Suppose is a function, and we calculated its linear approximation near to be .
What is ?
What is ?
What is ?
Taylor Polynomials
9 problems · hints, answers and solutions shown beside each one
Suppose is a function, and we calculated its linear approximation near to be .
What is ?
What is ?
What is ?
The linear approximation is chosen so that and .
(a) (b) (c) not enough information to know
The linear approximation is . Since we're approximating at , , and . However, there is no guarantee that and have the same value when . So:
(a)
(b)
(c) there is not enough information to find .
The curve is shown below. Sketch the linear approximation of about .
The graph of the linear approximation is a line, passing through , with slope .
The linear approximation is shown in red.
The linear approximation is a line, passing through , with slope . That is, the linear approximation to about is the tangent line to at . It is shown below in red.
What is the linear approximation of the function about ?
It's an extremely accurate approximation.
For any constant , , and , so our approximation gives us
Since itself is a linear function, the linear approximation is actually just itself. As a consequence, the linear approximation is perfectly accurate for all values of .
Use a linear approximation to estimate when . Sketch the curve and your linear approximation.
(Remember we use to mean the natural logarithm of , .)
You'll need to centre your approximation about some , which should have two properties: you can easily compute , and is close to .
We have no idea what is, but 0.93 is pretty close to 1, and we definitely know . The linear approximation of about is given by
So, we calculate:
Therefore,
When :
Use a linear approximation to estimate .
Approximate the function .
We approximate the function about , since 4 is a perfect square and it is close to 5.
We estimate .
Remark: , which is pretty close to . Our approximation seems pretty good.
Use a linear approximation to estimate
Approximate the function .
We approximate the function . We need to centre the approximation about some value such that we know and , and is not too far from .
needs to be a number whose fifth root we know. Since , and 32 is reasonably close to 30, is a great choice.
The linear approximation of about is
When :
We estimate .
Remark: , while . This is a decent estimation.
Use a linear approximation to estimate , then compare your estimation with the actual value.
Approximate the function .
,
If , then , which is the value we want to estimate. Let's take the linear approximation of about :
We estimate . If we calculate exactly (which is certainly possible to do by hand), we get 1030.301.
Remark: in the previous subsection, we used a constant approximation to estimate . That approximation was easy to do in your head, in a matter of seconds. The linear approximation is more accurate, but not much faster than simply calculating .
Imagine is some function, and you want to estimate . To do this, you choose a value and take an approximation (linear or constant) of about . Give an example of a function , and values and , where the constant approximation gives a more accurate estimation of than the linear approximation.
One possible choice of is .
There are many possible answers. One is , , and .
There are many possible answers. One is:
We know that and . Using a constant approximation of about , our estimation is , which is exactly the correct value. However, is we make a linear approximation of about , we get
which is not exactly the correct value.
Remark: in reality, we wouldn't estimate , because we know its value exactly. The purpose of this problem is to demonstrate that fancier approximations are not always more accurate. At the of this section, we'll talk about how to bound the error of your estimations, to make sure that you are finding something sufficiently accurate.
The function
is the linear approximation of about what point ?
Compare the derivatives.
The linear approximation of about is chosen so that and . So,
We've narrowed down to or . Recall the linear approximation of about is so its constant term is . We compute this for and .
So, when ,
and this does not hold when . We conclude .
From the UBC Math 100 open textbook project, © Joel Feldman, Andrew Rechnitzer, Elyse Yeager and others. Licensed CC BY-NC-SA 4.0; this HTML adaptation is released under the same licence. Full attribution.