Ayrton to be
where
are constants.
Find an expression for the variation of the electromotive-force (a) with regard to the length of the arc; (b) with regard to the strength of the current.
[Pg 48]
LET us try the effect of repeating several times over the operation of differentiating a function (see p. 13). Begin with a concrete case.
Let .
There is a certain notation, with which we are already acquainted (see
p. 14), used by some writers, that is very convenient. This is to
employ the general symbol for any function of
. Here the
symbol
is read as "function of," without saying what particular
function is meant. So the statement
merely tells us that
is a function of
, it may be
or
, or
or any other complicated function of
.
[Pg 49]
The corresponding symbol for the differential coefficient is
, which is simpler to write than
.
This is called the "derived function" of
.
Suppose we differentiate over again, we shall get the "second derived
function" or second differential coefficient, which is denoted by
; and so on.
Now let us generalize.
Let .
But this is not the only way of indicating successive differentiations.
For,
and this is more conveniently written as
,
or more usually
.
Similarly, we may write as the result of
thrice differentiating, .
[Pg 50]
Examples.
Now let us try .
In a similar manner if ,
Exercises IV. (See page 253 for Answers.)
Find and
for the
following expressions:
(1) .
(2) .
(3) .
[Pg 51]
(4) Find the 2nd and 3rd derived functions in the Exercises III. (p. 45), No. 1 to No. 7, and in the Examples given (p. 40), No. 1 to No. 7.
[Pg 52]
SOME of the most important problems of the calculus are those where time is the independent variable, and we have to think about the values of some other quantity that varies when the time varies. Some things grow larger as time goes on; some other things grow smaller. The distance that a train has got from its starting place goes on ever increasing as time goes on. Trees grow taller as the years go by. Which is growing at the greater rate; a plant 12 inches high which in one month becomes 14 inches high, or a tree 12 feet high which in a year becomes 14 feet high?
In this chapter we are going to make much use of the word rate. Nothing to do with poor-rate, or water-rate (except that even here the word suggests a proportion—a ratio—so many pence in the pound). Nothing to do even with birth-rate or death-rate, though these words suggest so many births or deaths per thousand of the population. When a motor-car whizzes by us, we say: What a terrific rate! When a spendthrift is flinging about his money, we remark that that young man is living at a prodigious rate. What do we mean by rate? In both these cases we are making a mental comparison of something that is happening, and the length of time that it takes to happen. If the[Pg 53] motor-car flies past us going 10 yards per second, a simple bit of mental arithmetic will show us that this is equivalent—while it lasts—to a rate of 600 yards per minute, or over 20 miles per hour.
Now in what sense is it true that a speed of 10 yards per second is the same as 600 yards per minute? Ten yards is not the same as 600 yards, nor is one second the same thing as one minute. What we mean by saying that the rate is the same, is this: that the proportion borne between distance passed over and time taken to pass over it, is the same in both cases.
Take another example. A man may have only a few pounds in his
possession, and yet be able to spend money at the rate of millions a
year-provided he goes on spending money at that rate for a few minutes
only. Suppose you hand a shilling over the counter to pay for some
goods; and suppose the operation lasts exactly one second. Then, during
that brief operation, you are parting with your money at the rate of 1
shilling per second, which is the same rate as per minute, or
per hour, or
per day, or
per year!
If you have
in your pocket, you can go on spending money at
the rate of a million a year for just
minutes.
It is said that Sandy had not been in London above five minutes when
"bang went sixpence." If he were to spend money at that rate all day
long, say for 12 hours, he would be spending 6 shillings an hour, or
per day, or
a week, not counting the
Sawbbath.
Now try to put some of these ideas into differential notation.
Let in this case stand for money, and let
stand for time.
If you are spending money, and the amount you spend in a short
[Pg 54]
time be called
, the rate of spending it will
be
, or rather, should be written with a minus
sign, as
, because
is a decrement, not an
increment. But money is not a good example for the calculus, because
it generally comes and goes by jumps, not by a continuous flow-you may
earn
a year, but it does not keep running in all day long in
a thin stream; it comes in only weekly, or monthly, or quarterly, in
lumps: and your expenditure also goes out in sudden payments.
A more apt illustration of the idea of a rate is furnished by the
speed of a moving body. From London (Euston station) to Liverpool
is 200 miles. If a train leaves London at 7 o'clock, and reaches
Liverpool at 11 o'clock, you know that, since it has travelled 200
miles in 4 hours, its average rate must have been 50 miles per hour;
because . Here you are really making a
mental comparison between the distance passed over and the time taken
to pass over it. You are dividing one by the other. If
is the
whole distance, and
the whole time, clearly the average rate is
. Now the speed was not actually constant all the way:
at starting, and during the slowing up at the end of the journey, the
speed was less. Probably at some part, when running downhill, the speed
was over 60 miles an hour. If, during any particular element of time
, the corresponding element of distance passed over was
,
then at that part of the journey the speed was
.
The rate at which one quantity (in the present instance,
distance) is changing in relation to the other quantity (in
this case, time) is properly expressed, then, by stating
the differential coefficient of one with respect to the other. A
velocity, scientifically expressed, is the rate at which a very
small distance in any given direction is being passed over; and may
therefore[Pg 55] be written
But if the velocity is not uniform, then it must be either
increasing or else decreasing. The rate at which a velocity is
increasing is called the acceleration. If a moving body is, at
any particular instant, gaining an additional velocity
in an
element of time
, then the acceleration
at that instant
may be written
but
is itself
. Hence we may
put
and this is usually written
; or the
acceleration is the second differential coefficient of the distance,
with respect to time. Acceleration is expressed as a change of velocity
in unit time, for instance, as being so many feet per second per
second; the notation used being feet
.
When a railway train has just begun to move, its velocity is
small; but it is rapidly gaining speed-it is being hurried up, or
accelerated, by the effort of the engine. So its
is large. When it has got up its top speed it is no longer being
accelerated, so that then
has fallen to
zero. But when it nears its stopping place its speed begins to slow
down; may, indeed, slow down very quickly if the brakes are put on,
[Pg 56]
and during this period of deceleration or slackening of pace,
the value of
, that is, of
will be negative.
To accelerate a mass requires the continuous application of
force. The force necessary to accelerate a mass is proportional to the
mass, and it is also proportional to the acceleration which is being
imparted. Hence we may write for the force
, the expression
The product of a mass by the speed at which it is going is called
its momentum, and is in symbols . If we differentiate
momentum with respect to time we shall get
for the rate of change of momentum. But, since
is a constant
quantity, this may be written
, which we see
above is the same as
. That is to say, force may be expressed
either as mass times acceleration, or as rate of change of momentum.
Again, if a force is employed to move something (against an equal and
opposite counter-force), it does work; and the amount of work done is
measured by the product of the force into the distance (in its own
direction) through which its point of application moves forward. So
if a force moves forward through a length
, the work done
(which we may call
) will be
where we take
as a constant force. If the force varies at
different parts of the range
, then we must find an expression for
its value from [Pg 57]point to point. If
be the force along the small
element of length
, the amount of work done will be
.
But as
is only an element of length, only an element of
work will be done. If we write
for work, then an element of work
will be
; and we have
which may be written
Further, we may transpose the expression and write
This gives us yet a third definition of force; that if it is being used to produce a displacement in any direction, the force (in that direction) is equal to the rate at which work is being done per unit of length in that direction. In this last sentence the word rate is clearly not used in its time-sense, but in its meaning as ratio or proportion.
Sir Isaac Newton, who was (along with Leibnitz) an inventor of the
methods of the calculus, regarded all quantities that were varying
as flowing; and the ratio which we nowadays call the differential
coefficient he regarded as the rate of flowing, or the
fluxion of the quantity in question. He did not use the notation
of the and
, and
(this was due to Leibnitz), but
had instead a notation of his own. If
was a quantity[Pg 58]
that varied, or "flowed," then his symbol for its rate of variation
(or "fluxion") was
. If
was the variable, then its
fluxion was called
. The dot over the letter indicated that
it had been differentiated. But this notation does not tell us what
is the independent variable with respect to which the differentiation
has been effected. When we see
we know that
is to be differentiated with respect to
. If we see
we know that
is to be differentiated with respect
to
. But if we see merely
, we cannot tell without
looking at the context whether this is to mean
or
or
, or what is the other
variable. So, therefore, this fluxional notation is less informing than
the differential notation, and has in consequence largely dropped out
of use. But its simplicity gives it an advantage if only we will agree
to use it for those cases exclusively where time is the independent
variable. In that case
will mean
and
will mean
; and
will mean
.
Adopting this fluxional notation we may write the mechanical equations considered in the paragraphs above, as follows:
Examples.
(1) A body moves so that the distance (in feet), which it
travels from a certain point
, is given by the relation
, where
is the time in seconds elapsed since a
certain instant. Find the velocity[Pg 59]
and acceleration 5 seconds after the body began to move, and also find
the corresponding values when the distance covered is 100 feet. Find
also the average velocity during the first 10 seconds of its motion.
(Suppose distances and motion to the right to be positive.)
Now
When and
. The body started from a point 10.4
feet to the right of the point
; and the time was reckoned from
the instant the body started.
When .
When , or
, and
;
.
When ,
(It is the same velocity as the velocity at the middle of the interval,
; for, the acceleration being constant, the velocity has varied
uniformly from zero when
to
when
.)
(2) In the above problem let us suppose
When and
, the time
is reckoned from the instant at which the body passed a point 10.4 ft.
from the point
,[Pg 60]
its velocity being then already
. To
find the time elapsed since it began moving, let
; then
. The body began moving 7.5
sec. before time was begun to be observed; 5 seconds after this gives
and
.
When ,
hence
.
To find the distance travelled during the 10 first seconds of the
motion one must know how far the body was from the point when it
started.
When ,
that is 0.85 ft. to the left of the point
.
Now, when ,
So, in 10 seconds, the distance travelled was , and
(3) Consider a similar problem when the distance is given by
. Then
constant. When
,
as before, and
; so that the body was moving in
the direction opposite to its motion in the previous cases. As the
acceleration is positive, however, we see that this velocity will
[Pg 61]
decrease as time goes on, until it becomes zero, when
or
; or
. After this, the velocity becomes
positive; and 5 seconds after the body started,
, and
When ,
When is zero,
,
informing us that the body moves back to 0.85 ft. beyond the point
before it stops. Ten seconds later
The distance travelled , and the average velocity is
again 2 ft./sec.
(4) Consider yet another problem of the same sort with . The acceleration is no more
constant.
When . The body is at rest, but just ready to
move with a negative acceleration, that is to gain a velocity towards
the point
.
(5) If we have , then
, and
.
When .
The body is moving towards the point with a velocity of
, and just at that instant the velocity
is uniform.
[Pg 62]
We see that the conditions of the motion can always be at once ascertained from the time-distance equation and its first and second derived functions. In the last two cases the mean velocity during the first 10 seconds and the velocity 5 seconds after the start will no more be the same, because the velocity is not increasing uniformly, the acceleration being no longer constant.
(6) The angle (in radians) turned through by a wheel is
given by
, where
is the time in seconds
from a certain instant; find the angular velocity
and the
angular acceleration
, (a) after 1 second; (b)
after it has performed one revolution. At what time is it at rest, and
how many revolutions has it performed up to that instant?
Writing for the acceleration
When .
When ,
This is a retardation; the wheel is slowing down.
After 1 revolution
By plotting the graph, , we can get the value
or values of
for which
; these are 2.11 and 3.03
(there is a third negative value).
[Pg 63]
When ,
When ,
The velocity is reversed. The wheel is evidently at rest between these
two instants; it is at rest when , that is when
,
or when
, it has performed
Exercises V. (See page 255 for Answers.)
(1) If ; find
and
.
(2) A body falling freely in space describes in seconds a space
, in feet, expressed by the equation
. Draw a curve
showing the relation between
and
. Also determine the
velocity of the body at the following times from its being let drop:
seconds;
seconds;
second.
(3) If ; find
and
.
[Pg 64]
(4) If a body move according to the law
find its velocity when
seconds;
being in feet.
(5) Find the acceleration of the body mentioned in the preceding
example. Is the acceleration the same for all values of ?
(6) The angle (in radians) turned through by a revolving
wheel is connected with the time
(in seconds) that has elapsed
since starting; by the law
Find the angular velocity (in radians per second) of that wheel
when seconds have elapsed. Find also its angular
acceleration.
(7) A slider moves so that, during the first part of its motion, its
distance in inches from its starting point is given by the
expression
Find the expression for the velocity and the acceleration at any time; and hence find the velocity and the acceleration after 3 seconds.
(8) The motion of a rising balloon is such that its height , in
miles, is given at any instant by the expression
;
being in seconds.
Find an expression for the velocity and the acceleration at any time. Draw curves to show the variation of height, velocity and acceleration during the first ten minutes of the ascent.
[Pg 65]
(9) A stone is thrown downwards into water and its depth in
metres at any instant
seconds after reaching the surface of the
water is given by the expression
Find an expression for the velocity and the acceleration at any time. Find the velocity and acceleration after 10 seconds.
(10) A body moves in such a way that the spaces described in the time
from starting is given by
, where
is a constant.
Find the value of
when the velocity is doubled from the 5th to
the 10th second; find it also when the velocity is numerically equal to
the acceleration at the end of the 10th second.
[Pg 66]
SOMETIMES one is stumped by finding that the expression to be differentiated is too complicated to tackle directly.
Thus, the equation
is awkward to a beginner.
Now the dodge to turn the difficulty is this: Write some symbol, such
as , for the expression
; then the equation becomes
which you can easily manage; for
Then tackle the expression
and differentiate it with respect to
,
[Pg 67]
Then all that remains is plain sailing;
that is,
and so the trick is done.
By and bye, when you have learned how to deal with sines, and cosines, and exponentials, you will find this dodge of increasing usefulness.
Examples.
Let us practise this dodge on a few examples.
(1) Differentiate .
Let .
(2) Differentiate .
Let .
[Pg 68]
(3) Differentiate .
Let .
(4) Differentiate .
Let .
(5) Differentiate .
Write this as .
(We may also write
and
differentiate as a product.)
Proceeding as in example (1) above, we get
[Pg 69]
Hence
or
(6) Differentiate .
We may write this
Differentiating , as shown in
example (2) above, we get
so that
(7) Differentiate .
Let .
[Pg 70]
Now let
and
.
Hence ,
(8) Differentiate .
We get
Let
and
.
Let
and
.
[Pg 71]
Hence
(9) Differentiate with respect to
.
(10) Find the first and second differential coefficients of
.
Let and let
; then
.
Hence
[Pg 72]
Now
(We shall need these two last differential coefficients later on. See
Ex. X. No. 11.)
Exercises VI. (See page 255 for Answers.)
Differentiate the following:
(1) .
(2) .
(3) .
(4) .
(5) .
(6) .
(7) .
(8) Differentiate with respect to
.
(9) Differentiate .
The process can be extended to three or more differential coefficients,
so that .
[Pg 73]
Examples.
(1) If , find
.
We have
(2) If ,
find
.
Hence
an expression in which
must be replaced by its value,
and
by its value in terms of
.
(3) If
and
, find
.
We get
(see example 5, p. 68); and
So that .
Replace now first , then
by its value.
[Pg 74]
Exercises VII. You can now successfully try the following. (See page 256 for Answers.)
(1) If
and
, find
.
(2) If
and
, find
.
(3) If
and
, find
.
[Pg 75]
IT is useful to consider what geometrical meaning can be given to the differential coefficient.
In the first place, any function of , such, for example, as
, or
, or
, can be plotted as a
curve; and nowadays every schoolboy is familiar with the process of
curve-plotting.
Fig. 7.
Let , in Fig. 7, be a portion of a curve plotted with respect
to the axes of coordinates
and
. Consider any point
on this curve, where the abscissa of the point is
and its
ordinate is
. Now observe how
changes when
is varied.
If
is made to increase by a small increment
, to the
right, it will be observed that
also (in this particular
curve) increases by[Pg 76] a small increment
(because this particular
curve happens to be an ascending curve). Then the ratio of
to
is a measure of the degree to which the curve is sloping
up between the two points
and
. As a matter of fact, it
can be seen on the figure that the curve between
and
has
many different slopes, so that we cannot very well speak of the slope
of the curve between
and
. If, however,
and
are so near each other that the small portion
of the curve is
practically straight, then it is true to say that the ratio
is the slope of the curve along
. The straight line
produced on either side touches the curve along the portion
only, and if this portion is indefinitely small, the straight line
will touch the curve at practically one point only, and be therefore a
tangent to the curve.
