Experimental Design and Analysis for Psychology

Herve Abdi He is currently a full professor in the School of Behavioral and Brain Sciences at the University of Texas at Dallas and an adjunct professor of radiology at the University of Texas Southwestern Medical Centerat Dallas. His research interests include face processing and computational models of face processing, neural networks, computational and statistical models of cognitive processes (especially memory and learning), experimental design, and multivariate statistical analysis. He has published several books and papers in these domains.Betty Edelman teaches Statistics for Psychology and Research Designand Analysis as a senior lecturer at the University of Texas at Dallas. Her interests include modeling of cognitive processes using neural networks. She is a co-author of several research articles and a book about neural networks.Dominique Valentin is currently associate professor at the University of Bourgogne at Dijon, France. She has published a book and several papers dealing with neural networks and modeling.W. Jay Dowling is a professor in the School of Behavioral and Brain Sciences at the University of Texas at Dallas. His research interests have centred on the psychological reality and relevance to perception and memory of patterns of musical organization.

The structure of the book makes a lot of sense, and the chapters I have seen are well-written.

• 1 INTRODUCTION TO EXPERIMENTAL DESIGN; 2 CORRELATION; 3 STATISTICAL TEST: THE F TEST; 4 SIMPLE LINEAR REGRESSION; 5 ORTHOGONAL MULTIPLE REGRESSION; 6 NON-ORTHOGONAL MULTIPLE REGRESSION; 7 ANOVA ONE FACTOR: INTUITIVE APPROACH AND COMPUTATION OF F; 8 ANOVA, ONE FACTOR: TEST, COMPUTATION, AND EFFECT SIZE; 9 ANOVA, ONE FACTOR: REGRESSION POINT OF VIEW; 10 ANOVE, ONE FACTOR: SCORE MODEL; 11 ASSUMPTIONS OF ANALYSIS OF VARIANCE; 12 ANALYSIS OF VARIANCE, ONE FACTOR: PLANNED ORTHOGONAL COMPARISONS; 13 ANOVA, ONE FACTOR: PLANNED NON-ORTHOGONAL COMPARISONS; 14 ANOVA, ONE FACTOR: POST HOC OR A POSTERIORI ANALYSES; 15 MORE ON EXPERIMENTAL DESIGN: MULTI-FACTORIAL DESIGNS; 16 ANOVA, TWO FACTORS: AXB OR S(AXB); 17 FACTORIAL DESIGNS AND CONTRASTS; 18 ANOVA, ONE FACTOR REPEATED MEASURES DESIGN: SXA; 19 ANOVA, TTWO FACTORS COMPLETELY REPEATED MEASURES: SXAXB; 20 ANOVA TWO FACTOR PARTIALLY REPEATED MEASURES: S(A)XB; 21 ANOVA, NESTED FACTORIAL DESIGNS: SXA(B); 22 HOW TO DERIVE EXPECTED VALUES FOR ANY DESIGN; A DESCRIPTIVE STATISTICS; B THE SUM SIGN: E; C ELEMENTARY PROBABILITY: A REFRESHER; D PROBABILITY DISTRIBUTIONS; E THE BINOMIAL TEST; F EXPECTED VALUES; STATISTICAL TABLES