Optimal Degree for Approximating Cosine with Taylor Series

In summary, the question asks for the degree of a MacLaurin polynomial needed to approximate cos(0.25) to 5 decimals of accuracy. This can be found using the remainder method, where |R(0.25)| = 0.00001 <= M/(n+1)! * |x - a|^(n+1). The value of M can be found by finding the largest possible value of the n+1 derivative of cosine, which can be \pm cosine or \pm sine. The process then becomes a plug-and-check game for n until the desired accuracy is achieved.
  • #1
hadroneater
59
0

Homework Statement


What degree Taylor Polynomial around a = 0(MacLaurin) is needed to approximate cos(0.25) to 5 decimals of accuracy?


Homework Equations


taylor series...to complicated to type out here

remainder of nth degree taylor polynomial = |R(x)| <= M/(n+1)! * |x - a|^(n+1)
where a = 0 in this case
and
M >= |f^(n+1)(t)|



The Attempt at a Solution


I don't really get this question at all. I know that |R(0.25)| = 0.00001 <= M/(n+1)! * |x - a|^(n+1)
But how do I get M when |f^(n+1)(t)| is unknown? I don't even know what |f^(n+1)(t)| means!
 
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  • #2
hadroneater said:

The Attempt at a Solution


I don't really get this question at all. I know that |R(0.25)| = 0.00001 <= M/(n+1)! * |x - a|^(n+1)
But how do I get M when |f^(n+1)(t)| is unknown? I don't even know what |f^(n+1)(t)| means!

f(n+1)(t) is the n+1:th derivative of f(t). So is your plan to find the lowest upper bound for Mn? It might be easier (and more likely to be correct too) if you just calculated enough terms from the series until you have the desired accuracy.
 
  • #3
But we aren't marked on that...it has to be through the remainder method.

Anyways, I know what f^(n+1)(t). I just don't know what to plug in for t. And after that, doesn't it just become a plug-and-check game for n until I get less than 0.00001?
 
  • #4
All derivatives of cosine are [itex]\pm cosine[/itex] or [itex]\pm sine[/itex]. What is the largest possible value of a sine or cosine?
 

What is the Taylor Series Remainder?

The Taylor Series Remainder is a mathematical concept used to estimate the error or the difference between a function and its Taylor polynomial approximation. It is denoted by Rn and can be used to determine the accuracy of a Taylor polynomial.

How is the Taylor Series Remainder calculated?

The Taylor Series Remainder is calculated using the Lagrange form of the remainder, also known as the Lagrange Error Bound. This formula takes into account the value of the (n+1)th derivative of the function at a certain point, as well as the distance between that point and the center of the Taylor polynomial.

What is the purpose of the Taylor Series Remainder?

The main purpose of the Taylor Series Remainder is to provide a way to measure the accuracy of a Taylor polynomial approximation. It can also be used to determine the number of terms needed in a Taylor polynomial to achieve a desired level of accuracy.

Can the Taylor Series Remainder be negative?

Yes, the Taylor Series Remainder can be negative. This may occur if the function being approximated is increasing while the Taylor polynomial is decreasing, or vice versa. In this case, the remainder would have an opposite sign to the error, indicating that the Taylor polynomial may overestimate or underestimate the function at that point.

How is the Taylor Series Remainder used in real-world applications?

The Taylor Series Remainder has various applications in fields such as physics, engineering, and economics. It is used to approximate functions that are difficult to calculate directly, and to improve the accuracy of numerical methods. It is also used in the analysis of algorithms and in the development of computer programs.

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