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Using and Interpreting Statistics in the Social, Behavioral, and Health Sciences

Using and Interpreting Statistics in the Social, Behavioral, and Health Sciences

March 2018 | 232 pages | SAGE Publications, Inc

Using and Interpreting Statistics in the Social, Behavioral, and Health Sciences is designed to be paired with any undergraduate introduction to research methods text used by students in a variety of disciplines. It introduces students to statistics at the conceptual level—examining the meaning of statistics, and why researchers use a particular statistical technique, rather than computational skills. Focusing on descriptive statistics, and some more advanced topics such as tests of significance, measures of association, and regression analysis, this brief, inexpensive text is the perfect companion to help students who have not yet taken an introductory statistics course or are confused by the statistics used in the articles they are reading.

Chapter 1: Brief Introduction to Research in the Social, Behavioral, and Health Sciences
What Is the Purpose of Research?

How Is Research Done?

Scientific Method and Hypothesis Testing

Inductive Research

Deductive Research

Research Designs

Chapter 2: Variables and Measurement
Variables and Data

Levels of Variable Measurement

Types of Relationships

Research Design and Measurement Quality

Chapter 3: How to Sample and Collect Data for Analysis
Why Use a Sample?

Probability Sampling Methods

Nonprobability Sampling Methods

Validating a Sample

Split Ballot Designs

How and Where Are Data Collected Today?

Chapter 4: Data Frequencies and Distributions
Univariate Frequencies and Relative Frequencies

Cumulative Percentages and Percentiles

Frequencies for Quantitative Data

Univariate Distributions

The Normal Distribution

Non-Normal Distribution Characteristics

Data Transformations for Dealing With Non-Normal Distributions

Bivariate Frequencies

Chapter 5: Using and Interpreting Univariate and Bivariate Visualizations
Univariate Data Visualization

Bivariate Data Visualization

Chapter 6: Central Tendency and Variability
Understanding How to Calculate and Interpret Measures of Central Tendency

Understanding How Individuals in a Distribution Vary Around a Central Tendency

Chapter 7: What Are z Scores, and Why Are They Important?
What Is a z Score?

How to Calculate a z Score

The Standard Normal Table

Working With the Standard Normal Distribution to Calculate z Scores, Raw Scores, and Percentiles

Confidence Intervals

Chapter 8: Hypothesis Testing and Statistical Significance
Null and Alternative Hypotheses

Statistical Significance

Test Statistic Distributions

Choosing a Test of Statistical Significance

The Chi-Square Test of Independence

The Independent Samples t Test

One-Way Analysis of Variance

Chapter 9: How to Measure the Relationship Between Nominal and Ordinal Variables
Choosing the Correct Measure of Association

Trying to Reduce Error (PRE Statistics)

Calculating and Interpreting Lambda

Calculating and Interpreting Gamma

Calculating and Interpreting Somers’ d

Calculating and Interpreting Kendall’s Tau-b

Interpreting PRE Statistics Overview

Chapter 10: Effect Size
Effect Size

Choosing an Effect Size

Chapter 11: How to Interpret and Report Regression Results
What Is a Regression?


Bivariate Regression

Coefficient of Determination (r2)

Multiple Regression

Logistic Regression

Chapter 12: Indices, Typologies, and Scales
Indices, Typologies, and Scales Defined and Explained

Appendix A. The Standard Normal Table
Appendix B. Critical Values for t Statistic
Appendix C. Critical Values for Chi-Square
Appendix D. Critical Values for F Statistic
Appendix E. Glossary
About the Authors

This book is great to help students understand the statistics provided on the various articles they read. It introduces statistics with clear and simple explanations as well as plenty of practical examples. The quick learning checks are a good tool for them to self-assess whether they are understanding what they read and the terms box provides a useful list of what was introduced in each chapter. I highly recommend it for students.

Miss Cristiana Viana Cardoso
Division of Criminology, Birmingham City University
November 20, 2018

William E. Wagner III

William E. Wagner, III,  PhD, is Chair of the Department of Sociology at California State University, Dominguez Hills and Executive Director of the Social Science Research & Instructional Council of the CSU. He is co-author of Adventures in Social Research, 11th edition (SAGE, 2022), The Practice of Survey Research (SAGE, 2016), and A Guide to R for Social and Behavioral Sciences (SAGE, 2020) and author of Using IBM® SPSS® Statistics for Research Methods and Social Science Statistics, 7th edition (SAGE, 2019). More About Author

Brian Joseph Gillespie

Brian Joseph Gillespie, Ph.D. is a researcher in the Faculty of Spatial Sciences at the University of Groningen in the Netherlands. He is the author of Household Mobility in America: Patterns, Processes, and Outcomes (Palgrave, 2017) and coauthor of The Practice of Survey Research: Theory and Applications (Sage, 2016) and Using and Interpreting Statistics in the Social, Behavioral, and Health Sciences (Sage, 2018). He has also published research in a variety of social science journals on topics related to family, migration, the life course, and interpersonal relationships.  More About Author

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ISBN: 9781526402493

SAGE Research Methods is a research methods tool created to help researchers, faculty and students with their research projects. SAGE Research Methods links over 175,000 pages of SAGE’s renowned book, journal and reference content with truly advanced search and discovery tools. Researchers can explore methods concepts to help them design research projects, understand particular methods or identify a new method, conduct their research, and write up their findings. Since SAGE Research Methods focuses on methodology rather than disciplines, it can be used across the social sciences, health sciences, and more.