What is a contingency table?

It's a matrix showing the frequency distribution of two categorical variables (e.g., rows = Gender, columns = Subscription Tier). The AI will automatically convert your raw data into this format.

Does it handle expected frequencies below 5?

The engine computes the result regardless, but the AI is instructed to warn you when expected frequencies are low, as the chi² approximation becomes less reliable in those cases.

Can it test more than two variables at once?

This engine performs a single pairwise independence test per execution. For multi-variable analysis, the AI can chain multiple calls to test different variable pairs sequentially.

Chi-Square Test Engine MCP Connector for Claude

A+

Run exact Chi-Square independence tests on contingency tables local. Get CPU-guaranteed chi² statistics and p-values for categorical analysis.

1 tools Official Updated Oct 1, 2026 Official Vinkius Partner

More Details Connect to Claude

The Chi-Square test determines whether two categorical variables are independent. Asking an LLM to compute expected frequencies across a matrix and then sum the chi² residuals is a recipe for hallucinated results.

This MCP computes the full test deterministically using jstat. The AI sends the observed frequency matrix, and the engine calculates exact expected frequencies, the chi² statistic, degrees of freedom, and the p-value — all locally on your CPU.

The Superpowers

Zero Hallucination: Exact chi² statistics computed deterministically.
Automatic Expected Frequencies: The engine builds the entire expected matrix internally.
Any Matrix Size: Supports 2x2, 3x3, or larger contingency tables.
Data Privacy: Your survey and business data stays local.

statisticsdata-analysiscategorical-datahypothesis-testingmath-enginedata-science