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Mathematical Expression Editor
We use a method called “linear approximation” to estimate the value of a
(complicated) function at a given point.
Given a function, a linear approximation is a fancy phrase for something you already
know:
The line tangent to the graph of a function at a point is
very close to the graph of the function near that point.
This tangent line is the graph of a linear function, called the linear approximation.
The graph of a function and the line tangent to the curve
at the point where are given in the figure below. Find the equation of the tangent
line.
Find the expression for , the slope of the tangent line to the curve at the point .
Select the correct choice.
We don’t have enough information to determine the slope.
Since we know a point and the slope of the tangent line, we can write an equation of
the tangent line.
We can define a function, , by . This function is linear, its graph is the line
tangent to the curve at the point where . This function deserves a special
name.
If is a function differentiable at , then a linear approximation for at is given by
Note that the graph of is just the tangent line to at .
A linear approximation of is a “good” approximation as long as is “not too far”
from . If one “zooms in” on sufficiently, then and the linear approximation are
nearly indistinguishable. As a first example, we will see how linear approximations
allow us to make approximate “difficult” computations.
Use a linear approximation of at to approximate .
To start, write
Now we evaluate and compare it to . From this we see that the linear approximation,
while perhaps inexact, is computationally easier than computing the cube
root.
What would happen if we chose instead? Then we would use , the linear
approximation of at . In that case, . The graph of , together with the graphs of and
is given in the figure below.
From the picture we can see that
.
So, our choice, , was better!
With modern calculators and computing software it may not appear necessary to use
linear approximations. In fact they are quite useful. In cases requiring an
explicit numerical approximation, they allow us to get a quick rough estimate
which can be used as a “reality check” on a more complex calculation. In
some complex calculations involving functions, the linear approximation
makes an otherwise intractable calculation possible, without serious loss of
accuracy.
Use a linear approximation of at to approximate .
To start, write so our linear
approximation is
Hence, a linear approximation for at is , and so . Comparing this to , we see that
the approximation is quite good. For this reason, it is common to approximate with
its linear approximation when is near zero.
Differentials
The graph of a function and the graph of , the linear approximation of at , are
shown in the figure below. Also, two quantities, and , and a point are marked
in the figure. Look carefully at the figure when answering the questions
below.
Select all the correct expressions for the quantity .
You can see that .
Select all the correct expressions for the quantity .
You can see that .
Recall: .
Based on the figure and the expression for , select all the correct expressions for .
Recall: .
So, we can write and call it a differential of at . Notice, that is a constant,
therefore is a linear function of a variable . Notice that we can define a differential at
any point of the domain of , provided that exists. We will do that in our next
definition.
Let be a differentiable function. We define , a differential of , at a
point by where is an independent variable that is called a differential
of . Geometrically, differentials can be interpreted via the diagram below.
Note, it is now the case (by definition!) that
We should not be surprised, since the slope of the tangent line in the figure is , and
this slope is also given by .
The differential is:
times .A single variable.
The differential is:
times .A single variable that is dependent on .
Essentially, differentials allow us to solve the problems presented in the previous
examples from a slightly different point of view. Recall, when is near but not equal
zero, hence, Since is simply a variable, and is simply a variable, we can replace
with to write
Adding to both sides we see or, equivalently While this is something of a “sleight of
hand” with variables, there are contexts where the language of differentials is
common. Here is the basic strategy:
We will repeat our previous examples using differentials.
Use differentials to approximate .
Set . We want to know . Since , we set . Setting ,
we have
Here we see a plot of with the differentials above marked:
Now we must compute :
Hence .
Use differentials to approximate .
Set . We want to know . Since , we will set and .
Write with me
Here we see a plot of with the differentials above marked:
Now we must compute :
Hence .
The upshot is that linear approximations and differentials are simply two slightly
different ways of doing the exact same thing.
Error approximation
Differentials also help us estimate error in real life settings.
The cross-section of a ml glass can be modeled by the function :
At cm from the base of the glass, there is a mark indicating when the glass is filled
to ml. If the glass is filled within millimeters of the mark, what are the bounds on
the volume? As a gesture of friendship, we will tell you that the volume in milliliters,
as a function of the height of water in centimeters, , is given by Note: If you persist
in your quest to learn calculus, you will be able to derive the formula above like it’s
no-big-deal.
We want to know what a small change in the height, does to the volume
. These small changes can be modeled by the differentials and . Since and
we use the fact that with to see Hence the volume will vary by roughly
milliliters.
New and old friends
You might be wondering, given a plot ,
What’s the difference between and ? What about and ?
Regardless, it is now a pressing question. Here’s the deal: is the average rate of
change of with respect to . On the other hand: is the instantaneous rate of
change of with respect to . Essentially, and are the same type of thing, they
are (usually small) changes in . However, and are very different things.
; it is the change in associated to .
, it is the change in associated to . Note: .
So, the change
Suppose . If we are at the point and , what is ? What is ?
Differentials can be confusing at first. However, when you master them, you will
have a powerful tool at your disposal.