Taylor Approximations and Error Analysis for ln(x+1) and arcsin(0.4)

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In summary, the first question asks to use Taylor's Theorem to determine the accuracy of the approximation of arcsin(0.4), which can be calculated using the formula R_n(x) = \frac{f^{N+1}(c)}{(N+1)!}(x-a)^{N+1}. The book answer is R_{3} \leq 7.82 * 10^{-3}. The second question involves finding the degree of the Maclaurin polynomial needed for the error in the approximation of ln(x+1) at x=1.5 to be less than 0.0001, which can be solved using the same formula with a=0 and the book answer being N=9
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clairez93
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Homework Statement



1. Use Taylor's Theorem to determine the accuracy of the approximation.

[tex] arcsin(0.4) = 0.4 + \frac{(0.4)^{3}}{2*3}}[/tex]

2. Determine the degree of the Maclaurin polynomial required for the error in the approximation of the function at the indicated value fo x to be less than 0.0001. Use a symbolic differentiation utility to obtain and evaluate the required derivatives.

[tex]f(x) = ln(x+1)[/tex] approximate f(1.5)

Homework Equations





The Attempt at a Solution



1.
[tex]f(x) = arcsin (0.4)[/tex]
[tex] x = 0.4[/tex]
[tex]a = 0.5[/tex]
[tex]N = 3[/tex]

[tex]R_{n}(x) = \frac{f^{N+1}(c)}{(N+1)!}(x-a)^{N+1}[/tex]
[tex]R_{3}(0.4) = \frac{f^{4}(c)}{4!}(0.4-0.5)^{4}[/tex]
[tex]= \frac{\frac{-3c(2c^{2}+3)}{(c^{2}-1)^{3}\sqrt{1-c^{2}}}}{4!}(0.4-0.5)^{4}[/tex] [tex]\leq[/tex] [tex]\frac{(0.4-0.5)^{4}}{4!} = 4.166666667 * 10^{-6}[/tex]

Book Answer: [tex]R_{3} \leq 7.82 * 10^{-3}[/tex]


No idea what I did wrong here.

2.
[tex]f(x) = ln(x+1)[/tex]
[tex]a = 0[/tex]
[tex]x = 1.5[/tex]
[tex]N = ?[/tex]

[tex]R_{n}(x) = \frac{f^{N+1}(c)}{(N+1)!}(x-a)^{N+1}[/tex]
[tex]R_{n}(x) = \frac{f^{N+1}(c)}{(N+1)!}(1.5)^{N+1}[/tex]
[tex]|R_{n}(1.5)| \leq 0.0001[/tex]

To make a long sheet of work short, I got all the way up to N=12 before I finally got to 0.0001. Here is the work for N=12:

N=12: [tex]|R_{12}(1.5)| = |\frac{f^{13}(c)}{13!}(1.5)^{13}| = |\frac{(479001600)}{(c+1)^{13}} * \frac{(1.5)^{13}}{13!}| = |\frac{(479001600)(3.1254*10^{-8})}{(c+1)^{13}}| = \frac{14.9707}{(c+1)^{13}} [/tex]

[tex]\frac{14.9707}{(1.5+1)^{13}} = 0.0001[/tex]

The book answer says N=9, for which when I tested I got this:

N=9: [tex]|R_{9}(1.5)| = |\frac{f^{10}(c)}{10!}(1.5)^{10}| = |\frac{(-362880)}{(c+1)^{10}} * \frac{(1.5)^{10}}{10!}| = |\frac{(-362880)(0.000106)}{(c+1)^{10}}| = \frac{5.7665}{(c+1)^{10}} [/tex]

[tex]\frac{5.77665}{(1.5+1)^{10}} = 0.000605[/tex] which isn't exactly less than 0.001.


When I went back through my notes to see if I did something wrong, I realized that since the function was decreasing, (c+1), on the bottom of the fraction, maybe I should have plugged in 0, since c should be greater than or equal to 0 and less than or equal to 1.5, thus the biggest R could be would be whatever I get when I plug 0 in, not 1.5.

However, if I plug in 0 for these instead of 1.5, it seems to make the problem worse, since as you can see, N=9, with 0 instead of 1.5 for C would get 1 on the bottom and thus R_9 would be 5.77665, which is very very far from 0.0001, much farther than when I used 1.5.

I'm thoroughly frustrated by this one. Please help!
 
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  • #2
You chose a=0.5. Probably that is a good choice. But then what would be the Taylor series? Not the one shown. So the writers of the problem did not choose a=0.5. What did they choose? The point is that the Taylor series for their choice is much simpler to write down than for your choice a=0.5.
 
  • #3
I think they chose a=0? Is that right?
 
  • #4
a = 0 is the way to get that Taylor series, yes. So do the rest of the problem on that basis.
 

FAQ: Taylor Approximations and Error Analysis for ln(x+1) and arcsin(0.4)

What are Taylor approximations?

Taylor approximations, also known as Taylor series, are mathematical methods used to approximate a function using a polynomial expression. They are used to estimate the behavior of a function at a specific point by using the derivatives of the function at that point.

How are Taylor approximations calculated?

Taylor approximations are calculated using the Taylor series formula, which involves taking the derivatives of a function at a specific point and using them to construct a polynomial expression. The more terms included in the series, the more accurate the approximation will be.

What is the purpose of using Taylor approximations?

The main purpose of using Taylor approximations is to approximate the behavior of a function at a specific point, especially for functions that are difficult to calculate directly. They can also be used to simplify complex functions and make them easier to work with.

What is the difference between Taylor series and Taylor polynomials?

Taylor series refers to the entire infinite series of terms used to approximate a function, while Taylor polynomials are finite expressions that involve a specific number of terms in the series. Taylor polynomials are more useful for practical applications since they are easier to calculate and provide a good enough approximation for most cases.

What are the limitations of using Taylor approximations?

Taylor approximations are limited by their accuracy, which depends on the number of terms included in the series. Including too few terms can result in a poor approximation, while including too many terms can make the expression too complex to be useful. Additionally, Taylor approximations only work for functions that are infinitely differentiable at the point of approximation.

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