The goals of this book are to provide a text from which grad and advanced undergrads could readily learn and to provide a sourcebook for researchers. The focus of this revision is emphasis on concepts and assumptions not just formulas and learning more f
The goals of this book are to provide a text from which grad and advanced undergrads could readily learn and to provide a sourcebook for researchers. The focus of this revision is emphasis on concepts and assumptions not just formulas and learning more f
Contents: Preface. Introduction. Looking at Data: Univariate Distributions. Looking at Data: Relations Between Quantitative Variables. Probability and the Binomial Distribution. Estimation and Hypothesis Tests: The Normal Distribution. Estimation, Hypothesis Tests, and Effect Size: The t Distribution. The Chi Square and F Distributions. Between Subjects Designs: One Factor. Contrasts Among Means. Trend Analysis. Multifactor Between-Subjects Designs: Significance Tests in the Two-Way Case. Multifactor Between-Subjects Designs: Further Developments. Repeated-Measures Designs. Mixed Designs: Between-Subjects and Within-Subjects Factors. Using Concomitant Variables to Increase Power: Blocking and Analysis of Covariance. Hierarchical Designs. Latin Squares and Related Designs. More About Correlation. More About Bivariate Regression. Multiple Regression. Regression With Categorical and Quantitative Variables: The General Linear Model. t Distribution. The Chi Square and F Distributions. Between Subjects Designs: One Factor. Contrasts Among Means. Trend Analysis. Multifactor Between-Subjects Designs: Significance Tests in the Two-Way Case. Multifactor Between-Subjects Designs: Further Developments. Repeated-Measures Designs. Mixed Designs: Between-Subjects and Within-Subjects Factors. Using Concomitant Variables to Increase Power: Blocking and Analysis of Covariance. Hierarchical Designs. Latin Squares and Related Designs. More About Correlation. More About Bivariate Regression. Multiple Regression. Regression With Categorical and Quantitative Variables: The General Linear Model. Appendices: Notation and Summation Operations. Expected Values and Their Applications. Statistical Tables.
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