Undergrad Confidence interval on Standard deviation

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The confidence interval for standard deviation can be calculated using the chi-square distribution, with degrees of freedom set at the sample size minus one, which is 499 for a sample size of 500. An online tool can assist in calculating this interval, specifically for standard deviation, and reports a range of 2.82 to 3.20 for the given values. For a 95% confidence interval, the standard deviation is reported as 0.94 times SD to 1.07 times SD. It's important to note that while the degrees of freedom is typically 499, some tools may not require this input. Accurate calculations can enhance understanding of variability in data.
iVenky
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I read that confidence interval on standard deviation can be found using chi-square distribution. If I have a sample size N=500, and sample standard deviation= 3 with mean=0, and I need a 95% confidence, I wasn't sure what to set for degrees of freedom in chi-square formula. Is the degrees of freedom same as the sample size? Is there an online-tool that can do the math for you if I enter the values?
 
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You can calculate your confidence interval with this tool:
Confidence Interval

The degrees of freedom is you sample size minus one (499), but that is not required by this tool.
 
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Hi,

Thanks for the reply, but I am interested in confidence interval of the standard deviation rather than the mean. The link that you mentioned doesn't contain the confidence interval for standard deviation
 
Thank you very much!
 
The standard _A " operator" maps a Null Hypothesis Ho into a decision set { Do not reject:=1 and reject :=0}. In this sense ( HA)_A , makes no sense. Since H0, HA aren't exhaustive, can we find an alternative operator, _A' , so that ( H_A)_A' makes sense? Isn't Pearson Neyman related to this? Hope I'm making sense. Edit: I was motivated by a superficial similarity of the idea with double transposition of matrices M, with ## (M^{T})^{T}=M##, and just wanted to see if it made sense to talk...

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