Remainder Estimation Theorem & Maclaurin Polynomials :[

In summary, the Remainder Estimation Theorem states that if f(x) can be approximated by p(x) to three decimal-place accuracy throughout the interval, then |f(x) - p(x)| is less than or equal to (M/(n+1)!)|x-xo|^(n+1).
  • #1
raincheck
38
0

Homework Statement



Use the Remainder Estimation Theorem to find an interval containing x=0 over which f(x) can be approximated by p(x) to three decimal-place accuracy throughout the interval. Check your answer by graphing |f(x) - p(x)| over the interval you obtained.

f(x)= sinx
p(x)= x - (x^(3)/3!)


Homework Equations



Remainder Estimation Theorem:
|Rn(x)| is less than or equal to (M/(n+1)!)|x-xo|^(n+1)


The Attempt at a Solution



i honestly have NO idea how to do this problem.. am i supposed to find the Maclaurin polynomial of sinx?

any help would be sooo appreciated!
 
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  • #2
p(x) IS the Maclaurin series for sin(x) up to n=4. Carefully write down the remainder term R and figure out how small x should be to guarantee R<0.001. Right?
 
  • #3
Hmm well that makes sense, but how do I find the remainder term? I don't understand that..
 
  • #4
You wrote down a somewhat garbled form of it in part 2). Look it up and figure out what the parts are in this particular case (sin(x) expanded around x=0).
 
  • #5
Oh.. is it Rn(x) = f(x) - pn(x) = f(x) - [sigma] (f^(k)*(xo))/k! * (x-xo)^k ?

That's the only other equation I can find..
 
  • #6
Noooo. No quite. It's actually more like your form in 2. Let's use that if you can tell me what M and x0 are.
 
  • #7
I guess I would say xo is 0? And M is |F^(n+1)(x)| ?
 
  • #8
That's a pretty good guess. Except that M is the maximum of the expression you wrote over all of the x in the interval where we are going to use R. Is that what you meant to say? Now can you think of a good ESTIMATE (upper bound) for M?
 
  • #9
Right.. M is the upper bound.. And I'm trying to find an interval with x=0 in it, so could the upper bound be pi? or 1? Ok, I'm not sure.
 
  • #10
What is f^(n+1)(x) in this case? While we are at it what is n? You are getting there.
 
  • #11
Isnt it the nth+1 derivative of ...sinx?
Hahah I don't feel like I'm getting it at all :[
 
  • #12
Why so glum? You are exactly right. What is n (there are two right answers!).
 
  • #13
Hmm.. I don't know isn't just infinity? Or does it get a value?
 
  • #14
It definitely gets a value! The series expansion may be infinite, but the remainder term estimates the error in truncating the infinite series to a finite one. What is the highest power in our FINITE series? (It's on your question page.)
 
  • #15
OH! Hmm..all that's on my question page is.. 0?
 
  • #16
raincheck said:
f(x)= sinx
p(x)= x - (x^(3)/3!)

One of these is a truncated series. Exercise: DO work out the Maclaurin expansion of sin(x). Maybe this is not what you are getting.
 
  • #17
Sorry. Meant to say "This is maybe what you are NOT getting."
 
  • #18
So: let xo = 0?
f(x)= sinx, f(0)=0 po(x)=0
f'(x)= cosx, f'(0)=1 p1(x)=x
f''(x)= -sinx, f''(0)=0 p2(x)= x
f'''(x)= -cosx, f'''(0)=-1 p3(x)=x - (1/3!)x^3
 
  • #19
Bravo! So we want the remainder term for which value of n?
 
  • #20
Hahah ummmmm... the p3?
 
  • #21
Right again! So you want R3(x). You could also use R4(x) since the x^4 term in the series vanishes, right? Now give me R3 and R4 - and tell me how to estimate the max(f^(n+1)(x)) part. Then you are practically done.
 
  • #22
Ohh ok awesome!
So R3(x) would be f(x) - p3(x) since its the remainder?
maybe... .008?
 
  • #23
More or less, yes. But give me the remainder term in the form you quoted in in part 2 of your question. It will indeed estimate the difference between sin(x) and p3(x).
 
  • #24
" |Rn(x)| is less than or equal to (M/(n+1)!)|x-xo|^(n+1) "

so am I using 3 as n?
Sorry for completely not getting this!
 
  • #25
Yesssss. Use n=3 (or 4). ESTIMATE M. It's a sin or a cos of something right? How big can it possibly be?
 
  • #26
OH ok
" |Rn(x)| is less than or equal to (M/(n+1)!)|x-xo|^(n+1) "

so (1/4!)|-xo|^(4) ?
I already know xo right? I still don't know what it is though..
 
  • #27
Let's call that good enuf. So R3(x)<=|x^4|/4!. (x0=0 right?). R3(x) is the size of the error you make when you when you evaluate p3(x) as an approximation to sin(x). You can see that as x gets big, the error can get big. The question you are being asked to answer is how big can x get and still keep R3(x)<0.001 (the three decimal places).
Sorry, I've got to run. I'll check in tomorrow... Good luck!
 
  • #28
so .001 = (x^4)/4! ? Would I solve for x?
Thanks so much for helping me! :]
 

Related to Remainder Estimation Theorem & Maclaurin Polynomials :[

What is the Remainder Estimation Theorem?

The Remainder Estimation Theorem is a mathematical tool that allows us to estimate the error in approximating a function with a polynomial. It is especially useful for approximating functions that are difficult to integrate or differentiate.

What is the Maclaurin Polynomial?

The Maclaurin Polynomial is a special case of the Taylor Polynomial, which is a polynomial that approximates a function by using its derivatives at a single point. In the case of the Maclaurin Polynomial, the point is chosen to be 0.

How is the Remainder Estimation Theorem used with Maclaurin Polynomials?

The Remainder Estimation Theorem is used to calculate the maximum possible error in approximating a function with a Maclaurin Polynomial. This allows us to determine the accuracy of the approximation and make adjustments if needed.

What are the main applications of the Remainder Estimation Theorem & Maclaurin Polynomials?

The Remainder Estimation Theorem and Maclaurin Polynomials have various applications in mathematics, physics, and engineering. They are used in numerical analysis, optimization, and solving differential equations, among others.

What are the limitations of the Remainder Estimation Theorem & Maclaurin Polynomials?

The Remainder Estimation Theorem and Maclaurin Polynomials are limited to approximating functions that are infinitely differentiable and have a convergent Taylor series. They may also not provide accurate approximations for functions with large intervals of convergence or highly oscillatory behavior.

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