Friedman Repeated Measures Test Calculator
Calculate a tie-corrected Friedman omnibus statistic, asymptotic p-value and Kendall concordance from complete repeated-condition rows.
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Result
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Calculation steps
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How to calculate
Rank conditions within each subject, aggregate condition ranks and apply the within-block tie correction.
Q=[12ΣRj²/(n k(k+1))−3n(k+1)]/tie correction; W=Q/[n(k−1)]
Worked example
Four subjects who each rank three conditions 1,2,3 give Friedman Q=8 and concordance W=1. The small design also receives an explicit chi-square-approximation limitation.
Assumptions and input details
2–500 complete subject rows and 3–12 repeated conditions. Rows must be independent blocks; each column is the same condition across subjects. Ties receive average ranks. All-equal within-row measurements leave the statistic undefined. The p-value is asymptotic and may be unreliable for small subject/condition counts; no exact permutation or post-hoc pairwise test is implemented.
References: SciPy: repeated-sample Friedman test and asymptotic limitations
Using this calculator
Can I enter my own problem?
Yes. Replace the example values with your own inputs. The result, calculation steps, tables and applicable diagrams update from those inputs. Blank or invalid values clear the result; example values are never silently substituted for missing inputs.
Are the results exact?
Results use floating-point arithmetic and displayed rounding. Read the formula, assumptions and any stated data precision before interpreting the result.
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The calculation runs in your browser. No account, file upload or external AI service is required. Inputs are not saved between page reloads.
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