This tangent to the curve has evidently the same slope as , so
that
is the slope of the tangent to the curve at
the point
for which the value of
is found.
We have seen that the short expression "the slope of a curve" has no precise meaning, because a curve has so many slopes-in fact, every small portion of a curve has a different slope. "The slope of a curve at a point" is, however, a perfectly defined thing; it is the slope of a very small portion of the curve situated just at that point; and we have seen that this is the same as "the slope of the tangent to the curve at that point."
Observe that is a short step to the right, and
the
corresponding short step upwards. These steps must be considered as
[Pg 77]
short as possible—in fact indefinitely short,—though in diagrams
we have to represent them by bits that are not infinitesimally small,
otherwise they could not be seen.
We shall hereafter make considerable use of this circumstance
that represents the slope of the curve at
any point.
Fig. 8.
If a curve is sloping up at at a particular point, as in
Fig. 8,
and
will be equal, and the value of
.
If the curve slopes up steeper than (Fig. 9),
will be greater than 1.
If the curve slopes up very gently, as in Fig. 10,
will be a fraction smaller than 1.
For a horizontal line, or a horizontal place in a curve, , and
therefore
.
If a curve slopes downward, as in Fig. 11, will be a
step down, and must therefore be reckoned of negative value; hence
will have negative sign also.
[Pg 78]
Fig. 9.
Fig. 10.
If the "curve" happens to be a straight line, like that in Fig. 12, the
value of will be the same at all points along it.
In other words its slope is constant.
If a curve is one that turns more upwards as it goes along to the
right, the values of will become greater and
greater with the increasing steepness, as in Fig. 13.
Fig. 11.
If a curve is one that gets flatter and flatter as it goes along, the
values of will become smaller and smaller as the
flatter part is reached, as in Fig. 14.
[Pg 79]
Fig. 12.
Fig. 13.
If a curve first descends, and then goes up again, as in Fig. 15,
presenting a concavity upwards, then clearly will
first be negative, with diminishing values as the curve flattens, then
will be zero at the point where the bottom of the trough of the curve
is reached; and from this point onward
will have
positive values that go on increasing. In such a case
is said to
pass by a minimum.
Fig. 14.
Fig. 15.
The minimum value of is not necessarily the
smallest value of
, it is that value of
corresponding to the
bottom of the trough; for instance, in Fig. 28 (p. 99), the value of
corresponding to the bottom of the trough is 1, while
takes
[Pg 80]elsewhere values which are smaller than this. The characteristic of a
minimum is that
must increase on either side of it.
N.B.—For the particular value of that makes
a
minimum, the value of
.
If a curve first ascends and then descends, the values of
will be positive at first; then zero, as the summit is
reached; then negative, as the curve slopes downwards, as in Fig. 16.
In this case
is said to pass by a maximum, but the maximum
value of
is not necessarily the greatest value of
. In Fig.
28, the maximum of
is
, but this is by no means
the greatest value
can have at some other point of the curve.
N.B.—For the particular value of that makes
a
maximum, the value of
.
If a curve has the peculiar form of Fig. 17, the values of
will always be positive; but there will be one
particular place where the slope is least steep, where the value of
will be a minimum; that is, less than it is at any
other part of the curve.
[Pg 81]
Fig. 16.
Fig. 17.
If a curve has the form of Fig. 18, the value of
will be negative in the upper part, and positive in the lower part;
while at the nose of the curve where it becomes actually perpendicular,
the value of
will be infinitely great.
Fig. 18.
Now that we understand that measures the steepness
of a curve at any point, let us turn to some of the equations which we
have already learned how to differentiate.
[Pg 82]
(1) As the simplest case take this:
It is plotted out in Fig. 19, using equal scales for and
.
If we put
, then the corresponding ordinate will be
;
that is to say, the "curve" crosses the
-axis at the height
.
From here it ascends at
; for whatever values we give to
to the right, we have an equal
to ascend. The line has a
gradient of 1 in 1.
Fig. 19.
Fig. 20.
Now differentiate , by the rules we have already learned (pp.
21 and 25 ante), and we get
.
The slope of the line is such that for every little step to the
right, we go an equal little step
upward. And this slope is
constant-always the same slope.
(2) Take another case:
[Pg 83]
We know that this curve, like the preceding one, will start from a
height on the
-axis. But before we draw the curve, let us
find its slope by differentiating; which gives
.
The slope will be constant, at an angle, the tangent of which is
here called
. Let us assign to
some numerical value—say
. Then we must give it such a slope that it ascends 1
in 3; or
will be 3 times as great as
; as magnified in
Fig. 21. So, draw the line in Fig. 20 at this slope.
Fig. 21.
(3) Now for a slightly harder case.
Let
Again the curve will start on the -axis at a height
above
the origin.
Now differentiate. [If you have forgotten, turn back to p. 25; or, rather, don't turn back, but think out the differentiation.]
This shows that the steepness will not be constant: it increases as
increases. At the starting point
, where
, the curve
(Fig. 22) has no steepness—that is, it is level. On the left of the
origin, where
has negative values,
will also
have negative values, or will descend from left to right, as in the
Figure.
[Pg 84]
Fig. 22.
Let us illustrate this by working out a particular instance. Taking the
equation
and differentiating it, we get
Now assign a few successive values, say from 0 to 5, to ; and
calculate the corresponding values of
by the first equation; and
of
from the second equation. Tabulating results, we
have:
| 0 | 1 | 2 | 3 | 4 | 5 | |
| 3 | 4 | 7 | ||||
| 0 | 1 | 2 |
Then plot them out in two curves, Figs. 23 and 24, in Fig. 23 plotting
the values of against those of
and in Fig. 24 those of
against those of
. For [Pg 85]any assigned value
of
, the height of the ordinate in the second curve is
proportional to the slope of the first curve.
Fig. 23.
Fig. 24.
If a curve comes to a sudden cusp, as in Fig. 25, the slope at that
point suddenly changes from a slope upward to a slope downward. In
that case will clearly undergo an abrupt change
from a positive to a negative value.
Fig. 25.
The following examples show further applications of the principles just explained.
[Pg 86]
(4) Find the slope of the tangent to the curve
at the point where
. Find the angle which this tangent makes
with the curve
.
The slope of the tangent is the slope of the curve at the point where
they touch one another (see p. 76); that is, it is the
of the curve for that point. Here
and for
, which is
the slope of the tangent and of the curve at that point. The tangent,
being a straight line, has for equation
, and its slope is
, hence
. Also if
; and as the tangent passes by
this point, the coordinates of the point must satisfy the equation of
the tangent, namely
so that
and
; the
equation of the tangent is therefore
.
Now, when two curves meet, the intersection being a point common to
both curves, its coordinates must satisfy the equation of each one
of the two curves; that is, it must be a solution of the system of
simultaneous equations formed by coupling together the equations of
the curves. Here the curves meet one another at points given by the
solution of
[Pg 87]
that is,
This equation has for its solutions and
.
The slope of the curve
at any point is
For the point where , this slope is zero; the curve is
horizontal. For the point where
hence the curve at that point slopes downwards to the right at such an
angle
with the horizontal that
; that is,
at
to the horizontal.
The slope of the straight line is ; that is, it
slopes downwards to the right and makes with the horizontal an angle
such that
; that is, an angle of
. It follows that at the first point the
curve cuts the straight line at an angle of
,
while at the second it cuts it at an angle of
.
(5) A straight line is to be drawn, through a point whose coordinates
are , as tangent to the curve
. Find the
coordinates of the point of contact.
The slope of the tangent must be the same as the
of the curve; that is,
.
The equation of the straight line is , and as it is
satisfied for the values
, then
; also,
its
.
The and the
of the point of contact must also satisfy both
the equation of the tangent and the equation of the curve.
[Pg 88]
We have then
four equations in
.
Equations (i) and (ii) give .
Replacing and
by their value in this, we get
which simplifies to
, the solutions of which are:
and
. Replacing in (i), we get
and
respectively; the two points of contact are then
,
, and
,
.
Note.—In all exercises dealing with curves, students will find it extremely instructive to verify the deductions obtained by actually plotting the curves.
Exercises VIII. (See page 256 for Answers.)
(1) Plot the curve , using a scale of
millimetres. Measure at points corresponding to different values of
, the angle of its slope.
Find, by differentiating the equation, the expression for slope; and see, from a Table of Natural Tangents, whether this agrees with the measured angle.
[Pg 89]
(2) Find what will be the slope of the curve
at the particular point that has as abscissa
.
(3) If , show that at the particular point of
the curve where
will have the value
.
(4) Find the of the equation
; and
calculate the numerical values of
for the points
corresponding to
,
,
.
(5) In the curve to which the equation is , find the
values of
at those points where the slope
.
(6) Find the slope, at any point, of the curve whose equation is
; and give the numerical
value of the slope at the place where
, and at that where
.
(7) The equation of a tangent to the curve , being
of the form
, where
and
are constants, find the
value of
and
if the point where the tangent touches the
curve has
for abscissa.
(8) At what angle do the two curves
cut one another?
(9) Tangents to the curve are drawn at
points for which
and
. Find the coordinates of the point
of intersection of the tangents and their mutual inclination.
[Pg 90]
(10) A straight line touches a curve
at one
point. What are the coordinates of the point of contact, and what is
the value of
?
[Pg 91]
ONE of the principal uses of the process of differentiating is to find out under what conditions the value of the thing differentiated becomes a maximum, or a minimum. This is often exceedingly important in engineering questions, where it is most desirable to know what conditions will make the cost of working a minimum, or will make the efficiency a maximum.
Now, to begin with a concrete case, let us take the equation
By assigning a number of successive values to , and finding the
corresponding values of
, we can readily see that the equation
represents a curve with a minimum.
| 0 | 1 | 2 | 3 | 4 | 5 | |
| 7 | 4 | 3 | 4 | 7 | 12 |
These values are plotted in Fig. 26, which shows that has
apparently a minimum value of 3, when
is made equal to 2.
But are you sure that the minimum occurs at 2, and not at
or at
?
[Pg 92]
Fig. 26.
Of course it would be possible with any algebraic expression to work out a lot of values, and in this way arrive gradually at the particular value that may be a maximum or a minimum.
Fig. 27.
Here is another example:
Let
[Pg 93]
Calculate a few values thus:
| -1 | 0 | 1 | 2 | 3 | 4 | 5 | |
| -4 | 0 | 2 | 2 | 0 | -4 | -10 |
Plot these values as in Fig. 27.
It will be evident that there will be a maximum somewhere between
and
; and the thing looks as if the maximum value
of
ought to be about
. Try some intermediate
values. If
; if
;
if
. How can we be sure that 2.25 is the
real maximum, or that it occurs exactly when
?
Now it may sound like juggling to be assured that there is a way by
which one can arrive straight at a maximum (or minimum) value without
making a lot of preliminary trials or guesses. And that way depends
on differentiating. Look back to an earlier page (78) for the remarks
about Figs. 14 and 15, and you will see that whenever a curve gets
either to its maximum or to its minimum height, at that point its
. Now this gives us the clue to the dodge that is
wanted. When there is put before you an equation, and you want to find
that value of
that will make its
a minimum (or a maximum),
first differentiate it, and having done so, write its
as equal to zero, and then solve for
.
Put this particular value of
into the original equation, and you
will then get the required value of
. This process is commonly
called "equating to zero."
To see how simply it works, take the example with which this chapter
opens, namely
[Pg 94]
Differentiating, we get:
Now equate this to zero, thus:
Solving this equation for
, we get:
Now, we know that the maximum (or minimum) will occur exactly when
.
Putting the value into the original equation, we get
Now look back at Fig. 26, and you will see that the minimum occurs when
, and that this minimum of
.
Try the second example (Fig. 24), which is
Differentiating, .
Equating to zero,
[Pg 95]
and putting this value of
into the original equation, we find:
This gives us exactly the information as to which the method of trying
a lot of values left us uncertain.
Now, before we go on to any further cases, we have two remarks to make.
When you are told to equate to zero, you feel at
first (that is if you have any wits of your own) a kind of resentment,
because you know that
has all sorts of different
values at different parts of the curve, according to whether it is
sloping up or down. So, when you are suddenly told to write
you resent it, and feel inclined to say that it can't be true. Now
you will have to understand the essential difference between "an
equation," and "an equation of condition." Ordinarily you are dealing
with equations that are true in themselves, but, on occasions, of which
the present are examples, you have to write down equations that are not
necessarily true, but are only true if certain conditions are to be
fulfilled; and you write them down in order, by solving them, to find
the conditions which make them true. Now we want to find the particular
value that
has when the curve is neither sloping up nor sloping
down, that is, at the particular place where
.
So, writing
does not mean that it always
is
; but you write it down as a condition in order to see
how much
will come out if
is to be zero.
[Pg 96]
The second remark is one which (if you have any wits of your own)
you will probably have already made: namely, that this much-belauded
process of equating to zero entirely fails to tell you whether the
that you thereby find is going to give you a maximum value of
or a minimum value of
. Quite so. It does not of itself
discriminate; it finds for you the right value of
but leaves you
to find out for yourselves whether the corresponding
is a maximum
or a minimum. Of course, if you have plotted the curve, you know
already which it will be.
For instance, take the equation:
Without stopping to think what curve it corresponds to, differentiate
it, and equate to zero:
whence
and, inserting this value,
will be either a maximum or else a minimum. But which? You will
hereafter be told a way, depending upon a second differentiation, (see
Chap. XII., p. 109). But at present it is enough if you will simply try
any other value of
differing a little from the one found, and see
whether with this altered value the corresponding value of
is
less or greater than that already found.
[Pg 97]
Try another simple problem in maxima and minima. Suppose you were asked to divide any number into two parts, such that the product was a maximum? How would you set about it if you did not know the trick of equating to zero? I suppose you could worry it out by the rule of try, try, try again. Let 60 be the number. You can try cutting it into two parts, and multiplying them together. Thus, 50 times 10 is 500; 52 times 8 is 416; 40 times 20 is 800; 45 times 15 is 675; 30 times 30 is 900. This looks like a maximum: try varying it. 31 times 29 is 899, which is not so good; and 32 times 28 is 896, which is worse. So it seems that the biggest product will be got by dividing into two equal halves.
Now see what the calculus tells you. Let the number to be cut into two
parts be called . Then if
is one part, the other will be
, and the product will be
or
. So we
write
. Now differentiate and equate to zero;
Solving for
, we get
.
So now we know that whatever number may be, we must divide
it into two equal parts if the product of the parts is to be a maximum;
and the value of that maximum product will always be
.
This is a very useful rule, and applies to any number of factors, so
that if a constant number,
is a
maximum when
.
[Pg 98]
Test Case.
Let us at once apply our knowledge to a case that we can test.
Let
and let us find whether this function has a maximum or minimum; and if
so, test whether it is a maximum or a minimum.
Differentiating, we get
Equating to zero, we get
whence
or
That is to say, when is made
, the corresponding
value of
will be either a maximum or a minimum. Accordingly,
putting
in the original equation, we get
Is this a maximum or a minimum? To test it, try putting a little
bigger than
,—say make
. Then
which is higher up than -0.25; showing that
is a
minimum.
Plot the curve for yourself, and verify the calculation.
[Pg 99]
Further Examples.
A most interesting example is afforded by a curve that has both a
maximum and a minimum. Its equation is:
Now
Fig. 28.
Equating to zero, we get the quadratic,
and solving the quadratic gives us two roots, viz.
[Pg 100]
Now, when ; and when
. The first
of these is a minimum, the second a maximum.
The curve itself may be plotted (as in Fig. 28) from the values calculated, as below, from the original equation.
| -1 | 0 | 1 | 2 | 3 | 4 | 5 | 6 | |
| 1 | 1 | 19 |
A further exercise in maxima and minima is afforded by the following example:
The equation to a circle of radius , having its centre
at
the point whose coordinates are
, as depicted in Fig. 29,
is:
Fig. 29.
This may be transformed into
[Pg 101]
Now we know beforehand, by mere inspection of the figure, that when
,
will be either at its maximum value,
, or else
at its minimum value,
. But let us not take advantage of this
knowledge; let us set about finding what value of
will make
a maximum or a minimum, by the process of differentiating and equating
to zero.
which reduces to
Then the condition for being maximum or minimum is:
Since no value whatever of will make the denominator infinite,
the only condition to give zero is
Inserting this value in the original equation for the circle, we find
and as the root of
is either
or
, we have two
resulting values of
,
[Pg 102]
The first of these is the maximum, at the top; the second the minimum, at the bottom.
