The computation of the mean square for treatments in a balanced one-way analysis of variance is trivial on any hand calculator with a variance or standard deviation key. More importantly, the calculation reinforces the fundamental and intuitive idea behind the balanced analysis of variance test, i.e., that a mean square for treatments is just a multiple of the sample variance of the corresponding treatment means. I think that automated computation should be motivated by boredom rather than bafflement. In addition to the four primary themes discussed above, there are several other characteristics that I have tried to incorporate into this book. I have tried to use examples to motivate theory rather than to illustrate theory.
Most chapters begin with data and an initial analysis of that data.
After illustrating results for the particular data, we go back and examine general models and procedures. As mentioned earlier, the theoretical material is generally confined to separate subsections or, less often, separate sections, so it is easy to ignore. I believe that the ultimate goal of all statistical analysis is prediction of observable quantities. I have incorporated predictive inferential procedures where they seemed natural. To this end, I have tried to consistently examine residual plots, to present alternative analyses using different transformations and case deletions, and to give some final answers in plain English.