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

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September 2017 | 392 pages | SAGE Publications, Inc

This new introductory statistics text from Dawn M. McBride, best-selling author of The Process of Research in Psychologycovers 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.

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Your students save 20% when you bundle McBride’s core text with McBride and Cutting’s Lab Manual for Statistical Analysis. Use bundle ISBN 978-1-5443-0974-3.

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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

Supplements

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“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
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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Sample Materials & Chapters

Chapter 1: Why Statistics?

Chapter 8: Hypothesis-Testing Logic


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ISBN: 9781506325224