If the curve is such that there is no place that is a maximum or minimum, the process of equating to zero will yield an impossible result. For instance:
Let
Then
Equating this to zero, we get ,
Therefore
has no maximum nor minimum.
A few more worked examples will enable you to thoroughly master this most interesting and useful application of the calculus.
(1) What are the sides of the rectangle of maximum area inscribed in a
circle of radius ?
If one side be called ,
and as the diagonal of the rectangle is necessarily a diameter, the
other side
.
Then, area of rectangle ,
If you have forgotten how to differentiate ,
here is a hint: write
and
, and seek
and
; fight it out, and only
if you can't get on refer to page 66.
[Pg 103]
You will get
For maximum or minimum we must have
that is,
and
.
The other side ; the two sides
are equal; the figure is a square the side of which is equal to the
diagonal of the square constructed on the radius. In this case it is,
of course, a maximum with which we are dealing.
(2) What is the radius of the opening of a conical vessel the sloping
side of which has a length when the capacity of the vessel is
greatest?
If be the radius and
the corresponding height,
.
Proceeding as in the previous problem, we get
for maximum or minimum.
Or, , and
, for a maximum, obviously.
(3) Find the maxima and minima of the function
[Pg 104]
We get
for maximum or minimum; or
There is only one value, hence only one maximum or minimum.
it is therefore a minimum. (It is instructive to plot the graph of the
function.)
(4) Find the maxima and minima of the function . (It will be found instructive to plot the graph.)
Differentiating gives at once (see example No. 1, p. 67)
for maximum or minimum.
Hence and
, the only solution. For
.
For , so this is a maximum.
(5) Find the maxima and minima of the function
[Pg 105]
We have
for maximum or minimum; or
or
; which has for solutions
These being imaginary, there is no real value of for which
; hence there is neither maximum nor minimum.
(6) Find the maxima and minima of the function
This may be written .
that is,
,
which is satisfied for
, and for
, that is for
. So there are
two solutions.
Taking first . If
,
and if
. On one side
is
imaginary; that is, there is no value of
that can be represented
by a graph; the latter is therefore entirely on the right side of the
axis of
(see Fig. 30).
On plotting the graph it will be found that the curve goes to the
origin, as if there were a minimum there; but instead of continuing
beyond, as it should do for a minimum, it retraces its steps (forming
[Pg 106]
what is called a "cusp"). There is no minimum, therefore, although the
condition for a minimum is satisfied, namely . It
is necessary therefore always to check by taking one value on either
side.
Fig. 30.
Now, if we take . If
and
; if
,
becomes 0.6389 and 0.0811; and if
,
becomes 0.8996 and 0.0804.
This shows that there are two branches of the curve; the upper one does not pass through a maximum, but the lower one does.
(7) A cylinder whose height is twice the radius of the base is
increasing in volume, so that all its parts keep always in the same
proportion to each other; that is, at any instant, the cylinder is
similar to the original cylinder. When the radius of the base
is feet, the surface area is increasing at the rate of 20 square
inches per second; at what rate is its volume then increasing?
[Pg 107]
The volume changes at the rate of cubic inches.
Make other examples for yourself. There are few subjects which offer such a wealth for interesting examples.
Exercises IX. (See page 257 for Answers.)
(1) What values of will make
a maximum and a minimum, if
?
(2) What value of will make
a maximum in the equation
?
(3) A line of length is to be cut up into 4 parts and put
together as a rectangle. Show that the area of the rectangle will be a
maximum if each of its sides is equal to
.
(4) A piece of string 30 inches long has its two ends joined together and is stretched by 3 pegs so as to form a triangle. What is the largest triangular area that can be enclosed by the string?
[Pg 108]
(5) Plot the curve corresponding to the equation
also find
, and deduce the value of
that will
make
a minimum; and find that minimum value of
.
(6) If , find what values of
will make
a
maximum or a minimum.
(7) What is the smallest square that can be inscribed in a given square?
(8) Inscribe in a given cone, the height of which is equal to the radius of the base, a cylinder (a whose volume is a maximum; (b) whose lateral area is a maximum; (c) whose total area is a maximum.
(9) Inscribe in a sphere, a cylinder (a) whose volume is a maximum; (b) whose lateral area is a maximum; (c) whose total area is a maximum.
(10) A spherical balloon is increasing in volume. If, when its radius
is feet, its volume is increasing at the rate of 4 cubic feet per
second, at what rate is its surface then increasing?
(11) Inscribe in a given sphere a cone whose volume is a maximum.
(12) The current given by a battery of
similar voltaic
cells is
, where
, are constants and
is the number of cells coupled in
series. Find the proportion of
to
for which the current is
greatest.
[Pg 109]
RETURNING to the process of successive differentiation, it
may be asked: Why does anybody want to differentiate twice over?
We know that when the variable quantities are space and time, by
differentiating twice over we get the acceleration of a moving body,
and that in the geometrical interpretation, as applied to curves,
means the slope of the curve. But what
can
mean in this case? Clearly it means
the rate (per unit of length
) at which the slope is changing-in
brief, it is a measure of the curvature of the slope.
Fig. 31.
Fig. 32.
Suppose a slope constant, as in Fig. 31.
[Pg 110]
Here, is of constant value.
Suppose, however, a case in which, like Fig. 32, the slope itself
is getting greater upwards, then ,
that is,
, will be
positive.
If the slope is becoming less as you go to the right (as in Fig. 14, p.
80), or as in Fig. 33, then, even though the curve may be going upward,
since the change is such as to diminish its slope, its
will be negative.
Fig. 33.
It is now time to initiate you into another secret-how to tell whether
the result that you get by "equating to zero" is a maximum or a
minimum. The trick is this: After you have differentiated (so as to
get the expression which you equate to zero), you then differentiate a
second time, and look whether the result of the second differentiation
is positive or negative. If
comes out positive, then you know that the value of
which
you got was a minimum; but if
comes
out negative, then the value of
which you got must be a
maximum. That's the rule.
The reason of it ought to be quite evident. Think of any curve that has
a minimum point in it (like Fig. 15, p. 80), or like Fig. 34, where the
point of minimum is marked
, and the curve is concave
upwards. To the left of
the slope is downward, that is,
negative, and is getting less negative. To the right of
the
slope has become upward, and is getting more and more upward. Clearly
the change of slope as the curve passes through
is such that
is positive, for its operation, as
increases toward the right, is to convert a downward slope into
an upward one.
Fig. 34.
Fig. 35.
Similarly, consider any curve that has a maximum point in it (like Fig.
16, p. 81), or like Fig. 35, where the curve is convex, and the maximum
point is marked . In this case, as the curve passes through
from left to right, its upward slope is converted into a downward
or negative slope, so that in this case the "slope of the slope"
is negative.
Go back now to the examples of the last chapter and verify in this [Pg 112] way the conclusions arrived at as to whether in any particular case there is a maximum or a minimum. You will find below a few worked out examples.
(1) Find the maximum or minimum of
(a) ;
(b) ;
and ascertain if it be a maximum or a minimum in each case.
(a) , and
; it is +; hence it is a minimum.
(b)
and
.
it is
hence it is a maximum.
(2) Find the maxima and minima of the function .
hence
corresponds to a minimum
. For
it is -;
hence
corresponds to a maximum
.
(3) Find the maxima and minima of .
[Pg 113]
or
, whose solutions are
and
.
The denominator is always positive, so it is sufficient to ascertain the sign of the numerator.
If we put , the numerator is negative; the maximum,
.
If we put , the numerator is positive; the minimum,
.
(4) The expense of handling the products of a certain factory
varies with the weekly output
according to the relation
, where
are positive constants. For
what output will the expense be least?
hence
and
.
As the output cannot be negative, .
Now
which is positive for all the values of
; hence
corresponds to a minimum.
[Pg 114]
(5) The total cost per hour of lighting a building with
lamps of a certain kind is
where
is the commercial efficiency (watts per candle),
Moreover, the relation connecting the average life of a lamp with
the commercial efficiency at which it is run is approximately
, where
and
are constants depending on the kind
of lamp.
Find the commercial efficiency for which the total cost of lighting will be least.
We have
for maximum or minimum.
This is clearly for minimum, since
[Pg 115]
which is positive for a positive value of
.
For a particular type of 16 candle-power lamps, pence,
pence; and it was found that
and
.
Exercises X. (You are advised to plot the graph of any numerical example.) (See p. 258 for the Answers.)
(1) Find the maxima and minima of
(2) Given , find expressions for
,
and for
, also find the value of
which makes
a maximum or a minimum, and show whether it is
maximum or minimum.
(3) Find how many maxima and how many minima there are in the curve,
the equation to which is
and how many in that of which the equation is
(4) Find the maxima and minima of
[Pg 116]
(5) Find the maxima and minima of
(6) Find the maxima and minima of
(7) Find the maxima and minima of
(8) Divide a number into two parts in such a way that three times
the square of one part plus twice the square of the other part shall be
a minimum.
(9) The efficiency of an electric generator at different values
of output
is expressed by the general equation:
where
is a constant depending chiefly on the energy losses in the
iron and
a constant depending chiefly on the resistance of the
copper parts. Find an expression for that value of the output at which
the efficiency will be a maximum.
(10) Suppose it to be known that consumption of coal by a certain
steamer may be represented by the formula ; where
is the number of tons of coal burned per hour and
is the
speed expressed in nautical miles per hour. The cost of wages, interest
on capital, and depreciation of that ship are together equal, per hour,
to the cost of 1 ton of coal. What speed will make the total cost
[Pg 117]
of a voyage of 1000 nautical miles a minimum? And, if coal costs 10
shillings per ton, what will that minimum cost of the voyage amount to?
(11) Find the maxima and minima of
(12) Find the maxima and minima of
[Pg 118]
Partial Fractions.
WE have seen that when we differentiate a fraction we have to perform a rather complicated operation; and, if the fraction is not itself a simple one, the result is bound to be a complicated expression. If we could split the fraction into two or more simpler fractions such that their sum is equivalent to the original fraction, we could then proceed by differentiating each of these simpler expressions. And the result of differentiating would be the sum of two (or more) differentials, each one of which is relatively simple; while the final expression, though of course it will be the same as that which could be obtained without resorting to this dodge, is thus obtained with much less effort and appears in a simplified form.
Let us see how to reach this result. Try first the job of adding two
fractions together to form a resultant fraction. Take, for example,
the two fractions and
. Every
schoolboy can add these together and find their sum to be
. And in the same way he can add together
three or more fractions. Now this process can certainly be reversed:
that is to say, that if this last expression were given, it is
[Pg 119]
certain that it can somehow be split back again into its original
components or partial fractions. Only we do not know in every case that
may be presented to us how we can so split it. In order to find
this out we shall consider a simple case at first. But it is important
to bear in mind that all which follows applies only to what are called
"proper" algebraic fractions, meaning fractions like the above, which
have the numerator of a lesser degree than the denominator; that
is, those in which the highest index of
is less in the numerator
than in the denominator. If we have to deal with such an expression as
, we can simplify it by division, since it
is equivalent to
; and
is a proper algebraic fraction to which the operation of splitting into
partial fractions can be applied, as explained hereafter.
Case I. If we perform many additions of two or more fractions the
denominators of which contain only terms in , and no terms in
,
, or any other powers of
, we always find
that the denominator of the final resulting fraction is the product
of the denominators of the fractions which were added to form the
result. It follows that by factorizing the denominator of this final
fraction, we can find every one of the denominators of the partial
fractions of which we are in search.
Suppose we wish to go back from to the
components which we know are
and
.
If we did not know what those components were we can still prepare the
way by writing:
leaving blank the places for the numerators until we know what to put
[Pg 120]
there. We always may assume the sign between the partial fractions to
be plus, since, if it be minus, we shall simply find
the corresponding numerator to be negative. Now, since the partial
fractions are proper fractions, the numerators are mere numbers
without
at all, and we can call them
as we
please. So, in this case, we have:
If now we perform the addition of these two partial fractions, we
get ; and this must be equal to
. And, as the denominators in these two
expressions are the same, the numerators must be equal, giving us:
Now, this is an equation with two unknown quantities, and it would
seem that we need another equation before we can solve them and find
and
. But there is another way out of this difficulty. The
equation must be true for all values of
; therefore it must be
true for such values of
as will cause
and
to
become zero, that is for
and for
respectively. If we
make
, we get
, so that
;
and if we make
, we get
, so
that
. Replacing the
and
of the partial fractions
by these new values, we find them to become
and
; and the thing is done.
As a farther example, let us take the fraction .
The denominator becomes zero when
is given the value 1; hence
is a factor of it, and obviously then the other factor
will be
; and this can again be decomposed into
[Pg 121]
. So we may write the fraction thus:
making three partial factors.
Proceeding as before, we find
Now, if we make , we get:
If , we get:
If , we get:
So then the partial fractions are:
which is far easier to differentiate with respect to
than the
complicated expression from which it is derived.
[Pg 122]
Case II. If some of the factors of the denominator contain
terms in , and are not conveniently put into factors, then
the corresponding numerator may contain a term in
, as well as a
simple number; and hence it becomes necessary to represent this unknown
numerator not by the symbol
but by
; the rest of the
calculation being made as before.
Try, for instance: .
Putting , we get
; and
; hence
and
Putting , we get
; hence
and
so that
, and the partial fractions are:
Take as another example the fraction
[Pg 123]
We get
In this case the determination of is not so easy. It
will be simpler to proceed as follows: Since the given fraction and
the fraction found by adding the partial fractions are equal, and have
identical denominators, the numerators must also be identically
the same. In such a case, and for such algebraical expressions as those
with which we are dealing here, the coefficients of the same powers
of
are equal and of same sign.
Hence, since
we have
(the coefficient of
in the left expression being zero);
; and
.
Here are four equations, from which we readily obtain
;
; so that the partial fractions are
. This method can
always be used; but the method shown first will be found the quickest
in the case of factors in
only.
Case III. When, among the factors of the denominator there are
some which are raised to some power, one must allow for the possible
existence of partial fractions having for denominator the several
powers of that factor up to the highest. For instance, in splitting
[Pg 124]
the fraction we must
allow for the possible existence of a denominator
as well as
and
.
It maybe thought, however, that, since the numerator of the fraction
the denominator of which is may contain terms in
,
we must allow for this in writing
for its numerator, so that
If, however, we try to find and
in this case, we
fail, because we get four unknowns; and we have only three relations
connecting them, yet
But if we write
we get
which gives
for
. Replacing
by its value,
transposing, gathering like terms and dividing by
, we get
, which gives
for
. Replacing
by
its value, we get
Hence ; so that the partial fractions are:
[Pg 125]
instead of
stated above as being the fractions from which
was obtained. The mystery is cleared if we observe that
can itself be split into the two fractions
, so that the three fractions
given are really equivalent to
which are the partial fractions obtained.
We see that it is sufficient to allow for one numerical term in each numerator, and that we always get the ultimate partial fractions.
When there is a power of a factor of in the denominator,
however, the corresponding numerators must be of the form
;
for example,
which gives
.
For , this gives
. Replacing, transposing, collecting
like terms, and dividing by
, we get
Hence and
and
or
and
, and finally,
or
. So that we
obtain as the partial fractions:
[Pg 126]
It is useful to check the results obtained. The simplest way is to
replace by a single value, say +1, both in the given expression
and in the partial fractions obtained.
Whenever the denominator contains but a power of a single factor, a very quick method is as follows:
Taking, for example, , let
; then
.
Replacing, we get
The partial fractions are, therefore,
Application to differentiation. Let it be required to differentiate
; we have
If we split the given expression into
we get, however,
[Pg 127]
which is really the same result as above split into partial fractions.
But the splitting, if done after differentiating, is more complicated,
as will easily be seen. When we shall deal with the integration
of such expressions, we shall find the splitting into partial fractions
a precious auxiliary (see p. 228).
Exercises XI. (See page 259 for Answers.)
Split into fractions:
(1) .
(2) .
(3) .
(4) .
(5) .
(6) .
(7) .
(8) .
(9) .
(10) .
(11) .
(12) .
(13) .
(14) .
[Pg 128]
(15) .
(16) .
(17) .
(18) .
Differential of an Inverse Function.
Consider the function (see p. 13) ; it can be expressed in
the form
; this latter form is called the inverse
function to the one originally given.
If ; if
,
and we see that
Consider ; the inverse function is
Here again
It can be shown that for all functions which can be put into the
inverse form, one can always write
[Pg 129]
It follows that, being given a function, if it be easier to differentiate the inverse function, this may be done, and the reciprocal of the differential coefficient of the inverse function gives the differential coefficient of the given function itself.
