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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.
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