How do you find the largest interval #(c-r,c+r)# on which the Taylor Polynomial #p_n(x,c)# approximates a function #y=f(x)# to within a given error?

Answer 1
Let us assume that there is #M>0# such that
#|f^{(n+1)}(x)| le M# for all #x#.
If we want the error to be less than #epsilon>0#, then
#|R_n(x;c)|=|{f^{(n+1)}(z)}/{(n+1)!}(x-c)^{n+1}|#,
where #z# is between #x# and #c#.
by replacing #|f^{(n+1)}(z)|# by #M#,
#le M/{(n+1)!}|x-c|^{n+1} < epsilon#
By solving for #|x-c|#,
#Rightarrow |x-c| < root(n+1){{epsilon (n+1)!}/M}#

Hence,

#r=root(n+1){{epsilon (n+1)!}/M}#

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Answer 2

To find the largest interval ((c - r, c + r)) on which the Taylor Polynomial (p_n(x, c)) approximates a function (y = f(x)) to within a given error, you can use the Taylor Remainder Theorem or Taylor's Inequality.

  1. Using Taylor Remainder Theorem: Taylor Remainder Theorem states that if (f) has (n+1) continuous derivatives on an interval containing (c) and (f^{(n+1)}(x)) exists on ((c - r, c + r)), then for each (x) in ((c - r, c + r)), there exists a number (z) between (x) and (c) such that: [ R_n(x) = \frac{f^{(n+1)}(z)}{(n+1)!}(x - c)^{n+1} ] Here, ( R_n(x) ) is the remainder term of the (n)th degree Taylor polynomial. You can choose (r) such that the error (|R_n(x)|) is less than or equal to the desired error.

  2. Using Taylor's Inequality: Taylor's Inequality provides an upper bound on the error of the Taylor polynomial approximation. It states that if (f) has (n+1) continuous derivatives on an interval containing (c) and (f^{(n+1)}(x)) exists on ((c - r, c + r)), then for each (x) in ((c - r, c + r)): [ |f(x) - p_n(x, c)| \leq \frac{M}{(n+1)!}|x - c|^{n+1} ] where ( M ) is an upper bound for ( |f^{(n+1)}(x)| ) on ((c - r, c + r)). You can choose ( r ) such that ( \frac{M}{(n+1)!}|x - c|^{n+1} ) is less than or equal to the desired error.

In both cases, you may need to analyze the behavior of the function and its derivatives to find suitable values for (r).

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Answer from HIX Tutor

When evaluating a one-sided limit, you need to be careful when a quantity is approaching zero since its sign is different depending on which way it is approaching zero from. Let us look at some examples.

When evaluating a one-sided limit, you need to be careful when a quantity is approaching zero since its sign is different depending on which way it is approaching zero from. Let us look at some examples.

When evaluating a one-sided limit, you need to be careful when a quantity is approaching zero since its sign is different depending on which way it is approaching zero from. Let us look at some examples.

When evaluating a one-sided limit, you need to be careful when a quantity is approaching zero since its sign is different depending on which way it is approaching zero from. Let us look at some examples.

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