This book is a concise and innovative book that gives a complete presentation of the design and analysis of experiments in approximately one half the space of competing books. With only the modest prerequisite of a basic (non-calculus) statistics course, this text is appropriate for the widest possible audience. Two procedures are generally used to analyze experimental design data analysis of variance (ANOVA) and regression analysis. Because ANOVA is more intuitive, this book devotes most of its first three chapters to showing how to use ANOVA to analyze balanced (equal sample size) experimental design data. The text first discusses regression analysis at the end of Chapter 2, where regression is used to analyze data that cannot be analyzed by ANOVA: unbalanced (unequal sample size) data from two-way factorials and data from incomplete block designs. Regression is then used again in Chapter 4 to analyze data resulting from two-level fractional factorial and block confounding experiments.
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Bruce L. Bowerman is professor emeritus of decision sciences at Miami University in Oxford, Ohio. He received his PhD degree in statistics from Iowa State University in 1974 and has over forty years of experience teaching basic statistics, regression analysis, time series forecasting, and other courses. He has been the recipient of an Outstanding Teaching award from his students at Miami and an Effective Educator award from the Richard T. Farmer School of Business Administration at Miami.
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