This section contains an example with a one-way analysis of variance (ANOVA) with three groups and seven observations.

Significant differences were determined using one-way analysis of variance with standard post-hoc testing (Statview, version 5.0, SAS Institute, Cary, NC).

The Brown-Forsythe test statistic is the F statistic resulting from an ordinary one-way analysis of variance on the absolute deviations from the median.

In statistics, one-way analysis of variance (abbreviated one-way ANOVA) is a technique used to compare means of two or more samples (using the F distribution).

The F-test in one-way analysis of variance is used to assess whether the expected values of a quantitative variable within several pre-defined groups differ from each other.

The parametric equivalent of the Kruskal-Wallis test is the one-way analysis of variance (ANOVA).

Since it is a non-parametric method, the Kruskal-Wallis test does not assume a normal distribution, unlike the analogous one-way analysis of variance.

Comparisons between the four groups at the same time point were analyzed by one-way analysis of variance followed by Tukey's-b post hoc test, where appropriate.

Comparison among groups of data were made using either an unpaired Student's t test or one-way analysis of variance (ANOVA), followed by a Bonferroni's post test.

In both groups of patients, the existence of a dose-related effect was investigated using a one-way analysis of variance for repeated measures including only the different concentrations of NO.