Alternating Series estimation theorem vs taylor remainder

In summary, the conversation discusses the use of Taylor's remainder theorem and the alternating series test to approximate a function with a polynomial. The resulting discussion leads to a discrepancy in the value of n needed to obtain an error less than 1/120. The discrepancy arises from the fact that the alternating series only considers odd terms, while the Taylor series includes even terms as well. This leads to a different value of n needed for the two methods.
  • #1
freshman2013
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Homework Statement



Let Tn(x) be the degree n polynomial of the function sin x at a=0. Suppose you approx f(x) by Tn(x) if abs(x)<=1, how many terms are need (what is n) to obtain an error less than 1/120

Homework Equations


Rn(x)=M(x-a)^(n+1)/(n+1)!

sin(x)=sum from 0 to ∞ of (-1)^n*x^(2n+1)/(2n+1)!

The Attempt at a Solution


For the alternating series test, I plugged in 1 for x in the sin x macluarin series and got 1/(2(n+1)+1)! <= 1/120 and got n=1
Then I used the Taylor's remainder theorem, got 1/(n+1)! <= 1/120 so n=4. why am I getting a different answer from Alternating series estimation theorem?
 
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  • #2
freshman2013 said:

Homework Statement



Let Tn(x) be the degree n polynomial of the function sin x at a=0. Suppose you approx f(x) by Tn(x) if abs(x)<=1, how many terms are need (what is n) to obtain an error less than 1/120

Homework Equations


Rn(x)=M(x-a)^(n+1)/(n+1)!

sin(x)=sum from 0 to ∞ of (-1)^n*x^(2n+1)/(2n+1)!

The Attempt at a Solution


For the alternating series test, I plugged in 1 for x in the sin x macluarin series and got 1/(2(n+1)+1)! <= 1/120 and got n=1
Then I used the Taylor's remainder theorem, got 1/(n+1)! <= 1/120 so n=4. why am I getting a different answer from Alternating series estimation theorem?

Let's write out a few terms of the two series. The alternating series is$$
x -\frac{x^3} 3 +\frac {x^5} 5~...$$
The Taylor series is$$
0+x+0-\frac {x^3} 3 + 0 +\frac{x^5} 5~...$$Does that give you an idea?
 

What is the Alternating Series Estimation Theorem?

The Alternating Series Estimation Theorem is a mathematical theorem that states if a series alternates between positive and negative terms and the absolute value of the terms decreases as the series progresses, then the series will converge to a specific value. This theorem is useful for estimating the value of a series without having to sum all of its terms.

What is the Taylor Remainder?

The Taylor Remainder is a mathematical term that refers to the difference between the actual value of a function and the value of its Taylor polynomial approximation. It is often used to measure the accuracy of a Taylor polynomial in approximating a function.

How does the Alternating Series Estimation Theorem differ from the Taylor Remainder?

The Alternating Series Estimation Theorem and Taylor Remainder are both used to estimate the value of a series or function. However, the Alternating Series Estimation Theorem applies specifically to alternating series, while the Taylor Remainder can be used for any function. Additionally, the Alternating Series Estimation Theorem provides an upper bound on the error, while the Taylor Remainder provides an exact value for the error.

When should I use the Alternating Series Estimation Theorem over the Taylor Remainder?

The Alternating Series Estimation Theorem is most useful when dealing with alternating series, as it provides a simple way to estimate the value of the series without having to sum all of its terms. The Taylor Remainder, on the other hand, is useful for approximating the value of any function, but requires more calculations for an accurate estimate.

Are there any limitations to using the Alternating Series Estimation Theorem or the Taylor Remainder?

Both the Alternating Series Estimation Theorem and the Taylor Remainder have their limitations. The Alternating Series Estimation Theorem only applies to alternating series, and may not provide an accurate estimate for series that do not alternate. The Taylor Remainder, while applicable to any function, may require a high degree Taylor polynomial to provide an accurate estimate, which can be time consuming to calculate.

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