The goal of statistical data analysis is to use data to gain and communicate knowledge about processes and phenomena. Comparing means is often part of an analysis, for data arising in both experimental and observational studies. Probably the most common method used to compare the means of several different treatments (or, more loosely, groups arising from stratification) is the analysis of variance (ANOVA). The analysis of means (ANOM) is an alternative procedure for comparing means. While it cannot be used in all the same settings as the ANOVA, when one is specifically interested in comparing means, such as when looking at fixed main effects in a designed experiment, ANOM has the advantages of being much more intuitive and providing an easily understood graphical result, which clearly indicates any means that are different (from the overall mean) and allows for easy assessment of practical as well as statistical significance. The graphical result is easy for nonstatisticians to understand and offers a clear advantage over ANOVA in that it sheds light on the nature of the differences among the populations.