StatsTest Blog
Experimental design, data analysis, and statistical tooling for modern teams. No hype, just the math.
Kolmogorov-Smirnov Test
The Kolmogorov-Smirnov Test compares a sample to a reference distribution or compares two samples to each other. Use it to test goodness-of-fit to any continuous distribution or to detect distribution drift.
Levene's Test
Levene's Test checks whether two or more groups have equal variances (homogeneity of variance). Use it to verify the equal-variance assumption before running ANOVA or t-tests.
Shapiro-Wilk Test
The Shapiro-Wilk Test evaluates whether a sample comes from a normally distributed population. Use it to check the normality assumption before running parametric tests like t-tests or ANOVA.
Log-Linear Analysis
Log-Linear Analysis is a test used to determine if the proportions of categories in two+ group variables significantly differ from each other.
Chi-Square Test of Independence
The Chi-Square Test of Independence is a test used to determine if the proportions of categories in two group variables differ from each other.
Exact Test of Goodness of Fit (multinomial model)
The multinomial exact test is a test used to determine if the proportions of categories in a single qualitative variable differ from an expected proportion.
Exact Test of Goodness of Fit
The Exact Test of Goodness of Fit is used to determine if the proportions of categories in a single qualitative variable differ from an expected proportion.
Fisher's Exact Test
Fisher's Exact Test is a statistical test used to determine if the proportions of categories in two group variables significantly differ from each other.
G-Test of Goodness of Fit
The G-Test of Goodness of Fit is used to determine if the proportions of categories in a single qualitative variable differ from an expected proportion.
G-Test
The G-Test is a test used to determine if the proportions of categories in two group variables significantly differ from each other.
McNemar Test
The McNemar Test is a statistical test used to determine if the proportions of categories in two related groups significantly differ from each other.
