Intended for the one- or two-term algebra-based course in statistical methods, this innovative book takes full advantage of the computer both as a computational and as an analytical tool. The focus is on a serious analysis of real case studies, on strategies and tools of modern statistical data analysis, on the interplay of statistics and scientific learning, and on the communication of results. It includes: -- Real-world case studies to introduce every method discussed -- Coverage that focuses on the types of problems graduate students typically encounter, with regression as the principle featured tool -- Strong, early coverage (Chapters 1-4) of the fundamentals of drawing sound inferences (introduced by means of two-sample problems) -- Excellent discussion of design issues (as they apply to case studies) throughout, with two experimental design chapters at the end of the book -- A plentiful variety of exercises: conceptual, computational, and data problems

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