Friedmanoverview how to example data see also
FriedmanStat > Nonparametrics > Friedman
Friedman test is a nonparametric analysis of a randomized block experiment, and thus provides an alternative to a Two-way analysis of variance. The hypotheses are:
H0: all treatment effects are zero versus H1: not all treatment effects are zero
Randomized block experiments are a generalization of paired experiments, and the Friedman test is a generalization of the paired sign test. Additivity (fit is sum of treatment and block effect) is not required for the test, but is required for the estimate of the treatment effects.
Response: Enter the column containing the response variable.
Treatment: Enter the column that contains the treatments.
Blocks: Enter the column that contains the blocks.
Store residuals: Check to store the residuals. The residuals are calculated as the (observation adjusted for treatment effect) - (adjusted block median).
Store fits: Check to store the fitted values. The fits are calculated as the (treatment effect) + (adjusted block median).
Minitab prints the test statistic, which has an approximately chi-square distribution, and the associated degrees of freedom (number of treatments minus one). If there are ties within one or more blocks, the average rank is used, and a test statistic corrected for ties is also printed. If there are many ties, the uncorrected test statistic is conservative; the corrected version is usually closer, but may be either conservative or liberal. Minitab displays an estimated median for each treatment level. The estimated median is the grand median plus the treatment effect. For details of the method used see [2].