Statistics · Hypothesis testing

Cochran’s Q Test Calculator

Compare three or more related binary conditions across the same subjects.

Statistics · Hypothesis testing

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Private in-browser calculation · explicit assumptions
Count-based tests compare observed outcomes with the pattern expected under the null model.
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  2. 2CalculateResults update automatically
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Understand the hypothesis test

What an omnibus test can—and cannot—say

Cochran’s Q Test. An omnibus statistic asks whether all modeled groups, cells, conditions, or spreads follow one joint null statement.

Test statistic and reference model

Q=(k−1)[kΣCj²−T²]/[kT−ΣRi²], approximately χ²(k−1).

A significant omnibus result identifies some difference, not which condition pairs differ.

Responsible interpretation

A small p-value says that some modeled difference exists; it does not identify which comparisons differ. Follow-up work needs multiplicity control and effect estimates.

Required assumption: Rows are independent subjects, columns are related conditions, entries are zero or one, and follow-up comparisons need multiplicity control.

Quick guide

How to use this calculator

  1. Enter the observations, probabilities, model parameters, or summary statistics requested by the visible labels.
  2. Keep every value on the same scale and confirm that the selected sampling relationship, distribution, and tail convention match the question you are investigating.
  3. Read the result together with its assumptions and interpretation. Statistical output summarizes uncertainty under a model; it does not repair biased data or establish causation.

Calculation method

How the cochran’s q test calculator works

Q=(k−1)[kΣCj²−T²]/[kT−ΣRi²], approximately χ²(k−1).

A significant omnibus result identifies some difference, not which condition pairs differ.

Worked example

Cochran’s Q Test example

Binary condition columns entered per subject test whether marginal success rates differ.

Q=(k−1)[kΣCj²−T²]/[kT−ΣRi²], approximately χ²(k−1).

Supported inputs

Precision and limits

Model and design

Rows are independent subjects, columns are related conditions, entries are zero or one, and follow-up comparisons need multiplicity control.

Input scope

Category lists accept up to 10,000 nonblank observations and render up to 200 distinct labels. Matching trims outer whitespace but remains case-sensitive; no numeric ordering or distance is inferred.

Interpretation

A significant omnibus result identifies some difference, not which condition pairs differ.

Decision boundary

The calculator does not validate how data were collected, diagnose dependence or bias, choose a scientifically meaningful effect, or replace review by a qualified statistician for consequential research, medical, regulatory, safety, or policy decisions.

Privacy

Entered values and calculated results stay in this browser and are not sent to an analytics service.

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