Calculating Degree of Taylor Polynomial for Approximating sqrt(e)

In summary, the degree of the Taylor polynomial needed to approximate sqrt(e) with error < 0.001 is 4, with a remainder term of [1.648/(n+1)!](0.5)^n+1. To find n, the value of M must be estimated by finding the upper bound of the (n+1)th derivative of e^x on the interval [0,1/2]. This can be done by testing different values of n until the remainder term is less than 0.001. If the function is not always the same derivative, another method must be used to estimate M.
  • #1
IntegrateMe
217
1
I just need help on how to start the problem, I'm not asking anyone to do it for me, I'm just slightly confused.

What is the degree of the Taylor polynomial needed to approximate sqrt(e) with error < 0.001. Use ex as your function, with x = 0.5.

I'm just honestly confused on where to even start, any help is greatly appreciated. Thanks.
 
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  • #2
Look up some form of the remainder term for a Taylor series and try to bound it by 0.001. I'm guessing you know the Taylor series for e^x, right?
 
  • #3
Yes, by "Taylor series" I'm assuming you mean the Maclaurin series centered at 0, so:

xn/n!

By "remainder form" do you mean Taylor's inequality:

R(x) = [M/(n+1)!][x-a]n+1

?

Thanks for the help.
 
  • #4
You asked "how to even start". I told you how to start. If you had presented that info to begin with we could have skipped the preliminaries. Ok, so now try to bound your R by 0.001. What's the largest M can be if x=1/2?
 
  • #5
I'm sorry. Don't get mad at me, I'm really trying.

How would i find out the M value without knowing what a or n equal? Taylor's inequality is what i really struggle with, I'm pretty good with figuring out series, but when it comes to "error" problems I'm a little shakey.
 
  • #6
IntegrateMe said:
I'm sorry. Don't get mad at me, I'm really trying.

How would i find out the M value without knowing what a or n equal? Taylor's inequality is what i really struggle with, I'm pretty good with figuring out series, but when it comes to "error" problems I'm a little shakey.

Sure. What is M? That's the thing you really need to estimate. How is it defined?
 
  • #7
We want to show that as n goes to infinity, the remainder will go to 0, correct? Because doesn't that show that we have a series that adequately represents our function? But in this case it's asking for the "degree" and isn't "n" the degree of the polynomial? I'm not sure what "M" represents, is it the upperbound?
 
  • #8
Ok, sure M will go to zero if it's a convergent Taylor series. But you want to know how fast it goes to zero so you can decide how many terms to keep. Doesn't M have something to do with the (n+1)th derivative of e^x on the interval [0,1/2]? Surely you can estimate that?
 
  • #9
The derivative of e^x will always be e^x, so no matter how many terms we add ( (n+1)th ), we will always have the same function.

So, am i trying to calculate the values of x that will make e^x bound within [0,1/2] ?
 
  • #10
Wait, so does that mean the fx+1(x) must be less than M.

So the nth derivative being ex:

ex<M
So, e0.5 < M
1.6487 < M

I may be completely wrong, just throwing something out there that i saw.
 
  • #11
Yes. That will bound M. Now write the whole remainder term in terms of n and try to find an n so it's less than 0.001.
 
  • #12
You lost me there, I'm sorry :/

I'm trying to find "n." I have all of my values except "n" and "a" so:

0.001 = [1.648/(n+1)!](0.5 - a)^(n+1)

I'm up to this point...if I'm correct.
 
  • #13
"a" is 0, isn't it? You were the one who said "Maclaurin series". So ok, 1.648*(0.5)^(n+1)/(n+1)!. Find an n so that's less than 0.001. This isn't all that hard, right?
 
  • #14
Haha, i get frightened to assume things that i don't know are 100% fact. Thanks for reassuring :)

Oh, ok. So i just set 1.648*(0.5)^(n+1)/(n+1)! < 0.001 and solve for n?

I get n = 4 by just plugging in different values for "n." Is there a more efficient way of doing this or is testing different values optimal?

btw, thanks a ton for the help...life saver!
 
  • #15
Testing different values of n is the perfect way to do it. Just looking at that expression you know n can't be too big. You're welcome.
 
  • #16
Thanks, i just have one more question. When we did this problem, our function e^x always had the save derivative. What happens if we get a different function where the f^n+1 isn't always the same?
 
  • #17
Then you have to find some other way to estimate the max of f^(n+1) by some other method. Like if f(x)=sin(x), then it's pretty safe to say |f^(n+1)(x)|<=1. Stuff like that.
 
  • #18
Ahh, ok. I have a pretty incompetent teacher and trying to make sense of the proofs represented in the book is often hard. Thanks for your help and care :)
 
  • #19
What if f(x) is equal cos(0.5)?
 
  • #20
zaboda42 said:
What if f(x) is equal cos(0.5)?

Then f(x) is a constant. Don't be silly. Do you mean f(x)=cos(0.5*x)?
 
  • #21
No I am just asking because would that mean that M is >= 0? Because the n+1'th derivative of cos(0.5) is just 0. Or, is M just the function itself?...

M >= cos(0.5)
 
  • #22
Oh, I see, you want cos(0.5) using the Taylor series for cos(x) around x=0. Not f(x)=cos(0.5). Do the same thing IntegrateMe did. M is related to a derivative of cos(x). Isn't it bounded by 1?
 

1. What is the formula for calculating the degree of Taylor polynomial for approximating sqrt(e)?

The formula for calculating the degree of Taylor polynomial for approximating sqrt(e) is n = (d + 1)/2, where n is the degree of the polynomial and d is the number of derivatives taken at the center point.

2. How do you choose the center point for calculating the degree of Taylor polynomial for approximating sqrt(e)?

The center point for calculating the degree of Taylor polynomial for approximating sqrt(e) is usually chosen to be the point at which the polynomial will be most accurate. This can be determined by evaluating the derivatives of sqrt(e) at different points and choosing the one with the smallest error.

3. What is the significance of the degree of Taylor polynomial for approximating sqrt(e)?

The degree of Taylor polynomial for approximating sqrt(e) represents the number of terms in the polynomial that will be used to approximate the function. A higher degree polynomial will result in a more accurate approximation, but will also require more calculations.

4. Can the degree of Taylor polynomial for approximating sqrt(e) be greater than the number of derivatives taken?

No, the degree of Taylor polynomial for approximating sqrt(e) cannot be greater than the number of derivatives taken. This is because the number of terms in the polynomial is determined by the number of derivatives taken, and a polynomial cannot have a higher degree than the number of terms it contains.

5. How can the degree of Taylor polynomial for approximating sqrt(e) be used to improve the accuracy of the approximation?

The degree of Taylor polynomial for approximating sqrt(e) can be used to improve the accuracy of the approximation by increasing the number of terms in the polynomial. This can be done by taking more derivatives at the center point, which will result in a higher degree polynomial and a more accurate approximation of sqrt(e).

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