As an example, suppose that we wish to differentiate
. We have seen one way of doing this,
by writing
, and finding
and
. This gives
If we had forgotten how to proceed by this method, or wished to check
our result by some other way of obtaining the differential coefficient,
or for any other reason we could not use the ordinary method, we can
proceed as follows: The inverse function is .
hence
Let us take as an other example .
The inverse function is or
, and
[Pg 130]
It follows that ,
as might have been found otherwise.
We shall find this dodge most useful later on; meanwhile you are advised to become familiar with it by verifying by its means the results obtained in Exercises I. (p. 24), Nos. 5, 6, 7; Examples (p. 67), Nos. 1, 2, 4; and Exercises VI. (p. 72), Nos. 1, 2, 3 and 4.
You will surely realize from this chapter and the preceding, that in many respects the calculus is an art rather than a science: an art only to be acquired, as all other arts are, by practice. Hence you should work many examples, and set yourself other examples, to see if you can work them out, until the various artifices become familiar by use.
[Pg 131]
LET there be a quantity growing in such a way that the increment of its growth, during a given time, shall always be proportional to its own magnitude. This resembles the process of reckoning interest on money at some fixed rate; for the bigger the capital, the bigger the amount of interest on it in a given time.
Now we must distinguish clearly between two cases, in our calculation, according as the calculation is made by what the arithmetic books call "simple interest," or by what they call "compound interest." For in the former case the capital remains fixed, while in the latter the interest is added to the capital, which therefore increases by successive additions.
(1) At simple interest. Consider a concrete case. Let the
capital at start be , and let the rate of interest be 10 per
cent. per annum. Then the increment to the owner of the capital will be
every year. Let him go on drawing his interest every year, and
hoard it by putting it by in a stocking, or locking it up in his safe.
Then, if he goes on for 10 years, by the end of that time he will have
received 10 increments of
each, or
, making, with
the original
, a total of
in all. His property will
have doubled itself in 10 years. If the rate of interest had been 5 per
cent., he would have had to hoard for 20 years to double his property.
If it had been only 2 per cent., he would have had to hoard for 50
years. It is easy to see[Pg 132] that if the value of the yearly interest is
of the capital, he must go on hoarding for
years
in order to double his property.
Or, if be the original capital, and the yearly interest is
, then, at the end of
years, his property will be
(2) At compound interest. As before, let the owner begin with a
capital of , earning interest at the rate of 10 per cent. per
annum; but, instead of hoarding the interest, let it be added to the
capital each year, so that the capital grows year by year. Then, at the
end of one year, the capital will have grown to
; and in the
second year (still at
) this will earn
interest.
He will start the third year with
, and the interest on that
will be
.; so that he starts the fourth year with
., and so on. It is easy to work it out, and find that at the end of
the ten years the total capital will have grown to
.
In fact, we see that at the end of each year, each pound will have
earned
of a pound, and therefore, if this is always
added on, each year multiplies the capital by
;
and if continued for ten years (which will multiply by this factor
ten times over) will multiply the original capital by 2.59374. Let
us put this into symbols. Put
for the original capital;
for the fraction added on at each of the
[Pg 133]
operations; and
for the value of the capital at the end of
the
operation. Then
But this mode of reckoning compound interest once a year, is really
not quite fair; for even during the first year the ought to
have been growing. At the end of half a year it ought to have been
at least
, and it certainly would have been fairer had the
interest for the second half of the year been calculated on
.
This would be equivalent to calling it
per half-year; with 20
operations, therefore, at each of which the capital is multiplied by
. If reckoned this way, by the end of ten years the
capital would have grown to
; for
But, even so, the process is still not quite fair; for, by the end of
the first month, there will be some interest earned; and a half-yearly
reckoning assumes that the capital remains stationary for six months
at a time. Suppose we divided the year into 10 parts, and reckon a
one-percent. interest for each tenth of the year. We now have 100
operations lasting over the ten years; or
which works out to
.
Even this is not final. Let the ten years be divided into 1000
periods, each of of a year; the interest being
per cent. for each such period; then
[Pg 134]
which works out to
.
Go even more minutely, and divide the ten years into 10,000 parts, each
of a year, with interest at
of 1
per cent. Then
which amounts to
.
Finally, it will be seen that what we are trying to
find is in reality the ultimate value of the expression
, which, as we see, is greater than
2; and which, as we take
larger and larger, grows closer and
closer to a particular limiting value. However big you make
, the
value of this expression grows nearer and nearer to the figure
a number never to be forgotten.
Let us take geometrical illustrations of these things. In Fig. 36,
stands for the original value.
is the whole time during
which the value is growing. It is divided into 10 periods, in each
of which there is an equal step up. Here
is a
constant; and if each step up is
of the original
,
then, by 10 such steps, the height is doubled. If we had taken 20
steps, each of half the height shown, at the end the height would still
be just doubled. Or
such steps, each of
of the
original height
, would suffice to double the height. This is
the case of simple interest. Here is 1 growing till it becomes 2.
Fig. 36.
In Fig. 37, we have the corresponding illustration of the
geometrical progression. Each of the successive ordinates is to be
, that is,
times as high as its
predecessor. The steps up are not equal,[Pg 135] because each step up is
now
of the ordinate at that part of the curve. If
we had literally 10 steps, with
for the multiplying factor, the final total would be
or 2.594 times the original 1.
But if only we take
sufficiently large (and the corresponding
sufficiently small), then the final value
to which unity will grow will be
2.71828.
Fig. 37.
Epsilon. To this mysterious number 2.7182818 etc., the
mathematicians have assigned as a symbol the Greek letter
[Pg 136]
(pronounced epsilon). All schoolboys know that the Greek
letter
(called pi) stands for 3.141592 etc.; but how
many of them know that epsilon means 2.71828? Yet it is an even more
important number than
!
What, then, is epsilon?
Suppose we were to let 1 grow at simple interest till it became 2; then, if at the same nominal rate of interest, and for the same time, we were to let 1 grow at true compound interest, instead of simple, it would grow to the value epsilon.
This process of growing proportionately, at every instant, to the magnitude at that instant, some people call a logarithmic rate of growing. Unit logarithmic rate of growth is that rate which in unit time will cause 1 to grow to 2.718281. It might also be called the organic rate of growing: because it is characteristic of organic growth (in certain circumstances) that the increment of the organism in a given time is proportional to the magnitude of the organism itself.
If we take 100 per cent. as the unit of rate, and any fixed
period as the unit of time, then the result of letting 1 grow
arithmetically at unit rate, for unit time, will be 2, while
the result of letting 1 grow logarithmically at unit rate, for
the same time, will be .
A little more about Epsilon. We have seen that we
require to know what value is reached by the expression
, when
becomes indefinitely
great. Arithmetically, here are tabulated a lot of values (which
anybody can calculate out by the help of an ordinary table of
logarithms) got by assuming
and so on, up to
[Pg 137]
.
It is, however, worth while to find another way of calculating this immensely important figure.
Accordingly, we will avail ourselves of the binomial theorem, and
expand the expression in that
well-known way.
The binomial theorem gives the rule that
Putting and
, we get
[Pg 138]
Now, if we suppose to become indefinitely great, say a billion,
or a billion billions, then
, and
, etc., will all
be sensibly equal to
; and then the series becomes
By taking this rapidly convergent series to as many terms as we please, we can work out the sum to any desired point of accuracy. Here is the working for ten terms:
is incommensurable with 1, and resembles
in being
an interminable non-recurrent decimal.
The Exponential Series. We shall have need of yet another series.
Let us, again making use of the binomial theorem, expand the
expression , which is the same as
when we make
indefinitely great.
[Pg 139]
But, when is made indefinitely great, this simplifies down to the
following:
This series is called the exponential series.
The great reason why is regarded of importance is that
possesses a property, not possessed by any other
function of
, that when you differentiate it its value remains
unchanged; or, in other words, its differential coefficient is the
same as itself. This can be instantly seen by differentiating it with
respect to
, thus:
which is exactly the same as the original series.
Now we might have gone to work the other way, and said: Go to; let us
find a function of , such that its differential coefficient is
the same as itself. Or, is there any expression, involving only powers
of
, which is unchanged by differentiation? Accordingly; let us
assume as a general expression that
(in which the coefficients
, etc. will have to be
determined), and differentiate it.
Now, if this new expression is really to be the same as that from
which it was derived, it is clear that must
; that
; that
;
that
, etc.
The law of change is therefore that
If, now, we take for the sake of further simplicity, we have
Differentiating it any number of times will give always the same series over again.
If, now, we take the particular case of , and evaluate the
[Pg 141]
series, we shall get simply
and therefore
thus finally demonstrating that
[Note.—How to read exponentials. For the benefit
of those who have no tutor at hand it may be of use to state that
is read as "epsilon to the eksth power;" or
some people read it "exponential eks." So
is read "epsilon to the pee-teeth-power" or "exponential
pee tee." Take some similar expressions:—Thus,
is read "epsilon to the minus two power" or "exponential
minus two."
is read "epsilon to the minus
ay-eksth" or "exponential minus ay-eks."]
Of course it follows that remains unchanged if
differentiated with respect to
. Also
, which is
equal to
, will, when differentiated
with respect to
, be
, because
is a
constant.
Natural or Naperian Logarithms.
Another reason why is important is because it was made by
Napier, the inventor of logarithms, the basis of his system. If
[Pg 142]
is the value of
, then
is the logarithm,
to the base
, of
. Or, if then
The two curves plotted in Figs. 38 and 39 represent these equations.
The points calculated are:
{For Fig. 38
| 0 | 0.5 | 1 | 1.5 | 2 | |
| 1 | 1.65 | 2.71 | 4.50 | 7.69 |
{For Fig. 39
| 1 | 2 | 3 | 4 | 8 | |
| 0 | 0.69 | 1.10 | 1.39 | 2.08 |
Fig. 39.
Fig. 38.
It will be seen that, though the calculations yield different points for plotting, yet the result is identical. The two equations really mean the same thing.
[Pg 143]
As many persons who use ordinary logarithms, which are calculated to
base 10 instead of base , are unfamiliar with the "natural"
logarithms, it may be worth while to say a word about them. The
ordinary rule that adding logarithms gives the logarithm of the product
still holds good; or
Also the rule of powers holds good;
But as 10 is no longer the basis, one cannot multiply by 100 or 1000 by
merely adding 2 or 3 to the index. One can change the natural logarithm
to the ordinary logarithm simply by multiplying it by 0.4343; or
Exponential and Logarithmic Equations.
Now let us try our hands at differentiating certain expressions that contain logarithms or exponentials.
Take the equation:
First transform this into
whence, since the differential of
with regard to
is the original function unchanged (see p. 139),
[Pg 144]
A USEFUL TABLE OF "NAPERIAN LOGARITHMS"
(Also called Natural Logarithms or Hyperbolic Logarithms)
| Number | Number | ||
| 1 | 0.0000 | 6 | 1.7918 |
| 1.1 | 0.0953 | 7 | 1.9459 |
| 1.2 | 0.1823 | 8 | 2.0794 |
| 1.5 | 0.4055 | 9 | 2.1972 |
| 1.7 | 0.5306 | 10 | 2.3026 |
| 2.0 | 0.6931 | 20 | 2.9957 |
| 2.2 | 0.7885 | 50 | 3.9120 |
| 2.5 | 0.9163 | 100 | 4.6052 |
| 2.7 | 0.9933 | 200 | 5.2983 |
| 2.8 | 1.0296 | 500 | 6.2146 |
| 3.0 | 1.0986 | 1,000 | 6.9078 |
| 3.5 | 1.2528 | 2,000 | 7.6009 |
| 4.0 | 1.3863 | 5,000 | 8.5172 |
| 4.5 | 1.5041 | 10,000 | 9.2103 |
| 5.0 | 1.6094 | 20,000 | 9.9035 |
[Pg 145]
and, reverting from the inverse to the original function,
Now this is a very curious result. It may be written
Note that is a result that we could never have got by the
rule for differentiating powers. That rule (page 24) is to multiply by
the power, and reduce the power by 1. Thus, differentiating
gave us
; and differentiating
gave
.
But differentiating
does not give us
or
,
because
is itself
, and is a constant. We
shall have to come back to this curious fact that differentiating
gives us
when we reach the
chapter on integrating.
Now, try to differentiate
that is
we have
, since the differential of
remains
. This gives
hence, reverting to the original function (see p. 128), we get
[Pg 146]
Next try
First change to natural logarithms by multiplying by the modulus
0.4343. This gives us
The next thing is not quite so simple. Try this:
Taking the logarithm of both sides, we get
Since is a constant, we get
hence, reverting to the original function.
[Pg 147]
We see that, since
We shall find that whenever we have an expression such as
a function of
, we always have
the differential coefficient of
the function of
, so that we could have written at once, from
,
Let us now attempt further examples.
Examples.
(1) . Let
; then
.
Or thus:
(2) . Let
; then
.
Or thus:
[Pg 148]
(3) .
Check by writing .
(4) .
For if
and
,
Check by writing .
(5) . Let
;
then
.
(6) .
Let
; then
.
[Pg 149]
(7) .
(8) .
For if ,
let
and
.
Similarly, if ) and
(9) .
and
[Pg 150]
(10)
(11) .
Let
.
(12) .
Try now the following exercises.
Exercises XII. (See page 260 for Answers.)
(1) Differentiate .
(2) Find the differential coefficient with respect to of the
expression
.
(3) If , find
.
(4) Show that if .
(5) If , find
.
Differentiate
[Pg 151]
(6) .
(7) .
(8) .
(9) .
(10) .
(11) .
(12) .
(13) It was shown by Lord Kelvin that the speed of signalling through
a submarine cable depends on the value of the ratio of the external
diameter of the core to the diameter of the enclosed copper wire. If
this ratio is called , then the number of signals
that can
be sent per minute can be expressed by the formula
where
is a constant depending on the length and the quality of
the materials. Show that if these are given,
will be a maximum if
.
(14) Find the maximum or minimum of
(15) Differentiate .
(16) Differentiate .
[Pg 152]
The Logarithmic Curve.
Let us return to the curve which has its successive ordinates in
geometrical progression, such as that represented by the equation .
We can see, by putting , that
is the initial height of
. Then when
Also, we see that is the numerical value of the ratio between
the height of any ordinate and that of the next preceding it. In
Fig. 40, we have taken
as
; each ordinate being
as high as the preceding one.
Fig. 40.
Fig. 41.
If two successive ordinates are related together thus in a constant
ratio, their logarithms will have a constant difference; so that, if we
should plot out a new curve, Fig. 41, with values of
as ordinates, it would be a straight line sloping up by equal
steps. In fact, it follows from the equation, that
[Pg 153]
Now, since is a mere number, and may be written
as
, it follows that
and the equation takes the new form
The Die-away Curve.
If we were to take as a proper fraction (less than unity), the
curve would obviously tend to sink downwards, as in Fig. 42, where each
successive ordinate is
of the height of the preceding
one.
The equation is still
but since
is less than one,
will
be a negative quantity, and may be written
; so that
, and now our equation for the curve takes the form
Fig. 42.
The importance of this expression is that, in the case where the
independent variable is time, the equation represents the course
of a [Pg 154]great many physical processes in which something is gradually
dying away. Thus, the cooling of a hot body is represented (in
Newton's celebrated "law of cooling") by the equation
where
is the original excess of temperature of a hot
body over that of its surroundings,
the excess of
temperature at the end of time
, and
is a constant-namely,
the constant of decrement, depending on the amount of surface exposed
by the body, and on its coefficients of conductivity and emissivity,
etc.
A similar formula,
is used to express the charge of an electrified body, originally having
a charge
, which is leaking away with a constant of decrement
; which constant depends in this case on the capacity of the body
and on the resistance of the leakage-path.
Oscillations given to a flexible spring die out after a time; and the dying-out of the amplitude of the motion may be expressed in a similar way.
[Pg 155]
In fact serves as a die-away factor for all
those phenomena in which the rate of decrease is proportional to the
magnitude of that which is decreasing; or where, in our usual symbols,
is proportional at every moment to the value that
has at that moment. For we have only to inspect the curve, Fig.
42 above, to see that, at every part of it, the slope
is proportional to the height
; the curve becoming flatter as
grows smaller. In symbols, thus
or
and, differentiating,
hence
or, in words, the slope of the curve is downward, and proportional to
and to the constant
.
We should have got the same result if we had taken the equation in the
form for then
But
giving us
as before.
