Friedman Test calculator

Compare three or more matched/repeated measurements. Compute the Friedman test statistic online for skewed or ordinal data.

What it does

The rank-based counterpart to repeated-measures ANOVA: ranks each subject's scores across conditions and asks whether some condition consistently ranks higher.

When to use it

The same subjects measured under three or more conditions, with an ordinal or skewed outcome.

Cautions

• Ranking happens within each subject, so it detects consistent ordering, not the size of any difference.
• A significant result needs post-hoc pairwise comparisons with a multiplicity correction to say which conditions differ.
• Any subject missing a condition is dropped entirely — check how many rows that removes.

Alternatives

• Repeated-measures ANOVA — the outcome is continuous and roughly normal within conditions
• Kruskal-Wallis — the groups are independent rather than the same subjects repeated

How to read the output

Q statistic and df

Ranks are assigned within each subject, then compared across occasions; Q is compared to a χ² with occasions − 1 df. This does not compare medians. It compares whether values in one group tend to exceed the other's. The two coincide only when the distributions have the same shape, so a significant result with differently-shaped distributions means 'these differ', not 'the median differs by X'.

N (subjects)

Ranking happens within a subject, so a subject missing any occasion cannot be ranked and is dropped entirely.

p-value

How surprising a difference at least this large would be IF the groups really were identical on this measure. A small p means the data would be surprising under that assumption. It is not the probability that the result is due to chance, and not the probability that the groups are the same — those read the conditional backwards. It also answers 'would this be surprising?', never 'is this big enough to matter?': with a large sample a trivial difference returns a small p, and the result looks identical to an important one.

How this calculator is validated · Which statistical test should I use?