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Confidence Interval for Standard Deviation

Created:October 10, 2024
Last Updated:March 25, 2025

This calculator will compute the confidence interval for a standard deviation based on a sample. You can either upload a dataset or manually input the sample size and standard deviation.

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What is a Confidence Interval for Standard Deviation?

A confidence interval for the standard deviation provides a range of plausible values for the population standard deviation based on a sample. It gives both an estimate of the standard deviation and a measure of the uncertainty associated with that estimate.

Formulas

Exact Confidence Interval

The confidence interval for the population standard deviation σ is given by:

[(n1)s2χα/2,n12,(n1)s2χ1α/2,n12] \left[\sqrt{\frac{(n-1)s^2}{\chi^2_{\alpha/2, n-1}}}, \sqrt{\frac{(n-1)s^2}{\chi^2_{1-\alpha/2, n-1}}}\right]

Standard Error Approximation

For large samples, the standard error of the sample standard deviation is:

SE(s)=s2(n1) SE(s) = \frac{s}{\sqrt{2(n-1)}}

This can be used to construct approximate confidence intervals: s±zα/2SE(s)s \pm z_{\alpha/2} \cdot SE(s)

Where:

  • nn is the sample size
  • ss is the sample standard deviation
  • χ(p,n1)2\chi^2_{(p, n - 1)} is the p-th percentile of the chi-square distribution with n-1 degrees of freedom
  • α\alpha is the significance level (e.g., 0.05 for a 95% confidence interval)
  • zα/2z_{\alpha/2} is the critical value from the standard normal distribution

Note: The standard error approximation is simpler but less accurate for small samples. Use the exact confidence interval when possible, especially for n < 30.

Interpretation

A 95% confidence interval for the standard deviation means that if we were to repeat the sampling process many times and calculate the confidence interval each time, about 95% of these intervals would contain the true population standard deviation.

Verification

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