[Pg 156]
The Time-constant. In the expression for the "die-away
factor" , the quantity
is the reciprocal of
another quantity known as "the time-constant," which we may
denote by the symbol
. Then the die-away factor will be written
; and it will be seen, by making
that the meaning of
(or of
) is that this is
the length of time which it takes for the original quantity (called
or
in the preceding instances) to die away
th part—that is to 0.3678—of its original
value.
The values of and
are continually
required in different branches of physics, and as they are given in
very few sets of mathematical tables, some of the values are tabulated
on p. 157 for convenience.
As an example of the use of this table, suppose there is a hot body
cooling, and that at the beginning of the experiment (i.e. when
) it is
hotter than the surrounding objects,
and if the time-constant of its cooling is 20 minutes (that is,
if it takes 20 minutes for its excess of temperature to fall to
part of
), then we can calculate
to what it will have fallen in any given time
. For instance, let
be 60 minutes. Then
, and we shall
have to find the value of
, and then multiply the
original
by this. The table shows that
is 0.0498. So that at the end of 60 minutes the excess of temperature
will have fallen to
.
[Pg 157]
THE LAW OF ORGANIC GROWTH
| 0.00 | 1.0000 | 1.0000 | 0.0000 |
| 0.10 | 1.1052 | 0.8187 | 0.1813 |
| 0.50 | 1.6487 | 0.6065 | 0.3935 |
| 0.75 | 2.1170 | 0.4724 | 0.5276 |
| 0.90 | 2.4596 | 0.4066 | 0.5934 |
| 1.00 | 2.7183 | 0.3679 | 0.6321 |
| 1.10 | 3.0042 | 0.3329 | 0.6671 |
| 1.20 | 3.3201 | 0.3012 | 0.6988 |
| 1.25 | 3.4903 | 0.2865 | 0.7135 |
| 1.50 | 4.4817 | 0.2231 | 0.7769 |
| 1.75 | 5.755 | 0.1738 | 0.8262 |
| 2.00 | 7.389 | 0.1353 | 0.8647 |
| 2.50 | 12.182 | 0.0821 | 0.9179 |
| 3.00 | 20.086 | 0.0498 | 0.9502 |
| 3.50 | 33.115 | 0.0302 | 0.9698 |
| 4.00 | 54.598 | 0.0183 | 0.9817 |
| 4.50 | 90.017 | 0.0111 | 0.9889 |
| 5.00 | 148.41 | 0.0067 | 0.9933 |
| 5.50 | 244.69 | 0.0041 | 0.9959 |
| 6.00 | 403.43 | 0.00248 | 0.99752 |
| 7.50 | 1808.04 | 0.00055 | 0.99947 |
| 10.00 | 22026.5 | 0.000045 | 0.999955 |
[Pg 158]
Further Examples.
(1) The strength of an electric current in a conductor at a time
secs. after the application of the electromotive force producing it
is given by the expression
.
The time constant is .
If ; then when
is very large the term
becomes 1, and
;
also
Its value at any time may be written:
the time-constant being 0.01. This means that it takes 0.01 sec. for
the variable term to fall by
of its
initial value
.
To find the value of the current when , say,
,
(from table).
It follows that, after 0.001 sec., the variable term is 9.048, and the actual current is
.
Similarly, at the end of 0.1 sec.,
the variable term is
, the current being
9.9995.
(2) The intensity of a beam of light which has passed through a
thickness
of some transparent medium is
, where
is the initial intensity of the beam
and
is a "constant of absorption."
[Pg 159]
This constant is usually found by experiments. If it be found, for
instance, that a beam of light has its intensity diminished by in passing through 10 cms. of a certain transparent medium, this
means that
or
, and from the table one sees that
very nearly;
hence
.
To find the thickness that will reduce the intensity to half its value,
one must find the value of which satisfies the equality
, or
. It is found
by putting this equation in its logarithmic form, namely,
which gives
(3) The quantity of a radio-active substance which has not yet
undergone transformation is known to be related to the initial quantity
of the substance by the relation
, where
is a constant and
the time in seconds
elapsed since the transformation began.
For "Radium ," if time is expressed in seconds, experiment shows
that
. Find the time required for
transforming half the substance. (This time is called the "mean life"
of the substance.)
We have .
and
[Pg 160]
Exercises XIII. (See page 260 for Answers.)
(1) Draw the curve ; where
,
and
is given various values from 0 to 20.
(2) If a hot body cools so that in 24 minutes its excess of temperature has fallen to half the initial amount, deduce the time-constant, and find how long it will be in cooling down to 1 per cent. of the original excess.
(3) Plot the curve .
(4) The following equations give very similar curves:
Draw all three curves, taking millimetres;
millimetres.
(5) Find the differential coefficient of with respect to
, if
(6) For "Thorium ," the value of
is 5; find the "mean
life," that is, the time taken by the transformation of a quantity
of "Thorium
" equal to half the initial quantity
in the expression
being in seconds.
[Pg 161]
(7) A condenser of capacity , charged to a
potential
, is discharging through a resistance of 10,000
ohms. Find the potential
after (a) 0.1 second; (b) 0.01 second;
assuming that the fall of potential follows the rule
.
(8) The charge of an electrified insulated metal sphere is
reduced from 20 to 16 units in 10 minutes. Find the coefficient
of leakage, if
being the
initial charge and
being in seconds. Hence find the time taken by
half the charge to leak away.
(9) The damping on a telephone line can be ascertained from the
relation , where
is the strength,
after
seconds, of a telephonic current of initial strength
;
is the length of the line in kilometres, and
is a constant. For the Franco-English submarine cable laid in 1910,
. Find the damping at the end of the cable (40
kilometres), and the length along which
is still
of the
original current (limiting value of very good audition).
(10) The pressure of the atmosphere at an altitude
kilometres is given by
being the
pressure at sea-level (760 millimetres).
The pressures at 10, 20 and 50 kilometres being 199.2, 42.2, 0.32
respectively, find in each case. Using the mean value of
,
find the percentage error in each case.
(11) Find the minimum or maximum of .
(12) Find the minimum or maximum of .
(13) Find the minimum or maximum of .
[Pg 162]
GREEK letters being usual to denote angles, we will take as
the usual letter for any variable angle the letter ("theta").
Let us consider the function
Fig. 43.
What we have to investigate is the value of ; or, in other words, if the angle
varies, we
have to find the relation between the increment of the sine and the
increment of the angle, both increments being indefinitely small in
themselves. Examine Fig. 43, wherein, if the radius of the circle is
[Pg 163]
unity, the height of
is the sine, and
is the angle.
Now, if
is supposed to increase by the addition to it of the
small angle
—an element of angle—the height of
,
the sine, will be increased by a small element
. The new height
will be the sine of the new angle
, or,
stating it as an equation,
and subtracting from this the first equation gives
The quantity on the right-hand side is the difference between two
sines, and books on trigonometry tell us how to work this out. For they
tell us that if and
are two different angles,
If, then, we put for one angle, and
for the other, we may write
But if we regard as indefinitely small, then in the limit
we may neglect
by comparison with
,
and may also take
as being the same as
. The equation then becomes:
[Pg 164]
The accompanying curves, Figs. 44 and 45, show, plotted to scale, the
values of , and
,
for the corresponding values of
.
Fig. 45.
Fig. 44.
[Pg 165]
Take next the cosine.
Let .
Now .
Therefore
And it follows that
Lastly, take the tangent.
Let
Expanding, as shown in books on trigonometry,
[Pg 166]
Now remember that if is indefinitely diminished, the value
of
becomes identical with
, and
is negligibly small compared with 1, so that the expression reduces to
Collecting these results, we have:
Sometimes, in mechanical and physical questions, as, for example,
in simple harmonic motion and in wave-motions, we have to deal with
angles that increase in proportion to the time. Thus, if be the
time of one complete period, or movement round the circle,
then, since the angle all round the circle is
radians, or
, the amount of angle moved through in time
, will
be
[Pg 167]
If the frequency, or number of periods per second, be denoted by
, then
, and we may then write:
Then we shall have
If, now, we wish to know how the sine varies with respect to time, we
must differentiate with respect, not to , but to
. For
this we must resort to the artifice explained in Chapter IX., p. 66,
and put
Now will obviously be
; so that
Similarly, it follows that
Second Differential Coefficient of Sine or Cosine.
We have seen that when is differentiated with respect
to
it becomes
and that when
is differentiated with respect to
it becomes
; or, in symbols,
[Pg 168]
So we have this curious result that we have found a function such that if we differentiate it twice over, we get the same thing from which we started, but with the sign changed from + to -.
The same thing is true for the cosine; for differentiating gives us
, and differentiating
gives us
or thus:
Sines and cosines are the only functions of which the second differential coefficient is equal (and of opposite sign to) the original function.
Examples.
With what we have so far learned we can now differentiate expressions of a more complex nature.
(1) .
If is the arc whose sine is
, then
.
Passing now from the inverse function to the original one, we get
Now
hence
a rather unexpected result.
[Pg 169]
(2) .
This is the same thing as .
Let ; then
;
.
(3) .
Let ; then
.
(4) .
Let .
(5) .
(6) .
Let ;
;
.
[Pg 170]
(7) .
Let (see p. 67).
(for, if
,
hence
)
hence .
(8) .
Exercises XIV. (See page 261 for Answers.)
(1) Differentiate the following:
(i) .
(ii) ; and
.
(iii) ; and
.
(2) Find the value of for which
is a maximum.
[Pg 171]
(3) Differentiate .
(4) If , find
.
(5) Differentiate .
(6) Differentiate .
(7) Plot the curve ; and
show that the slope of the curve at
is half the
maximum slope.
(8) If , find
.
(9) If , find the
differential coefficient of
with respect to
.
(10) Differentiate .
(11) Differentiate the three equations of Exercises XIII. (p. 160), No.
4, and compare their differential coefficients, as to whether they are
equal, or nearly equal, for very small values of , or for very
large values of
, or for values of
in the neighbourhood of
.
(12) Differentiate the following:
(i) .
(ii) .
(iii) .
(iv) .
(v) .
(13) Differentiate .
(14) Differentiate .
(15) Find the maximum or minimum of .
[Pg 172]
WE sometimes come across quantities that are functions of more
than one independent variable. Thus, we may find a case where
depends on two other variable quantities, one of which we will call
and the other
. In symbols
Take the simplest concrete case.
Let .
What are we to do? If we were to treat as a constant, and
differentiate with respect to
, we should get
or if we treat
as a constant, and differentiate with respect to
, we should have:
The little letters here put as subscripts are to show which quantity has been taken as constant in the operation.
[Pg 173]
Another way of indicating that the differentiation has been performed
only partially, that is, has been performed only with respect
to one of the independent variables, is to write the differential
coefficients with Greek deltas, like , instead of little
. In this way
If we put in these values for and
respectively, we shall
have
But, if you think of it, you will observe that the total variation of
depends on both these things at the same time. That is to
say, if both are varying, the real
ought to be written
and this is called a total differential. In some books it is
written
.
Example (1). Find the partial differential coefficients of the
expression . The answers are:
[Pg 174]
The first is obtained by supposing constant, the second is
obtained by supposing
constant; then
Example (2). Let . Then, treating first
and
then
as constant, we get in the usual way
so that
.
Example (3). A cone having height and radius of base
has volume
. If its height remains
constant, while
changes, the ratio of change of volume, with
respect to radius, is different from ratio of change of volume with
respect to height which would occur if the height were varied and the
radius kept constant, for
The variation when both the radius and the height change is given by
.
Example (4). In the following example and
denote
two arbitrary functions of any form whatsoever. For example, they may
be sine-functions, or exponentials, or mere algebraic functions of the
[Pg 175]
two independent variables,
and
. This being understood,
let us take the expression
or,
where
Then
(where the figure 1 is simply the coefficient of
in
and
); and
Also
and
whence
This differential equation is of immense importance in mathematical physics.
Maxima and Minima of Functions of two Independent Variables.
Example (5). Let us take up again Exercise IX., p. 107, No. 4.
Let and
be the length of two of the portions of the
string. The third is
, and the area of the triangle is
[Pg 176]
, where
is the half perimeter,
15, so that
, where
Clearly is maximum when
is maximum.
For a maximum (clearly it will not be a minimum in this case), one must
have simultaneously
that is,
An immediate solution is .
If we now introduce this condition in the value of , we find
For maximum or minimum,
, which
gives
or
.
Clearly gives minimum area;
gives the maximum, for
, which is +30 for
and -30
for
.
[Pg 177]
Example (6). Find the dimensions of an ordinary railway coal
truck with rectangular ends, so that, for a given volume the area
of sides and floor together is as small as possible.
The truck is a rectangular box open at the top. Let be the length
and
be the width; then the depth is
. The
surface area is
For minimum (clearly it won't be a maximum here),
Here also, an immediate solution is , so that
,
for minimum, and
Exercises XV. (See page 263 for Answers.)
(1) Differentiate the expression
with respect to
alone, and with respect to
alone.
(2) Find the partial differential coefficients with respect to
and
, of the expression
[Pg 178]
(3) Let .
Find the value of . Also find the value
of
.
(4) Find the total differential of .
(5) Find the total differential of ; of
;
and of
.
(6) Verify that the sum of three quantities ,
,
, whose
product is a constant
, is maximum when these three quantities are
equal.
(7) Find the maximum or minimum of the function
(8) The post-office regulations state that no parcel is to be of such a size that its length plus its girth exceeds 6 feet. What is the greatest volume that can be sent by post (a) in the case of a package of rectangular cross section; (b) in the case of a package of circular cross section.
(9) Divide into 3 parts such that the continued product of
their sines may be a maximum or minimum.
(10) Find the maximum or minimum of .
(11) Find maximum and minimum of
(12) A telpherage bucket of given capacity has the shape of a horizontal isosceles triangular prism with the apex underneath, and [Pg 179] the opposite face open. Find its dimensions in order that the least amount of iron sheet may be used in its construction.
[Pg 180]
THE great secret has already been revealed that this
mysterious symbol , which is after all only a long
,
merely means "the sum of," or "the sum of all such quantities
as." It therefore resembles that other symbol
(the Greek
Sigma), which is also a sign of summation. There is this
difference, however, in the practice of mathematical men as to the use
of these signs, that while
is generally used to indicate the
sum of a number of finite quantities, the integral sign
is
generally used to indicate the summing up of a vast number of small
quantities of indefinitely minute magnitude, mere elements in fact,
that go to make up the total required. Thus
, and
.
Any one can understand how the whole of anything can be conceived of
as made up of a lot of little bits; and the smaller the bits the more
of them there will be. Thus, a line one inch long may be conceived as
made up of 10 pieces, each of an inch long; or of
100 parts, each part being
of an inch long; or of
parts, each of which is
of an
inch long; or, pushing the thought to the limits of conceivability, it
may be regarded as made up of an infinite number of elements each of
which is infinitesimally small.
Yes, you will say, but what is the use of thinking of anything that [Pg 181] way? Why not think of it straight off, as a whole? The simple reason is that there are a vast number of cases in which one cannot calculate the bigness of the thing as a whole without reckoning up the sum of a lot of small parts. The process of "integrating" is to enable us to calculate totals that otherwise we should be unable to estimate directly.
Let us first take one or two simple cases to familiarize ourselves with this notion of summing up a lot of separate parts.
Consider the series:
Here each member of the series is formed by taking it half the value of the preceding. What is the value of the total if we could go on to an infinite number of terms? Every schoolboy knows that the answer is 2. Think of it, if you like, as a line.
Fig. 46.
Begin with one inch; add a half inch, add a quarter;
add an eighth; and so on. If at any point of the operation we stop,
there will still be a piece wanting to make up the whole 2 inches;
and the piece wanting will always be the same size as the last piece
added. Thus, if after having put together , and
, we stop, there will be
wanting. If
we go on till we have added
, there will still be
wanting. The remainder needed will always be equal to
the last term added. By an infinite number of operations only should we
reach the actual 2 inches. Practically we should reach it when we got
to pieces so small that they [Pg
182] could not be drawn-that would be after about 10 terms,
for the eleventh term is
. If we want to go so far
that not even a Whitworth's measuring machine would detect it, we
should merely have to go to about 20 terms. A microscope would not
show even the
term! So the infinite number of
operations is no such dreadful thing after all. The integral
is simply the whole lot. But, as we shall see, there are cases in
which the integral calculus enables us to get at the exact total that
there would be as the result of an infinite number of operations. In
such cases the integral calculus gives us a rapid and easy way of
getting at a result that would otherwise require an interminable lot of
elaborate working out. So we had best lose no time in learning how
to integrate.
Slopes of Curves, and the Curves themselves.
