One-sample variance test

When to consider it

• Compare a normal population variance against a reference variance.

Assumptions and scope

• Normal populations are required for exact inference. These tests are sensitive to non-normality; consider median-centered Levene for comparing groups.

Required inputs

• Observations — Numeric observations; preserve the row and column structure described above.
• Reference variance (squared units) — Enter the method parameter described above.

Review missing values and data coding before running. Sample inputs are synthetic teaching examples.

Implementation

Two-sided chi-square test and 95% interval for a normal population variance. Independent normal observations and positive reference/sample variances required. Sensitive to non-normality. Synthetic example: 40 independent simulated measurements, reference variance 4.

• scipy 1.15.3: scipy.stats.chi2.cdf, scipy.stats.chi2.sf, scipy.stats.chi2.ppf

These are pinned library versions; saved results record the versions actually used at runtime.

Library references

• SciPy statistical methods
• statsmodels models and statistical tests
• scikit-learn clustering
• lifelines survival comparisons