StatsTest Blog
Experimental design, data analysis, and statistical tooling for modern teams. No hype, just the math.

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.

Two Proportion Z-Test
The Two-Proportion Z-Test is a test used to determine if the proportions of categories in two group variables differ from each other.

Chi-Square Goodness Of Fit Test
The Chi-Square Goodness Of Fit Test is a test used to determine if the proportions of categories in a qualitative variable differ from expected proportions.

One-Proportion Z-Test
The One-Proportion Z-Test is used to determine if the proportions of categories in a single qualitative variable differ from an expected proportion.

One-Way ANCOVA
The One-Way ANCOVA is a test used to determine if 3+ groups are different from each other on your variable of interest in the presence of a covariate.