Let us make a little preliminary enquiry about the slopes of curves. For we have seen that differentiating a curve means finding an expression for its slope (or for its slopes at different points). Can we perform the reverse process of reconstructing the whole curve if the slope (or slopes) are prescribed for us?
Go back to case (2) on p. 82. Here we have the simplest of curves, a
sloping line with the equation
[Pg 183]
Fig. 47.
We know that here represents the initial height of
when
, and that
, which is the same as
, is
the "slope" of the line. The line has a constant slope. All along it
the elementary triangles
have the same proportion
between height and base. Suppose we were to take the
's, and
's of finite magnitude, so that
's made up one inch, then
there would be ten little triangles like
Now, suppose that we were ordered to reconstruct the "curve," starting
merely from the information that . What could
we do? Still taking the little
's as of finite size, we could
draw 10 of them, all with the same slope, and then put them together,
end to end, like this:
Fig. 48.
And, as the slope is the same for all, they would join to make, as in
Fig. 48, a sloping line sloping with the correct slope . And whether we take the
's and
's as finite or
infinitely small, as they are all alike, clearly
,
if we reckon
as the total of all the
's, and
as the
total of all the
's. But whereabouts [Pg 184] are we to put this sloping line? Are we
to start at the origin
, or higher up? As the only information
we have is as to the slope, we are without any instructions as to
the particular height above
; in fact the initial height is
undetermined. The slope will be the same, whatever the initial height.
Let us therefore make a shot at what may be wanted, and start the
sloping line at a height
above
. That is, we have the
equation
It becomes evident now that in this case the added constant means the
particular value that has when
.
Now let us take a harder case, that of a line, the slope of which is
not constant, but turns up more and more. Let us assume that the upward
slope gets greater and greater in proportion as grows. In
[Pg 185]
symbols this is:
Or, to give a concrete case, take
, so that
Then we had best begin by calculating a few of the values of the slope
at different values of , and also draw little diagrams of them.
When
Now try to put the pieces together, setting each so that the middle
of its base is the proper distance to the right, and so that they fit
together at the corners; thus (Fig. 49). The result is, of course, not
a smooth curve: but it is an approximation to one. If we had taken bits
half as long, and twice as numerous, like Fig. 50, we should have a
better approximation. But for a perfect curve we ought to take each
and its corresponding
infinitesimally small, and infinitely
numerous.
[Pg 186]
Fig. 49.
Then, how much ought the value of any to be? Clearly, at any
point
of the curve, the value of
will be the sum of all
the little
's from 0 up to that level, that is to say,
.
And as each
is equal to
,
it follows that the whole
will be equal to the sum of all such
bits as
, or, as we should write it,
.
Fig. 50.
Now if had been constant,
would
have been the same as
, or
. But
began by being 0, and increases to the particular
[Pg 187]
value of
at the point
, so that its average value from 0
to that point is
. Hence
; or
.
Fig. 51.
But, as in the previous case, this requires the addition of an
undetermined constant , because we have not been told at what
height above the origin the curve will begin, when
. So we
write, as the equation of the curve drawn in Fig. 51,
Exercises XVI. (See page 264 for Answers.)
(1) Find the ultimate sum of
etc.
(2) Show that the series
etc., is convergent, and find its sum to 8 terms.
(3) If
etc., find
.
[Pg 188]
(4) Following a reasoning similar to that explained in this chapter,
find ,
(5) If , find
.
[Pg 189]
DIFFERENTIATING is the process by which when is given us
(as a function of
), we can find
.
Like every other mathematical operation, the process of differentiation
may be reversed; thus, if differentiating gives us
; if one begins with
one would say that reversing the process would yield
. But here comes in a curious point. We should get
if we had begun with any of the following:
,
or
, or
, or
with any added
constant. So it is clear that in working backwards from
to
, one must make provision for the possibility of there
being an added constant, the value of which will be undetermined until
ascertained in some other way. So, if differentiating
yields
, going backwards from
will
give us
; where
stands for the yet undetermined
possible constant.
Clearly, in dealing with powers of , the rule for working
backwards will be: Increase the power by 1, then divide by that
increased power, and add the undetermined constant.
[Pg 190]
So, in the case where
working backwards, we get
If differentiating the equation gives us
it is a matter of common sense that beginning with
and reversing the process, will give us
So, when we are dealing with a multiplying constant, we must simply put
the constant as a multiplier of the result of the integration.
Thus, if , the reverse process gives us
.
But this is incomplete. For we must remember that if we had started with
where
is any constant quantity whatever, we should equally have found
So, therefore, when we reverse the process we must always remember to add on this undetermined constant, even if we do not yet know what its value will be.
[Pg 191]
This process, the reverse of differentiating, is called
integrating; for it consists in finding the value of the whole
quantity when you are given only an expression for
or for
. Hitherto we have as much as possible kept
and
together as a differential coefficient: henceforth we shall
more often have to separate them.
If we begin with a simple case,
We may write this, if we like, as
Now this is a "differential equation" which informs us that an element
of is equal to the corresponding element of
multiplied by
. Now, what we want is the integral; therefore, write down
with the proper symbol the instructions to integrate both sides, thus:
[Note as to reading integrals: the above would be read thus:
"Integral dee-wy equals integral eks-squared dee-eks."]
We haven't yet integrated: we have only written down instructions to
integrate—if we can. Let us try. Plenty of other fools can do it-why
not we also? The left-hand side is simplicity itself. The sum of all
the bits of is the same thing as
itself. So we may at once
put:
[Pg 192]
But when we come to the right-hand side of the equation we must
remember that what we have got to sum up together is not all the 's,
but all such terms as
; and this will not
be the same as
, because
is not a constant.
For some of the
's will be multiplied by big values of
, and some will be multiplied by small values of
,
according to what
happens to be. So we must bethink ourselves as
to what we know about this process of integration being the reverse of
differentiation. Now, our rule for this reversed process—see p. 189
ante—when dealing with
is "increase the power by one,
and divide by the same number as this increased power." That is to say,
will be changed[5] to
. Put this into
the equation; but don't forget to add the "constant of integration"
at the end. So we get:
You have actually performed the integration. How easy!
Let us try another simple case.
Let
where
is any constant multiplier. Well, we found when
differentiating (see p. 27) that any constant factor in the value of
reappeared[Pg 193]
unchanged in the value of
. In the reversed process
of integrating, it will therefore also reappear in the value of
.
So we may go to work as before, thus
So that is done. How easy!
We begin to realize now that integrating is a process of finding
our way back, as compared with differentiating. If ever, during
differentiating, we have found any particular expression-in this
example —we can find our way back to the
from
which it was derived. The contrast between the two processes may be
illustrated by the following remark due to a well-known teacher. If
a stranger were set down in Trafalgar Square, and told to find his
way to Euston Station, he might find the task hopeless. But if he had
previously been personally conducted from Euston Station to Trafalgar
Square, it would be comparatively easy to him to find his way back to
Euston Station.
Integration of the Sum or Difference of two Functions.
Let
then
[Pg 194]
There is no reason why we should not integrate each term separately: for, as may be seen on p. 34, we found that when we differentiated the sum of two separate functions, the differential coefficient was simply the sum of the two separate differentiations. So, when we work backwards, integrating, the integration will be simply the sum of the two separate integrations.
Our instructions will then be:
If either of the terms had been a negative quantity, the corresponding term in the integral would have also been negative. So that differences are as readily dealt with as sums.
How to deal with Constant Terms.
Suppose there is in the expression to be integrated a constant
term—such as this:
This is laughably easy. For you have only to remember that when you
differentiated the expression , the result was
.
Hence, when you work the other way and integrate, the constant
[Pg 195]
reappears multiplied by
. So we get
Here are a lot of examples on which to try your newly acquired powers.
Examples.
(1) Given . Find
Ans.
.
(2) Find . It is
or
or
.
(3) Given . Find
. Ans.
.
(4) . Find
.
and
(5) Integrate . Ans.
.
[Pg 196]
All these are easy enough. Let us try another case.
Let .
Proceeding as before, we will write
Well, but what is the integral of ?
If you look back amongst the results of differentiating and
and
, etc., you will find we never got
from any one of them as the value of
. We got
from
; we got
from
; we got
1 from
(that is, from
itself); but we did not get
from
, for two very good reasons. First,
is simply
, and is a constant, and could not have a differential
coefficient. Secondly, even if it could be differentiated, its
differential coefficient (got by slavishly following the usual rule)
would be
, and that multiplication by zero gives it
zero value! Therefore when we now come to try to integrate
,
we see that it does not come in anywhere in the powers of
that are given by the rule:
It is an exceptional case.
Well; but try again. Look through all the various differentials
obtained from various functions of , and try to find amongst
them
. A sufficient search will show that we actually did
get
as the result of differentiating the
function
(see p. 145).
[Pg 197]
Then, of course, since we know that differentiating
gives us
, we know that, by reversing the process,
integrating
will give us
.
But we must not forget the constant factor
that was given, nor
must we omit to add the undetermined constant of integration. This then
gives us as the solution to the present problem,
N.B.—Here note this very remarkable fact, that we could not
have integrated in the above case if we had not happened to know
the corresponding differentiation. If no one had found out that
differentiating gave
, we should have
been utterly stuck by the problem how to integrate
.
Indeed it should be frankly admitted that this is one of the curious
features of the integral calculus:—that you can't integrate anything
before the reverse process of differentiating something else has
yielded that expression which you want to integrate. No one, even
to-day, is able to find the general integral of the expression,
because
has never yet been found to result from
differentiating anything else.
Another simple case.
Find .
On looking at the function to be integrated, you remark that it
is the product of two different functions of . You could,
you think, integrate
by itself, or
by
itself. Of course you could. But what to do with a product? None of
[Pg 198]
the differentiations you have learned have yielded you for the
differential coefficient a product like this. Failing such, the
simplest thing is to multiply up the two functions, and then integrate.
This gives us
And this is the same as
And performing the integrations, we get
Some other Integrals.
Now that we know that integration is the reverse of differentiation, we
may at once look up the differential coefficients we already know, and
see from what functions they were derived. This gives us the following
integrals ready made:
[Pg 199]
(for if
).
Also we may deduce the following:
(for if
).
(for if
; hence to get
one must differentiate
).
Try also ; a little dodge will simplify matters:
[Pg 200]
and
See also the Table of Standard Forms on pp. 249-251. You should make such a table for yourself, putting in it only the general functions which you have successfully differentiated and integrated. See to it that it grows steadily!
On Double and Triple Integrals.
In many cases it is necessary to integrate some expression for two
or more variables contained in it; and in that case the sign of
integration appears more than once. Thus,
means that some function of the variables
and
has to be
integrated for each. It does not matter in which order they are done.
Thus, take the function
. Integrating it with respect to
gives us:
Now, integrate this with respect to :
[Pg 201]
to which of course a constant is to be added. If we had reversed the
order of the operations, the result would have been the same.
In dealing with areas of surfaces and of solids, we have often to
integrate both for length and breadth, and thus have integrals of the
form
where
is some property that depends, at each point, on
and on
. This would then be called a surface-integral. It
indicates that the value of all such elements as
(that is to say, of the value of
over a little rectangle
long and
broad) has to be summed up over the whole length
and whole breadth.
Similarly in the case of solids, where we deal with three dimensions.
Consider any element of volume, the small cube whose dimensions are
. If the figure of the solid be expressed by the function
, then the whole solid will have the volume-integral,
Naturally, such integrations have to be taken between appropriate
limits[6] in each dimension; and the integration cannot be performed
unless one knows in what way the boundaries of the surface depend on
,
, and
. If the limits for
are from
to
, those for
from
to
, and those for
from
to
, then clearly we have
[Pg 202]
There are of course plenty of complicated and difficult cases; but, in general, it is quite easy to see the significance of the symbols where they are intended to indicate that a certain integration has to be performed over a given surface, or throughout a given solid space.
Exercises XVII. (See p. 264 for the Answers.)
(1) Find when
.
(2) Find .
(3) Find .
(4) Find .
(5) Integrate .
(6) Find .
(7) If ; find
.
(8) Find .
(9) Find .
(10) Find .
(11) Find .
(12) Find .
(13) Find .
(14) Find .
[Pg 203]
(15) Find .
(16) Find .
(17) Find .
(18) Find .
[5]
[You may ask, what has become of the little at the end? Well,
remember that it was really part of the differential coefficient,
and when changed over to the right-hand side, as in the
,
serves as a reminder that
is the independent variable with
respect to which the operation is to be effected; and, as the result
of the product being totalled up, the power of
has increased by
one. You will soon become familiar with all this.]
[Pg 204]
ONE use of the integral calculus is to enable us to ascertain the values of areas bounded by curves.
Let us try to get at the subject bit by bit.
Fig. 52.
Let (Fig. 52) be a curve, the equation to which is known. That
is,
in this curve is some known function of
. Think of a
piece of the curve from the point
to the point
.
[Pg 205]
Let a perpendicular be dropped from
, and another
from the point
. Then call
and
, and
the ordinates
and
. We have thus marked out
the area
that lies beneath the piece
. The problem
is, how can we calculate the value of this area?
The secret of solving this problem is to conceive the area as being
divided up into a lot of narrow strips, each of them being of the width
. The smaller we take
, the more of them there will be
between
and
. Now, the whole area is clearly equal
to the sum of the areas of all such strips. Our business will then be
to discover an expression for the area of any one narrow strip, and to
integrate it so as to add together all the strips. Now think of any one
of the strips. will be like this: being bounded between two vertical
sides, with a flat bottom
, and with a slightly curved sloping
top. Suppose we take its average height as being
; then, as its
width is
, its area will be
. And seeing that we may
take the width as narrow as we please, if we only take it narrow enough
its average height will be the same as the height at the middle of it.
Now let us call the unknown value of the whole area
, meaning
surface. The area of one strip will be simply a bit of the whole area,
and may therefore be called
. So we may write
If then we add up all the strips, we get
[Pg 206]
So then our finding depends on whether we can integrate
for the particular case, when we know what the value of
is
as a function of
.
For instance, if you were told that for the particular curve in
question , no doubt you could put that value into the
expression and say: then I must find
.
That is all very well; but a little thought will show you that
something more must be done. Because the area we are trying to find
is not the area under the whole length of the curve, but only the
area limited on the left by , and on the right by
, it
follows that we must do something to define our area between those
'limits.'
This introduces us to a new notion, namely that of integrating
between limits. We suppose to vary, and for the present
purpose we do not require any value of
below
(that is
), nor any value of
above
(that is
).
When an integral is to be thus defined between two limits, we call the
lower of the two values the inferior limit, and the upper value
the superior limit. Any integral so limited we designate as a
definite integral, by way of distinguishing it from a general
integral to which no limits are assigned.
In the symbols which give instructions to integrate, the limits are
marked by putting them at the top and bottom respectively of the sign
of integration. Thus the instruction
will be read: find the integral of
between the inferior
limit
and the superior limit
.
[Pg 207]
Sometimes the thing is written more simply
Well, but how do you find an integral between limits, when you
have got these instructions?
Look again at Fig. 52 (p. 204). Suppose we could find the area under
the larger piece of curve from to
, that is from
to
, naming the area
. Then, suppose we could find
the area under the smaller piece from
to
, that is from
to
, namely the area
. If then we were
to subtract the smaller area from the larger, we should have left as a
remainder the area
, which is what we want. Here we have the
clue as to what to do; the definite integral between the two limits is
the difference between the integral worked out for the superior
limit and the integral worked out for the lower limit.
Let us then go ahead. First, find the general integral thus:
and, as
is the equation to the curve (Fig. 52),
is the general integral which we must find.
Doing the integration in question by the rule (p. 193), we get
and this will be the whole area from 0 up to any value of
that we
may assign.
[Pg 208]
Therefore, the larger area up to the superior limit will be
and the smaller area up to the inferior limit
will be
Now, subtract the smaller from the larger, and we get for the area
the value,
This is the answer we wanted. Let us give some numerical values.
Suppose , and
and
. Then the
area
is equal to
Let us here put down a symbolic way of stating what we have ascertained
about limits:
where
is the integrated value of
corresponding to
, and
that corresponding to
.
[Pg 209]
All integration between limits requires the difference between two
values to be thus found. Also note that, in making the subtraction the
added constant has disappeared.
Examples.
(1) To familiarize ourselves with the process, let us take a case
of which we know the answer beforehand. Let us find the area of the
triangle (Fig. 53), which has base and height
. We know
beforehand, from obvious mensuration, that the answer will come 24.
Fig. 53.
Now, here we have as the "curve" a sloping line for which the equation
is
The area in question will be
Integrating (p. 192), and putting down the value of
the general integral in square brackets with the limits marked above
and below, we get[Pg 210]
Fig. 54.
