Renowned statistician R.G. Miller set the pace for statistics students with Beyond ANOVA: Basics of Applied Statistics. Designed to show students how to work with a set of "real world data," Miller's text goes beyond any specific discipline, and considers a whole variety of techniques from ANOVA to empirical Bayes methods; the jackknife, bootstrap methods; and the James-Stein estimator.
This reissue of Miller's classic book has been revised by professors at Stanford University, California. As before, one of the main strengths of Beyond ANOVA is its promotion of the use of the most straightforward data analysis methods-giving students a viable option, instead of resorting to complicated and unnecessary tests.
Assuming a basic background in statistics, Beyond ANOVA is written for undergraduates and graduate statistics students. Its approach will also be valued by biologists, social scientists, engineers, and anyone who may wish to handle their own data analysis.
A course text for graduate students of biology, social science, or engineering with some knowledge of the analysis of variance, nonparametric statistics, and other techniques, but are still unsure what to do when faced with a set of living, snarling data. Describes the variety of techniques that can be brought to bear on a problem, focusing on the statistical problem rather than theory. First published in 1986 just before Miller's death, and out of print since 1991. Annotation c. by Book News, Inc., Portland, Or.