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The Process of Statistical Analysis in Psychology
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The Process of Statistical Analysis in Psychology

September 2017 | 392 pages | SAGE Publications, Inc
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This new introductory statistics text from Dawn M. McBride, best-selling author of The Process of Research in Psychology, covers the background and process of statistical analysis, along with how to use essential tools for working with data from the field. Research studies are included throughout from both the perspective of a student conducting their own research study and of someone encountering research in their daily life. McBride helps readers gain the knowledge they need to become better consumers of research and statistics used in everyday decision-making and connects the process of research design with the tools employed in statistical analysis. Instructors and students alike will appreciate the extra opportunities for practice with the accompanying Lab Manual for Statistical Analysis, also written by McBride and her frequent collaborator, J. Cooper Cutting.

Bundle the The Process of Statistical Analysis in Psychology with Lab Manual for Statistical Analysis for only $5 more! Bundle ISBN: 978-1-5443-0974-3

 
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

“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
Middle Tennessee State University

“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
Colby-Sawyer College

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

Michael Ray
The College at Brockport, State University of New York

Good student friendly book with good coverage of material

Mr Matthew Hope
Social Science, Newcastle College
April 22, 2019
Report this review
Key features

KEY FEATURES:

  • Statistics is approached as a step-by-step process to guide students through using statistics as a tool for understanding data.
  • A focus on conceptual understanding of inferential tests allows students to comprehend the concepts driving the tests, rather than just how to compute the statistics.
  • Scaffolding of concepts helps students understand concepts as they are introduced multiple
  • times throughout the course content.
  • Thinking About Research features provide a brief summary of a published research study with a focus on the data analysis and interpretation, along with critical thinking questions that help students understand how statistics are used in psychological research.
  • An accompanying lab manual by Dawn M. McBride and co-author J. Cooper Cutting provides students additional opportunities for practice to master the material.

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