Let us satisfy ourselves about this rather surprising dodge of
calculation, by testing it on a simple example. Get some squared paper,
preferably some that is ruled in little squares of one-eighth inch or
one-tenth inch each way. On this squared paper plot out the graph of
the equation,
The values to be plotted will be:
| 0 | 3 | 6 | 9 | 12 | |
| 0 | 1 | 2 | 3 | 4 |
[Pg 211]
The plot is given in Fig. 54.
Now reckon out the area beneath the curve by counting the little
squares below the line, from as far as
on the
right. There are 18 whole squares and four triangles, each of which has
an area equal to
squares; or, in total, 24 squares.
Hence 24 is the numerical value of the integral of
between the lower limit of
and the higher limit of
.
As a further exercise, show that the value of the same integral between
the limits of and
is 36.
Fig. 55.
(2) Find the area, between limits and
,
of the curve
.
[Pg 212]
N.B.—Notice that in dealing with definite integrals the
constant always disappears by subtraction.
Fig. 56.
Let it be noted that this process of subtracting one part from a
larger to find the difference is really a common practice. How do
you find the area of a plane ring (Fig. 56), the outer radius of
which is and the inner radius is
? You know from
mensuration that the area of the outer circle is
;
then you find the area of the inner circle,
; then
you subtract the latter from the former, and find area of ring
; which may be written
mean circumference of ring × width of ring.
(3) Here's another case - that of the die-away curve (p. 153).
Find the area between and
, of the curve (Fig. 57) whose
equation is
[Pg 213]
The integration (p. 198) gives
Fig. 57.
Fig. 58.
(4) Another example is afforded by the adiabatic curve of a perfect
gas, the equation to which is , where
stands for
pressure,
for volume, and
is of the value 1.42 (Fig. 58).
Find the area under the curve (which is proportional to the work done
in suddenly compressing the gas) from volume to volume
.
Here we have
[Pg 214]
An Exercise.
Prove the ordinary mensuration formula, that the area of a circle
whose radius is
, is equal to
.
Fig. 59.
Consider an elementary zone or annulus of the surface (Fig. 59), of
breadth , situated at a distance
from the centre. We may
consider the entire surface as consisting of such narrow zones, and the
whole area
will simply be the integral of all such elementary
zones from centre to margin, that is, integrated from
to
.
We have therefore to find an expression for the elementary area
of the narrow zone. Think of it as a strip of breadth
, and of a
length that is the periphery of the circle of radius
, that is, a
length of
. Then we have, as the area of the narrow zone,
Hence the area of the whole circle will be:
[Pg 215]
Now, the general integral of is
.
Therefore,
Another Exercise.
Fig. 60.
Let us find the mean ordinate of the positive part of the curve
, which is shown in Fig. 60. To find the mean ordinate,
we shall have to find the area of the piece
, and then divide
it by the length of the base
. But before we can find the area
we must ascertain the length of the base, so as to know up to what
limit we are to integrate. At
the ordinate
has zero value;
therefore, we must look at the equation and see what value of
will make
. Now, clearly, if
is
will also be 0,
the curve passing through the origin
; but also, if
;
so that
gives us the position of the point
.
[Pg 216]
Then the area wanted is
But the base length is 1.
Therefore, the average ordinate of the curve .
[N.B.—It will be a pretty and simple exercise in maxima and minima to find by differentiation what is the height of the maximum ordinate. It must be greater than the average.]
The mean ordinate of any curve, over a range from to
, is given by the expression,
One can also find in the same way the surface area of a solid of revolution.
Example.
The curve is revolving about the axis of
. Find the
area of the surface generated by the curve between
and
.
A point on the curve, the ordinate of which is , describes a
circumference of length
, and a narrow belt of the surface,
of width
, corresponding to this point, has for area
.
The total area is
[Pg 217]
Areas in Polar Coordinates.
Fig. 61.
When the equation of the boundary of an area is given as a function
of the distance of a point of it from a fixed point
(see
Fig. 61) called the pole, and of the angle which
makes
with the positive horizontal direction
, the process just
explained can be applied just as easily, with a small modification.
Instead of a strip of area, we consider a small triangle
, the
angle at
being
, and we find the sum of all the little
triangles making up the required area.
The area of such a small triangle is approximately
or
; hence the portion
of the area included between the curve and two positions of
corresponding to the angles
and
is given
by
Examples.
(1) Find the area of the sector of 1 radian in a circumference of
radius inches.
The polar equation of the circumference is evidently . The area
is
(2) Find the area of the first quadrant of the curve (known as
"Pascal's Snail"), the polar equation of which is .
Volumes by Integration.
What we have done with the area of a little strip of a surface, we can, of course, just as easily do with the volume of a little strip of a solid. We can add up all the little strips that make up the total solid, and find its volume, just as we have added up all the small little bits that made up an area to find the final area of the figure operated upon.
Examples.
(1) Find the volume of a sphere of radius .
A thin spherical shell has for volume (see Fig. 59,
p. 214); summing up all the concentric shells which make up the sphere,
[Pg 219]
we have
Fig. 62.
We can also proceed as follows: a slice of the sphere, of thickness ,
has for volume
(see Fig. 62). Also
and
are related by the expression
(2) Find the volume of the solid generated by the revolution of the
curve about the axis of
, between
and
.
[Pg 220]
The volume of a strip of the solid is .
Hence
On Quadratic Means.
In certain branches of physics, particularly in the study of
alternating electric currents, it is necessary to be able to calculate
the quadratic mean of a variable quantity. By "quadratic mean"
is denoted the square root of the mean of the squares of all the
values between the limits considered. Other names for the quadratic
mean of any quantity are its "virtual" value, or its "R.M.S." (meaning
root-mean-square) value. The French term is valeur efficace. If
is the function under consideration, and the quadratic mean is to
be taken between the limits of
and
; then the quadratic
mean is expressed as
Examples.
(1) To find the quadratic mean of the function (Fig. 63).
Here the integral is , which is
. Dividing by
and taking the square
root, we have
[Pg 221]
Fig. 63.
Here the arithmetical mean is ; and the ratio
of quadratic to arithmetical mean (this ratio is called the
form-factor) is
.
(2) To find the quadratic mean of the function .
The integral is , that is
.
Hence
(3) To find the quadratic mean of the function .
The integral is ,
that is
,
which is
.
Hence the quadratic mean is .
Exercises XVIII. (See p. 265 for Answers.)
(1) Find the area of the curve between
and
, and the mean ordinates between these limits.
[Pg 222]
(2) Find the area of the parabola between
and
. Show that it is two-thirds of the rectangle of the
limiting ordinate and of its abscissa.
(3) Find the area of the positive portion of a sine curve and the mean ordinate.
(4) Find the area of the positive portion of the curve ,
and find the mean ordinate.
(5) Find the area included between the two branches of the curve
from
to
, also the area
of the positive portion of the lower branch of the curve (see Fig. 30,
p. 106).
(6) Find the volume of a cone of radius of base , and of height
.
(7) Find the area of the curve between
and
.
(8) Find the volume generated by the curve , as it
revolves about the axis of
, between
and
.
(9) Find the volume generated by a sine curve revolving about the axis
of . Find also the area of its surface.
(10) Find the area of the portion of the curve included
between
and
. Find the mean ordinate between these
limits.
(11) Show that the quadratic mean of the function , between
the limits of 0 and
radians, is
. Find
also the arithmetical mean of the same function between the same
limits; and show that the form-factor is
.
[Pg 223]
(12) Find the arithmetical and quadratic means of the function , from
to
.
(13) Find the quadratic mean and the arithmetical mean of the function
.
(14) A certain curve has the equation .
Find the area included between the curve and the axis of
, from
the ordinate at
to the ordinate at
. Find also the
height of the mean ordinate of the curve between these points.
(15) Show that the radius of a circle, the area of which is twice the
area of a polar diagram, is equal to the quadratic mean of all the
values of for that polar diagram.
(16) Find the volume generated by the curve rotating about the axis of
.
[Pg 224]
Dodges. A great part of the labour of integrating things consists in licking them into some shape that can be integrated. The books-and by this is meant the serious books-on the Integral Calculus are full of plans and methods and dodges and artifices for this kind of work. The following are a few of them.
Integration by Parts. This name is given to a dodge, the formula
for which is
It is useful in some cases that you can't tackle directly, for it shows
that if in any case can be found, then
can also be found. The formula can be deduced as follows. From p. 37,
we have,
which may be written
which by direct integration gives the above expression.
[Pg 225]
Examples.
(1) Find .
Write , and for
write
. We shall
then have
, while
.
Putting these into the formula, we get
(2) Find .
Write
then
and
(3) Try .
[Pg 226]
Hence
and
(4) Find .
Write
then
Now find , integrating by parts (as in Example 1
above):
Hence
(5) Find .
Write
then
(see Chap. IX., p. 66).
[Pg 227]
and
; so that
Here we may use a little dodge, for we can write
Adding these two last equations, we get rid of
, and we have
Do you remember meeting ? it is got by
differentiating
(see p. 168); hence its integral is
, and so
You can try now some exercises by yourself; you will find some at the end of this chapter.
Substitution. This is the same dodge as explained in Chap. IX., p. 66. Let us illustrate its application to integration by a few examples.
(1) .
Let
replace
[Pg 228]
(2) .
Let
so that
is the result of differentiating
.
Hence the integral is
.
(3) .
Let
then the integral becomes
;
but
is the result of differentiating
.
Hence one has finally for the value of the given integral.
Formulæ of Reduction are special forms applicable chiefly to binomial and trigonometrical expressions that have to be integrated, and have to be reduced into some form of which the integral is known.
Rationalization, and Factorization of Denominator are dodges applicable in special cases, but they do not admit of any short or general explanation. Much practice is needed to become familiar with these preparatory processes.
The following example shows how the process of splitting into partial fractions, which we learned in Chap. XIII., p. 118, can be made use of in integration.
[Pg 229]
Take again ; if we split
into partial fractions, this becomes (see p.
230):
Notice that the same integral can be expressed sometimes in more than
one way (which are equivalent to one another).
Pitfalls. A beginner is liable to overlook certain points
that a practised hand would avoid; such as the use of factors that
are equivalent to either zero or infinity, and the occurrence of
indeterminate quantities such as . There is no golden
rule that will meet every possible case. Nothing but practice and
intelligent care will avail. An example of a pitfall which had to be
circumvented arose in Chap. XVIII., p. 189, when we came to the problem
of integrating
.
Triumphs. By triumphs must be understood the successes with
which the calculus has been applied to the solution of problems
otherwise intractable. Often in the consideration of physical
relations one is able to build up an expression for the law governing
the interaction of the parts or of the forces that govern them,
such expression being naturally in the form of a differential
equation, that is an equation containing differential coefficients
with or without other algebraic quantities. And when such a
differential equation has been found, one can get no further until
it has been integrated. Generally it is much easier to state the
appropriate differential equation than to solve it: the real trouble
begins then only when one wants to integrate, unless indeed the
[Pg 230]
equation is seen to possess some standard form of which the integral
is known, and then the triumph is easy. The equation which results
from integrating a differential equation is called[7] its "solution";
and it is quite astonishing how in many cases the solution looks as
if it had no relation to the differential equation of which it is
the integrated form. The solution often seems as different from the
original expression as a butterfly does from the caterpillar that it
was. Who would have supposed that such an innocent thing as
could blossom out into
yet the latter is the solution of the former.
As a last example, let us work out the above together.
By partial fractions,
[Pg 231]
Not a very difficult metamorphosis!
There are whole treatises, such as Boole's Differential Equations, devoted to the subject of thus finding the "solutions" for different original forms.
Exercises XIX. (See p. 266 for Answers.)
(1) Find .
(2) Find .
(3) Find .
(4) Find .
(5) Find .
(6) Find .
(7) Find .
(8) Find .
(9) Find .
(10) Find .
(11) Find .
(12) Find .
(13) Find .
(14) Find .
[7] This means that the actual result of solving it is called its "solution." But many mathematicians would say, with Professor Forsyth, "every differential equation is considered as solved when the value of the dependent variable is expressed as a function of the independent variable by means either of known functions, or of integrals, whether the integrations in the latter can or cannot be expressed in terms of functions already known."
[Pg 232]
IN this chapter we go to work finding solutions to some important differential equations, using for this purpose the processes shown in the preceding chapters.
The beginner, who now knows how easy most of those processes are in themselves, will here begin to realize that integration is an art. As in all arts, so in this, facility can be acquired only by diligent and regular practice. He who would attain that facility must work out examples, and more examples, and yet more examples, such as are found abundantly in all the regular treatises on the Calculus. Our purpose here must be to afford the briefest introduction to serious work.
Example 1. Find the solution of the differential equation
Transposing we have
[Pg 233]
Now the mere inspection of this relation tells us that we have got to
do with a case in which is proportional to
.
If we think of the curve which will represent
as a function of
, it will be such that its slope at any point will be proportional
to the ordinate at that point, and will be a negative slope if
is
positive. So obviously the curve will be a die-away curve (p. 153), and
the solution will contain
as a factor. But, without
presuming on this bit of sagacity, let us go to work.
As both and
occur in the equation and on opposite sides,
we can do nothing until we get both
and
to one side, and
to the other. To do this, we must split our usually inseparable
companions
and
from one another.
Having done the deed, we now can see that both sides have got into a
shape that is integrable, because we recognize ,
or
, as a differential that we have met with (p.
143) when differentiating logarithms. So we may at once write down the
instructions to integrate,
and doing the two integrations, we have:
where
is the yet undetermined constant[8] of
integration. Then, delogarizing, we get:
[Pg 234]
which is the solution required. Now, this solution looks
quite unlike the original differential equation from which it was
constructed: yet to an expert mathematician they both convey the same
information as to the way in which
depends on
.
Now, as to the , its meaning depends on the initial value
of
. For if we put
in order to see what value
then has, we find that this makes
; and as
we see that
is nothing else than the
particular value[9] of
at starting. This we may call
,
and so write the solution as
Example 2.
Let us take as an example to solve
where
is a constant. Again, inspecting the equation will suggest,
(1) that somehow or other
will come into the solution,
and (2) that if at any part of the curve
becomes either a maximum
or a minimum, so that
, then
will have the
value
. But let us go to work as before, separating the
differentials and trying to transform the thing into some integrable
shape.
[Pg 235]
Now we have done our best to get nothing but and
on one
side, and nothing but
on the other. But is the result on the
left side integrable?
It is of the same form as the result on p. 145; so, writing the
instructions to integrate, we have:
and, doing the integration, and adding the appropriate constant,
and finally,
which is the solution.
If the condition is laid down that when
we can find
; for then the exponential becomes
; and we have
[Pg 236]
Putting in this value, the solution becomes
But further, if grows indefinitely,
will grow to a maximum;
for when
, the exponential
, giving
. Substituting this, we get finally
This result is also of importance in physical science.
Example 3.
Let
We shall find this much less tractable than the preceding. First divide
through by .
Now, as it stands, the left side is not integrable. But it can be made
so by the artifice - and this is where skill and practice suggest a
plan-of multiplying all the terms by ,
giving us:
which is the same as
[Pg 237]
and this being a perfect differential may be integrated thus:-since,
if
,
The last term is obviously a term which will die out as
increases, and may be omitted. The trouble now comes in to find the
integral that appears as a factor. To tackle this we resort to the
device (see p. 224) of integration by parts, the general formula for
which is
. For this purpose write
We shall then have
Inserting these, the integral in question becomes:
[Pg 238]
The last integral is still irreducible. To evade the difficulty, repeat
the integration by parts of the left side, but treating it in the
reverse way by writing:
Inserting these, we get
Noting that the final intractable integral in [C] is the same as
that in , we may eliminate it, by multiplying
by
, and multiplying [c] by
, and adding them.
The result, when cleared down, is:
Inserting this value in , we get
To simplify still further, let us imagine an angle such that
.
[Pg 239]
Then
and
Substituting these, we get:
which may be written
which is the solution desired.
This is indeed none other than the equation of an alternating electric
current, where represents the amplitude of the electromotive
force,
the frequency,
the resistance,
the coefficient
of self-induction of the circuit, and
is an angle of lag.
Example 4.
Suppose that .
We could integrate this expression directly, if were a function
of
only, and
a function of
only; but, if both
and
are functions that depend on both
and
, how are
we to integrate it? Is it itself an exact differential? That is: have
and
each been formed by partial differentiation from some
[Pg 240]
common function
, or not? If they have, then
And if such a common function exists, then
is an exact differential (compare p. 172).
