XLSTAT - One-sample variance test

Use of the one-sample variance test

Use this tool to compare the variance of a normally-distributed sample with a given value.

Description of the one-sample variance test

Let us consider a samle of n independent normally distributed observations. One shows that the sample variance, s² follows a scaled chi-squared distribution with n-1 degrees of freedom.

s² ~ [σ²/(n-1)] * Χ²n-1

where s² is the theoretical sample variance. This allows us to compute a confidence interval around the variance.

To compare this variance to a reference value, a parametric test is proposed. It is based on the following statistic:

Χ0² = (n-1) s²/σ0²

which follows a chi-square distribution with n-1 degrees of freedom.

This test is said to be parametric as its use requires the assumption that the samples are distributed normally. Moreover, it also assumed that the observations are independent and identically distributed. The normality of the distribution can be tested beforehand using the normality tests.

Three types of test are possible depending on the alternative hypothesis chosen:

For the two-tailed test, the null H0 and alternative Ha hypotheses are as follows:

  • H0 : s² = s0²
  • Ha : s² ≠ s0²

In the left one-tailed test, the following hypotheses are used:

  • H0 : s² = s0²
  • Ha : s² <s0²

In the right one-tailed test, the following hypotheses are used:

  • H0 : s² = s0²
  • Ha : s² >s0²

XLSTAT

This analysis is available in the XLStat-Base addin for Microsoft Excel

About KCS

Kovach Computing Services (KCS) was founded in 1993 by Dr. Warren Kovach. The company specializes in the development and marketing of inexpensive and easy-to-use statistical software for scientists, as well as in data analysis consulting.

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