Analysis of Variance versus Analysis of Means: A Comparative Study

Abstract

One-way analysis of variance (ANOVA) model is very famous and versatile statistical technique for studying the relation between response variable and one or more explanatory or predictor variables. In effect, ANOVA extends the two sample t-test for testing the equality of two population means to a more general null hypothesis of comparing the equality of more than two means. Meanwhile, the analysis of means (ANOM) is a graphical method for presenting multiple group comparisons with an overall mean. ANOM has enjoyed great popularity in quality control, and piles of extensions and applications have been discussed. The single-factor ANOVA and ANOM models are discussed and compared with each other‟s using actual data. The results on the cash offers and productivity improvement data are shown that the two models are not always giving the same results.