Now the test of the matter is this. If the expression is an exact
differential, it must be true that
which is necessarily true.
Take as an illustration the equation
Is this an exact differential or not? Apply the test.
which do not agree. Therefore, it is not an exact differential, and the
two functions
and
have not come from a common
original function.
[Pg 241]
It is possible in such cases to discover, however, an integrating
factor, that is to say, a factor such that if both are multiplied by
this factor, the expression will become an exact differential. There is
no one rule for discovering such an integrating factor; but experience
will usually suggest one. In the present instance will act as
such. Multiplying by
, we get
Now apply the test to this.
which agrees. Hence this is an exact differential, and may be
integrated. Now, if
,
Hence
so that we get
Example 5. Let .
In this case we have a differential equation of the second degree, in
which appears in the form of a second differential coefficient,
as well as in person.
Transposing, we have .
[Pg 242]
It appears from this that we have to do with a function such that
its second differential coefficient is proportional to itself, but
with reversed sign. In Chapter XV, we found that there was such a
function-namely, the sine (or the cosine also) which possessed this
property. So, without further ado, we may infer that the solution will
be of the form . However, let us go to work.
Multiply both sides of the original equation by
and integrate, giving us
, and, as
being a constant. Then, taking the square roots,
But it can be shown that (see p. 168)
whence, passing from angles to sines,
where
is a constant angle that comes in by integration.
Or, preferably, this may be written
[Pg 243]
Example 6. .
Here we have obviously to deal with a function which is such
that its second differential coefficient is proportional to itself.
The only function we know that has this property is the exponential
function (see p. 139), and we may be certain therefore that the
solution of the equation will be of that form.
Proceeding as before, by multiplying through by ,
and integrating, we get
,
and, as
,
where
is a constant, and
.
Now, if
,
and
Hence, integrating, this gives us
Now
whence
[Pg 244]
Subtracting (2) from (1) and dividing by 2, we then have
which is more conveniently written
Or, the solution, which at first sight does not look as if it had
anything to do with the original equation, shows that
consists of
two terms, one of which grows logarithmically as
increases, and
of a second term which dies away as
increases.
Example 7.
Let
Examination of this expression will show that, if , it has the
form of Example 1, the solution of which was a negative exponential.
On the other hand, if
, its form becomes the same as that
of Example 6, the solution of which is the sum of a positive and a
negative exponential. It is therefore not very surprising to find that
the solution of the present example is
The steps by which this solution is reached are not given here; they may be found in advanced treatises.
[Pg 245]
Example 8.
It was seen (p. 174) that this equation was derived from the original
where
and
were any arbitrary functions of
.
Another way of dealing with it is to transform it by a change of
variables into
where
, and
, leading to the same general
solution. If we consider a case in which
vanishes, then we have simply
and this merely states that, at the time
is a particular
function of
, and may be looked upon as denoting that the curve
of the relation of
to
has a particular shape. Then any
change in the value of
is equivalent simply to an alteration in
the origin from which
is reckoned. That is to say, it indicates
that, the form of the function being conserved, it is propagated along
the
direction with a uniform velocity
; so that whatever
the value of the ordinate
at any particular time
at
any particular point
, the same value of
will appear at
the subsequent time
at a point further along, the abscissa
of which is
. In this case the
simplified equation represents the propagation of a wave (of any form)
at a uniform speed along the
direction.
[Pg 246]
If the differential equation had been written
the solution would have been the same, but the velocity of propagation
would have had the value
You have now been personally conducted over the frontiers into the enchanted land. And in order that you may have a handy reference to the principal results, the author, in bidding you farewell, begs to present you with a passport in the shape of a convenient collection of standard forms (see pp. 249-251). In the middle column are set down a number of the functions which most commonly occur. The results of differentiating them are set down on the left; the results of integrating them are set down on the right. May you find them useful!
[8]
We may write down any form of constant as the "constant
of integration," and the form is adopted here by
preference, because the other terms in this line of equation are, or
are treated as logarithms; and it saves complications afterward if the
added constant be of the same kind.
[Pg 247]
IT may be confidently assumed that when this tractate "Calculus made Easy" falls into the hands of the professional mathematicians, they will (if not too lazy) rise up as one man, and damn it as being a thoroughly bad book. Of that there can be, from their point of view, no possible manner of doubt whatever. It commits several most grievous and deplorable errors.
First, it shows how ridiculously easy most of the operations of the calculus really are.
Secondly, it gives away so many trade secrets. By showing you that what one fool can do, other fools can do also, it lets you see that these mathematical swells, who pride themselves on having mastered such an awfully difficult subject as the calculus, have no such great reason to be puffed up. They like you to think how terribly difficult it is, and don't want that superstition to be rudely dissipated.
Thirdly, among the dreadful things they will say about "So Easy" is this: that there is an utter failure on the part of the author to demonstrate with rigid and satisfactory completeness the validity of sundry methods which he has presented in simple fashion, and has even dared to use in solving problems! But why should he not? You don't forbid the use of a watch to every person who does not know how [Pg 248] to make one? You don't object to the musician playing on a violin that he has not himself constructed. You don't teach the rules of syntax to children until they have already become fluent in the use of speech. It would be equally absurd to require general rigid demonstrations to be expounded to beginners in the calculus.
One other thing will the professed mathematicians say about this thoroughly bad and vicious book: that the reason why it is so easy is because the author has left out all the things that are really difficult. And the ghastly fact about this accusation is that—it is true! That is, indeed, why the book has been written-written for the legion of innocents who have hitherto been deterred from acquiring the elements of the calculus by the stupid way in which its teaching is almost always presented. Any subject can be made repulsive by presenting it bristling with difficulties. The aim of this book is to enable beginners to learn its language, to acquire familiarity with its endearing simplicities, and to grasp its powerful methods of solving problems, without being compelled to toil through the intricate out-of-the-way (and mostly irrelevant) mathematical gymnastics so dear to the unpractical mathematician.
There are amongst young engineers a number on whose ears the adage that what one fool can do, another can, may fall with a familiar sound. They are earnestly requested not to give the author away, nor to tell the mathematicians what a fool he really is.
[Pg 249]
| Algebraic. | ||
| 1 | ||
| 0 | ||
| 1 | ||
| Exponential and Logarithmic. | ||
| Trigonometrical. | ||
| Circular (Inverse). | ||
| Hyperbolic. | ||
| Miscellaneous. | ||
[Pg 252]
Exercises I. (p. 24.)
(1) .
(2) .
(3) .
(4) .
(5) .
(6) .
(7) .
(8) .
(9) .
(10) .
Exercises II. (p. 31.)
(1) .
(2) .
(3) .
(4) .
(5) .
(6) .
(7) .
(8) and 7.47 candle power per volt respectively.
(9) ,
.
[Pg 253]
(10) .
(11) .
(12) .
Exercises III. (p. 45.)
(1) (a) .
(b) .
(c) .
(d) .
(2) .
(3) .
(4) .
(5) .
(6) .
(7) .
(8) .
(9) .
(10) .
(11) .
(12) or
.
(13) .
(14) .
[Pg 254]
Exercises IV. (p. 50.)
(1) .
(2) .
(3) .
(4) (Exercises III.):
(1) (a) .
(b) .
(c) 2,0.
(d) .
(2) .
(3) 2,0.
(4) .
(5) 2,0.
(6) .
(7) .
(Examples, p. 40):
(1) .
(2) .
(3) .
(4) .
(5) .
(6) .
(7) .
[Pg 255]
Exercises V. (p. 63.)
(2) 64; 147.2; and 0.32 feet per second.
(3) .
(4) 45.1 feet per second.
(5) 12.4 feet per second per second. Yes.
(6) Angular velocity radians per second; angular acceleration
radians per second per second.
(7) .
(8) .
(9) and 0.00211.
(10) .
Exercises VI. (p. 72.)
(1) .
(2) .
(3) .
(4) .
(5) .
[Pg 256]
(6) .
(7) .
(8) .
(9) .
Exercises VII. (p. 74.)
(1) .
(2) .
(3) .
Exercises VIII. (p. 88.)
(2) 1.44.
(4) ; and the numerical values are:
, and 15.
(5) .
(6) . Slope is zero
where
; and is
where
.
[Pg 257]
(7) .
(8) Intersections at . Angles
.
(9) Intersection at . Angle
.
(10) .
Exercises IX. (p. 107.)
(1) Min.: ; max.:
.
(2) .
(4) square inches.
(5) .
(6) Max. for ; min. for
.
(7) Join the middle points of the four sides.
(8) , no max.
(9) .
(10) At the rate of square feet per second.
(11) .
(12) .
[Pg 258]
Exercises X. (p. 115.)
(1) Max.: ; min.:
.
(2) (a maximum).
(3) (a) One maximum and two minima.
(b) One maximum. ( ; other points unreal.)
(4) Min.: .
(5) Max: .
(6) Max.: .
Min.: .
(7) Max.: .
Min.: .
(8) .
(9) .
(10) Speed 8.66 nautical miles per hour. Time taken 115.47 hours. Minimum cost £112.12s.
(11) Max. and min. for . (See example no. 10, p.
71.)
(12) Min.: ; max.:
.
[Pg 259]
Exercises XI. (p. 127.)
(1) .
(2) .
(3) .
(4) .
(5) .
(6) .
(7) .
(8) .
(9) .
(10) .
(11) .
(12) .
(13) .
(14) .
(15) .
(16) .
(17) .
(18) .
[Pg 260]
Exercises XII. (p. 150.)
(1) .
(2) .
(3) .
(5) .
(6) .
(7) .
(8) .
(9) .
(10) .
(11) .
(12) .
(14) Min.: for
.
(15) .
(16) .
Exercises XIII. (p. 160.)
(1) Let , and use the Table on page
157.
(2) minutes.
(3) Take ; and use the Table on page 157.
(5) (a) ;
(b) ;
(c) .
[Pg 261]
(6) 0.14 second.
(7) (a) 1.642; (b) 15.58.
(8) .
(9) is
of
kilometres.
(10) , mean
.
(11) Min. for .
(12) Max. for .
(13) Min. for .
Exercises XIV. (p. 170.)
(1) (i) ;
(ii)
and
;
(iii)
and
.
(2) or
radians.
(3) .
(4) .
(5) .
(6) .
[Pg 262]
(7) The slope is ,
which is a maximum when
,
or
; the value of the slope being then
.
When
the slope is
.
(8)
(9) .
(10)
(11) (i) ;
(ii) ;
(iii) .
(12) (i) ;
(ii) ;
(iii) ;
(iv) ;
(v) .
(13) .
(14) .
(15) ; is max. for
, min. for
.
[Pg 263]
Exercises XV. (p. 177.)
(1) .
(2) ;
(3) .
(4) .
(5)
(7) Minimum for .
(8) (a) Length 2 feet, width depth
foot, vol.
cubic
feet.
(9) All three parts equal; the product is maximum.
(10) Minimum for .
(11) Min.: and
.
(12) Angle at apex ; equal sides
length
.
[Pg 264]
Exercises XVI. (p. 187.)
(1) .
(2) 0.6344.
(3) 0.2624.
(4) (a) ;
(b) .
(5) .
Exercises XVII. (p. 202.)
(1) .
(2) .
(3) .
(4) .
(5) .
(6) .
(7) .
(8) by division.
Therefore the answer is
.
(See pages 196 and 198.)
(9) .
(10) .
(11) .
(12) .
(13) .
(14) .
[Pg 265]
(15) .
(16) .
(17) .
(18) .
Exercises XVIII. (p. 221.)
(1) Area ; mean ordinate
.
(2) Area of
.
(3) Area ; mean ordinate
.
(4) Area mean ordinate
.
(5) .
(6) Volume .
(7) 1.25.
(8) 79.4.
(9) Volume ; area of surface
(from 0 to
).
(10) .
(12) Arithmetical mean ; quadratic mean
.
(13) Quadratic mean ;
arithmetical mean
.
The first involves a somewhat difficult integral, and may be stated
thus: By definition the quadratic mean will be
[Pg 266]
Now the integration indicated by
is more readily obtained if for
we write
For
we write
; and, for
,
Making these substitutions, and integrating, we get (see p. 198)
At the lower limit the substitution of 0 for causes all this
to vanish, whilst at the upper limit the substitution of
for
gives
. And hence the answer
follows.
(14) Area is 62.6 square units. Mean ordinate is 10.42.
(16) 436.3. (This solid is pear shaped.)
Exercises XIX. (p. 231.)
(1) .
(2) .
[Pg 267]
(3) .
(4) .
(5) .
(6) .
(7) .
(8) .
(9) .
(10) .
(11) .
(12) .
(13) .
(14) . (Let
; then, in the result, let
.)
You had better differentiate now the answer and work back to the given expression as a check.
Every earnest student is exhorted to manufacture more examples for himself at every stage, so as to test his powers. When integrating he can always test his answer by differentiating it, to see whether he gets back the expression from which he started.
There are lots of books which give examples for practice. It will suffice here to name two: R. G. Blaine's The Calculus and its Applications, and F. M. Saxelby's A Course in Practical Mathematics.
[Pg 268]
An Introduction to the Calculus. Based on Graphical Methods. By Prof. G. A. Gibson, M.A., LL.D. 3s. 6d.
An Elementary Treatise on the Calculus. With Illustrations from Geometry, Mechanics, and Physics. By Prof. G. A. Gibson, M.A., LL.D. 7s. 6d.
Differential Calculus for Beginners. By J. Edwards, M.A. 4s. 6d.
Integral Calculus for Beginners. With an Introduction to the Study of Differential Equations. By Joseph Edwards, M.A. 4s. 6d.
Calculus Made Easy. Being a very-simplest Introduction to those beautiful Methods of Reckoning which are generally called by the terrifying names of the Differential Calculus and the Integral Calculus. By F. R. S. 2s. net. New Edition, with many Examples.
A First Course in the Differential and Integral Calculus. By Prof. W. F. Osgood, Ph.D. 8s. 6d. net.
Practical Integration for the use of Engineers, etc. By A. S. Percival, M.A. 2s. 6d. net.
Differential Calculus. With Applications and numerous Examples. An Elementary Treatise by Joseph Edwards, M.A. 14s.
[Pg 269]
Differential and Integral Calculus for Technical Schools and Colleges. By P. A. Lambert, m.A. 7s. 6d.
Differential and Integral Calculus. With Applications. By Sir A. G. Greenhill, F.R.S. 10s. 6d.
A Treatise on the Integral Calculus and its Applications. By I. Todhunter, F.R.S. 10s. 6d. Key. By H. St. J. Hunter, M.A. 10s. 6d.
A Treatise on the Differential Calculus and the Elements of the Integral Calculus. With numerous Examples. By I. Todhunter, F.R.S. 10s. 6d. Key. By H. St. J. Hunter, M.A. 10s. 6d.
Ordinary Differential Equations. An Elementary Text-book. By James Morris Page, Ph.D. 6s. 6d.
An Introduction to the Modern Theory of Equations. By Prof. F. Cajori, Ph.D. 7s. 6d. net.
A Treatise on Differential Equations. By Andrew Russell Forsyth, Sc.D., LL.D. Fourth Edition. 14s. net.
A Short Course on Differential Equations. By Prof. Donald F. Campbell, Ph.D. 4s. net.
A Manual of Quaternions. By C. J. Joly, M.A., D.Sc., F.R.S. 10s. net.
The Theory of Determinants in the Historical Order of Development. Vol. I. Part I. General Determinants, up to 1841. Part II. Special Determinants, up to 1841. 17s. net. Vol. II. The Period 1841 to 1860. 17s. net. By T. Muir,
[Pg 270]
An Introduction to the Theory of Infinite Series. By T. J. I'A Bromwich, M.A., F.R.S. 15s. net.
Introduction to the Theory of Fourier's Series and Integrals, and the Mathematical Theory of the Conduction of Heat. By Prof. H. S. Carslaw, M.A., D.Sc., F.R.S.E. 14s. net.
TRANSCRIBER'S NOTE
Minor presentational changes, and minor typographical and numerical corrections, have been made without comment.
In Chapter XIV, pages 132-159, numerical values of
,
, and related
quantities of British currency have been verified and rounded to the
nearest digit.
On page 142 (page 146 in the original), the graphs of the natural logarithm and exponential functions, Figures 38 and 39, have been interchanged to match the surrounding text.
The vertical dashed lines in the natural logarithm graph, Figure 39 (Figure 38 in the original), have been moved to match the data in the corresponding table.
On page 164 (page 167 in the original), the graphs of the sine and cosine functions, Figures 44 and 45, have been interchanged to match the surrounding text.