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The Process of Statistical Analysis in Psychology
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Table of Contents

Preface About the Author PART I: WHY DO WE USE STATISTICS? 1 Why Statistics? What Can Statistics Do for Me? Research Design and Statistics Chapter Summary Thinking About Research Test Yourself 2 The Starting Place: Data and Distributions Populations and Samples Types of Data Frequency Distributions Frequency Distributions in Excel Frequency Distributions in SPSS Summary of Frequency Distributions Chapter Summary Thinking About Research Test Yourself 3 Probability and Sampling Concepts of Probability Sampling Techniques Distribution of Sample Means Introduction Chapter Summary Thinking About Research Test Yourself PART II: DESCRIPTIVE STATISTICS 4 Central Tendency Central Tendency in Distributions Mean Median Mode Which Measure of Central Tendency Should I Use? Chapter Summary Thinking About Research Test Yourself 5 Variability Variability in Distributions Range and Interquartile Range Standard Deviation Which Measure of Variability Should I Use? Chapter Summary Thinking About Research Test Yourself 6 Presenting Descriptive Statistics Descriptive Statistics in Graphs Descriptive Statistics in Tables APA Style for Graphs and Tables Chapter Summary Thinking About Research Test Yourself PART III: BASICS OF HYPOTHESIS TESTING 7 The Normal Distribution and z Scores The z Score Transformation The Normal Distribution Chapter Summary Thinking About Research Test Yourself 8 Hypothesis-Testing Logic Using the Normal Distribution to Test Hypotheses Logic of Hypothesis Testing Types of Hypothesis-Testing Errors Statistical Significance Chapter Summary Thinking About Research Test Yourself PART IV: THE NUTS AND BOLTS OF STATISTICAL TESTS 9 The t Distribution The t Distribution One-Sample t Test Using SPSS to Conduct a One-Sample t Test Test Assumptions Chapter Summary Thinking About Research Test Yourself 10 Related/Paired Samples t Test Calculating a Related/Paired Samples t Test Using SPSS to Conduct a Related/Paired Samples t Test Test Assumptions Chapter Summary Thinking About Research Test Yourself 11 Independent Samples t Test Independent Samples Calculating the Independent Samples t Test Using SPSS to Conduct an Independent Samples t Test Test Assumptions Chapter Summary Thinking About Research Test Yourself 12 One-Way Analysis of Variance (ANOVA) More Than Two Independent Samples Calculating the F Score in an ANOVA Using SPSS to Conduct a One-Way Between-Subjects ANOVA Test Assumptions Chapter Summary Thinking About Research Test Yourself 13 Two-Way Analysis of Variance (ANOVA) Factorial Designs Calculating a Two-Way ANOVA Understanding Interactions Using SPSS to Calculate Two-Way Between-Subjects ANOVAs Test Assumptions Chapter Summary Thinking About Research Test Yourself 14 One-Way Within-Subjects Analysis of Variance (ANOVA) Within-Subjects Designs Calculating a Within-Subjects ANOVA Using SPSS to Calculate One-Way Within-Subjects ANOVAs Test Assumptions More Complex Within-Subjects Designs Chapter Summary Thinking About Research Test Yourself 15 Correlation Tests and Simple Linear Regression Correlation Versus Causation Hypothesis Testing With Pearson r Using SPSS to Conduct a Pearson r Test Regression Analyses Nonlinear Relationships Chapter Summary Thinking About Research Test Yourself 16 Chi-Square Tests Parametric Versus Nonparametric Tests Observed Versus Expected Frequencies Calculating a Chi-Square by Hand Calculating a Chi-Square Using SPSS Chapter Summary Thinking About Research Test Yourself Appendix A: Answers to Stop and Think Questions Appendix B: Unit Normal Table (z Table) Appendix C: t Distribution Table Appendix D: F Distribution Table Appendix E: Pearson r Critical Values Table Appendix F: Chi-Square Critical Values Table Glossary References Index

About the Author

Dawn M. McBride is a professor of psychology at Illinois State University. She earned her PhD in cognitive psychology from the University of California, Irvine, in 1999 and her BA from the University of California, Los Angeles in 1991. Her research interests include automatic forms of memory, false memory, prospective memory, and forgetting. She is the author or co-author of more than 30 peer-reviewed articles and book chapters and the author of three textbooks on cognition, research methods, and statistics. She teaches courses in introductory psychology, cognition and learning, human memory, research methods, statistics, and experimental design. She is a recipient of the Illinois State University Teaching Initiative Award and the Illinois State University SPA/Psi Chi Jim Johnson Award for commitment to undergraduate mentorship, involvement, and achievement.

Reviews

"This is a good text on introductory statistics that uses clear language and is easy for undergraduate students to read and understand. It goes through data analysis as it relates to research design and hypothesis testing step by step, which is a unique contribution of this book."

-- Paul S. Foster

"I really like the idea of an integrated stats/methods text that could also be used separately. The activities in the lab manual are nicely done and would provide additional practice for the students."

-- Courtney McManus

"A well thought-out statistics book that hits all the high points that students need without getting bogged down."

-- Michael Ray

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