Statistics for Psychology, 7th edition

  • Arthur Aron, 
  • Elaine N. Aron, 
  • Elliot J. Coups, 
  • Erin Cooley

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Statistics for Psychology emphasizes the logic behind statistics by placing definitional formulas center stage. For each procedure, the authors provide definitional formulas (in words) and computational formulas (in numbers and symbols). Emphasizing meaning and concepts rather than just symbols and numbers, this approach discourages rote memorization and helps you master the statistical analysis skills you need.

Joining longtime authors Arthur and Elaine Aron, new co-author and prolific researcher Erin Cooley brings a fresh perspective to the 7th Edition. Her contributions include new examples focusing on social inequality, her area of expertise. Updates to the text's content, examples and coverage of controversies ensure an up-to-date learning experience.

Published by Pearson (July 1st 2022) - Copyright © 2023

ISBN-13: 9780137994496

Subject: Research Methods & Statistics

Category: Statistics for Psychology


  1. Displaying the Order in a Group of Numbers Using Tables and Graphs
  2. Central Tendency and Variability
  3. Some Key Ingredients for Inferential Statistics
  4. Introduction to Hypothesis Testing
  5. Hypothesis Tests with Means of Samples
  6. Making Sense of Statistical Significance
  7. Introduction to t Tests
  8. The t Test for Independent Means
  9. Introduction to the Analysis of Variance
  10. Factorial Analysis of Variance
  11. Correlation
  12. Prediction
  13. Chi-Square Tests
  14. Strategies When Population Distributions Are Not Normal
  15. The General Linear Model and Making Sense of Advanced Statistical Procedures in Research Articles


  1. Tables
  2. Steps of Hypothesis Testing for Major Procedures
  3. Formulas
  4. Answers to Set 1 Practice Problems

WEB CHAPTERS (Downloadable at Student Resource Page)

  1. Overview of the Logic and Language of Psychology Research
  2. Applying Statistical Methods in Your Own Research Project
  3. Repeated Measures Analysis of Variance
  4. Integration and the General Linear Model

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