4.4.1—Non-parametric tests

A non-parametric test uses limited assumptions, often the signs or ranks of observations rather than a normal model. It is useful when outliers, skew or ordinal data make a parametric test unsuitable.

State the null and alternative, preserve pairing or independence, and use the exact sampling distribution or critical region specified for the statistic.

For paired measurements, analyse the signs of within-pair differences rather than treating the two columns as independent samples.

“Non-parametric” does not mean assumption-free: independence, symmetry or a meaningful ordering may still be required.