Experimental design and analysis for psychology

著者

書誌事項

Experimental design and analysis for psychology

Hervé Abdi ... [et al.]

Oxford University Press, 2009

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注記

Includes bibliographical references (p. [518]-530) and index

内容説明・目次

内容説明

Careful data collection and analysis lies at the heart of good research, through which our understanding of psychology is enhanced. Yet the students who will become the next generation of researchers need more exposure to statistics and experimental design than a typical introductory course presents. Experimental Design and Analysis for Psychology provides a complete course in data collection and analysis for students who need to go beyond the basics. Acting as a true course companion, the text's engaging writing style leads readers through a range of often challenging topics, blending examples and exercises with careful explanations and custom-drawn figures to ensure even the most daunting concepts can be fully understood. Opening with a review of key concepts, including probability, correlation, and regression, the book goes on to explore the analysis of variance and factorial designs, before moving on to consider a range of more specialised, but yet powerful, statistical tools, including the General Linear Model, and the concept of unbalanced designs. Not just a printed book, Experimental Design and Analysis for Psychology is enhanced by a range of online materials, all of which add to its value as an ideal teaching and learning resource. The Online Resource Centre features: For registered adopters: Figures from the book, available to download. Answers to exercises featured in the book. Online-only Part III: bonus chapters featuring more advanced material, to extend the coverage of the printed book. For students: A downloadable workbook, featuring exercises for self-study. SAS, SPSS and R companions, featuring program code and output for all major examples in the book tailored to these three software packages.

目次

  • 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

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