These authors have previously described how to use the "t" test to compare two groups. In this article, they describe the use of a different test, analysis of variance (ANOVA) to compare more than two groups. ANOVA is a test of group differences: do at least two of the means differ from each other? ANOVA assumes (1) normal distribution of residuals; and (2) variation in each group is similar. In ANOVA, variation is calculated from the sum of squares (SS), and this value is given in ANOVA test results. Briefly, it is computed from the squares of the difference between each individual value and the mean value of the group that this individual value has come from. The authors point out that ANOVA may not necessarily be the best approach to analysis of several factors. This analysis is based on categories. Even if one of the sources of variation is a graded or continuous factor such as dose, each level is considered independently. This is a very general account of a widely used test. There are a lot of possible pitfalls in the more complex versions; careful planning of the study and good advice, in equal measure, are important ingredients in the successful use of analysis of variance. (Contains 2 tables and 3 figures.)