Estimating error using comparison/limit comparison test

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SUMMARY

The discussion centers on the correct application of the comparison test for estimating error in series approximations. The user seeks clarification on whether to use the formula R_{n} ≤ T_{n} ≤ ∫_{n+1}^{∞} or R_{n} ≤ T_{n} ≤ ∫_{n}^{∞} for estimating the error when approximating the sum of a series using the first 10 terms. The confusion arises from differing methods presented in textbooks, particularly regarding the indexing for p-series and geometric series. Visual aids, such as diagrams illustrating the integration area, are recommended for better understanding.

PREREQUISITES
  • Understanding of series convergence and divergence
  • Familiarity with the comparison test in calculus
  • Knowledge of p-series and geometric series
  • Basic skills in integral calculus
NEXT STEPS
  • Review the comparison test for series convergence in calculus textbooks
  • Study the differences between p-series and geometric series
  • Learn how to visually represent series approximations using diagrams
  • Practice estimating errors in series using both methods discussed
USEFUL FOR

Students and educators in calculus, particularly those focusing on series and convergence tests, as well as anyone seeking to clarify the application of the comparison test for error estimation in series approximations.

motornoob101
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I am confused about the right formula for this. Is it

[itex]R_{n} \leq T_{n} \leq \int_{n+1}^{\infty}[/itex] or [itex]R_{n} \leq T_{n} \leq\int_{n}^{\infty}[/itex]?

Say for example, I want to estimate the error in using the sum of the first 10 terms to approximate the sum of the series.

The textbook seems to use both methods (Use n for the p-series and n+1 for the geometric series)

(as seen in the examples here)

http://p3t3rl1.googlepages.com/textsolutionconfused.jpg

and I am quite confused which it is the right way. I am wondering if someone could clear this up for me. Thanks!
 
Last edited by a moderator:
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It is always best to draw a picture, not an exact one, but one that contains the crucial rectangles. The index depends on how the integration area is split into equidistant parts and whether you start counting by ##0## or by ##1##.
 

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