Finding Error in Alternating Series

In summary, the conversation discusses determining the convergence of a given series and finding the sum with a given error bound. The series is found to converge using the Leibniz Criterion and Cauchy Criterion. The error is then determined to be less than the absolute value of the m+1 term when summing the first m terms of the series.
  • #1
SclayP
27
0
The problem statement says to find out if the next series converge, and if it does to calculate the sum with an error [tex]ε< 10^{-3}[/tex]

The serie is this one

[itex]\sum^{\infty}_{n=1} (-1)^nne^{-n}[/itex]
First of all the serie converges because of Leibniz Criterion but the i did the series of |an|

I did it with Cauchy Criterion and the seris converges again...

[itex]\sum_{n=1}^{\infty} \frac{n}{e^{-n}}[/itex]

[tex]\lim_{n \rightarrow +\infty} \frac{\sqrt[n]{n}}{\sqrt[n]{e^n}}[/tex]

[tex]\lim_{n \rightarrow +\infty} \frac{\sqrt[n]{n}}{e}[/tex]

[tex]\frac{1}{e}<1[/tex]

Now i have to find the error and that i don't know how to do it..

Thank.
 
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  • #2
With an alternating series whose terms are decreasing there's an easy method. If you sum the first m terms of your series then the error is less the absolute value of the m+1 term.
 

FAQ: Finding Error in Alternating Series

What is a "Problem - Series with error"?

A "Problem - Series with error" refers to a series of data points or measurements that contain errors or inconsistencies. These errors can occur due to various factors such as human error, equipment malfunction, or natural variation in the data.

Why is it important to identify and address errors in a series of data?

Identifying and addressing errors in a series of data is crucial because it ensures the accuracy and reliability of the data. If errors are left unaddressed, it can lead to incorrect conclusions and unreliable results.

How can errors in a series of data be identified?

Errors in a series of data can be identified through various methods such as visual inspection, statistical analysis, and cross-checking with other data sources. It is also important to have a thorough understanding of the data and the potential sources of error.

What are some common types of errors in a series of data?

Some common types of errors in a series of data include measurement errors, transcription errors, sampling errors, and data entry errors. These errors can be caused by various factors such as faulty equipment, human error, or incorrect data recording.

How can errors in a series of data be corrected?

Once errors have been identified, they can be corrected by either removing the erroneous data points or by making adjustments to the data based on the type and source of the error. It is important to document any changes made to the data to maintain transparency and accuracy.

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