Mean-Value Theorem, Taylor's formula, and error estimation

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Discussion Overview

The discussion revolves around the relationship between the Mean-Value Theorem (MVT) and Taylor's formula, particularly focusing on error estimation in Taylor approximations. Participants explore how MVT can be interpreted in the context of Taylor series and its implications for approximating functions.

Discussion Character

  • Exploratory
  • Technical explanation
  • Conceptual clarification
  • Debate/contested

Main Points Raised

  • One participant notes that Taylor's formula provides an error estimation similar to that of linear approximation, specifically referencing the case where n=0 relates to MVT.
  • Another participant explains that MVT indicates there is at least one point between x and a where the tangent equals the slope of the secant line, suggesting a relationship between the two concepts.
  • A participant highlights that for quadratic functions, the point described by MVT is the midpoint between x and a, while for higher-order functions, the error is influenced by delta and higher-order terms.
  • There is a request for further clarification on the implications of MVT for higher-order functions and their error estimation.

Areas of Agreement / Disagreement

Participants express varying levels of understanding regarding the implications of MVT and Taylor's formula, with some seeking clarification on specific points. There is no consensus on the exact nature of the error estimation or how MVT applies to higher-order functions.

Contextual Notes

Some participants reference specific mathematical examples and seek further explanation, indicating potential gaps in understanding or assumptions about the applicability of MVT to different types of functions.

Who May Find This Useful

This discussion may be useful for students and practitioners interested in the mathematical foundations of approximation techniques, particularly in the context of calculus and analysis.

mcastillo356
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TL;DR
Can't conclude any error estimation from MVT, i.e., Taylor's formula for ##n=0##
Hi, PF

Taylor's formula provides a formula for the error in a Taylor approximation ##f(x)\approx{P_{n}(x)}## similar to that provided for linear approximation.

Observe that the case ##n=0## of Taylor's formula, namely,

##f(x)=P_{0}(x)+E_{0}(x)=f(a)+\dfrac{f'(s)}{1!}(x-a)##,

is just the Mean-Value Theorem

##\dfrac{f(x)-f(a)}{x-a}=f'(s)## for some ##s## between ##a##

and ##x##

The question is: to what extent, i.e. how, MVT provides a formula for the error in a Taylor approximation?

Attempt: let ##f(x)=e^{x}##, ##x=2##, ##a=0##: for ##n=0##

1- ##\dfrac{e^{2}-1}{2}=e^{s}##
2- ##\ln{\dfrac{e^{2}-1}{2}}=s\cdot{\ln{e}}\Rightarrow##
3- ##\Rightarrow{s\approx{1.1614}}##
4- ##\therefore{f(s)\approx{3.1944}}\Rightarrow##
5- All I can conclude is that the slope of the chord line joining the points ##(0,1)## and ##(2,7.3890)## is equal to the slope of the tangent line to the curve ##y=e^x## at the point ##(1.1614,3.1944)##, so the two lines are parallel.
6- Which is here the error estimation, or how can I find out?

Greetings

geogebra-export.png

PS: I post with no preview. Twice edited
 
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MVT says there is at least one point between x and a that has a tangent egual to the slope of the line through f(x) and f(a) (the secant). For a quadratic, that point will always be exactly be the mid point between x and a (on the x axis). For higher order functions, the error depends on the delta and the higher order terms in the function.
 
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valenumr said:
MVT says there is at least one point between x and a that has a tangent egual to the slope of the line through f(x) and f(a) (the secant). For a quadratic, that point will always be exactly be the mid point between x and a (on the x axis).
Didn't know that fact for quadratics. Nice
valenumr said:
For higher order functions, the error depends on the delta and the higher order terms in the function.
Sorry, could this be explained furthermore?

Love, thanks @valenumr
 

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