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Statistics: A Tool for Social Research and Data Analysis, 6th Edition |

Joseph F. Healey, Christopher Donoghue, Steven Prus

Copyright 2027
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Statistics: A Tool for Social Research and Data Analysis 6th Edition by Joseph F. Healey/Christopher Donoghue/Steven Prus

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Overview
Meet the Authors
What's New
Features
Table of Contents
Pricing

Overview

Statistics: A Tool for Social Research and Data Analysis introduces students to statistical analysis for the social sciences (such as political science, social work, and criminology). The reader will acquire the ability to critically read professional social science literature while developing an appreciation of statistics from a uniquely Canadian perspective. This text is comprehensive, while remaining accessible and reader-friendly for students with varying levels of mathematical skill. The variety of special features within this product help students analyze data successfully while providing a solid grounding in traditional formulas and the use of the latest SPSS statistical software package. Upon completion of this text, social science majors will have developed the skills necessary to become statistically literate.

This edition is available in MindTap — an online learning platform that helps you stay organized and study effectively by providing all your course materials and study tools in one place. Along with additional course content, MindTap lets you highlight, take notes, create flashcards, and more.

Meet the Authors

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Joseph F. Healey

Joseph F. Healey is Professor Emeritus of Sociology at Christopher Newport University. In addition to STATISTICS: A TOOL FOR SOCIAL RESEARCH AND DATA ANALYSIS, he is the author of RACE, ETHNICITY, GENDER AND CLASS, 8th Edition (Sage, 2018 ) and DIVERSITY AND SOCIETY, 6th Edition (Sage, 2020 ) as well as co-author of several other texts. Dr. Healey earned his A.B. and M.A. from The College of William and Mary (sociology and anthropology) and his Ph.D. from the University of Virginia (sociology and anthropology). In his spare time, he plays and records music for the hammer dulcimer and banjo.

Christopher Donoghue

Christopher Donoghue is Associate Professor of Sociology at Montclair State University in New Jersey. He is the author of many articles on bullying, race and ethnicity, and nursing home care, with his work appearing in such journals as THE GERONTOLOGIST, SOCIOLOGICAL FORUM, RESEARCH ON AGING, JOURNAL OF ADOLESCENCE, THE SOCIAL SCIENCE JOURNAL, DISABILITY AND SOCIETY, HEALTHCARE MANAGEMENT REVIEW, CHILDREN AND SCHOOLS, SOCIOLOGICAL STUDIES OF CHILDREN AND YOUTH and SEX EDUCATION. Dr. Donoghue earned his B.A. from Seton Hall University, his M.A. from Montclair State University and his Ph.D. from Fordham University. Recently he helped to establish a new Master of Arts in Social Research and Analysis program at Montclair State.

Steven Prus

Steven Prus is an associate professor in the department of sociology and anthropology at Carleton University. His Ph.D. is from Simon Fraser University. Professor Prus received a post-doctoral fellowship in Health and Aging Studies at the McMaster University Centre for Gerontological Studies in Hamilton and Statistics Canada in Ottawa. His current interests lie in the area of health and aging using large-scale sample survey data. Professor Prus teaches medical sociology and social statistics at Carleton.

What's New

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Chapter 6 discussion and example on estimation techniques have been updated using recent 2025 federal election polling and estimation data.
Chi square (formerly Ch. 7) and measures of association for categorical data(formerly Ch. 8) have been combined into a new chapter (Chapter 7).
Material on hypothesis testing with gamma and spearman’s rho (Chapter 8) has been greatly expanded.
Chapter 12 on bivariate regression and correlation has been thoroughly updated.
Step-by-step, visual demonstration on how to use SPSS, along with SPSS dataset for the 2021 Census and 2019 General Social Survey.

Features

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Applying Statistics boxes illustrate specific ways in which statistics can be used to answer questions.
End-of-chapter problems are organized by discipline, so students can easily connect what they learn to their own academic interests.
Interpreting Statistics sections provide additional, detailed examples of how to express the meaning of statistics.
Step-by-step computational algorithms are provided for each statistic
Reading Statistics boxes show real examples from Canadian research and explain how statistics are reported and interpreted in professional literature.
Flow charts that help students select appropriate statistics are provided at the beginning of each chapter, depicting the selection process in detail.
Writing style is clear and easy to read while still introducing important statistical vocabulary in a way that feels approachable for students.
The Cengage Canada Teaching Advantage delivers research-based instructor resources that promote student engagement and higher-order thinking to enable the success of Canadian students and educators. With a focus on quality, all our resources are copyedited and questions are reviewed to ensure the content is accurate and relevant to the new edition.
MindTap is an online learning platform that helps students stay organized and study effectively by providing all of their course materials and study tools in one place. Along with additional course content, MindTap lets them highlight, take notes, create flashcards and more.

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Brief Contents
Preface

Prologue: Basic Mathematics Review

Chapter 1 Introduction

Part 1 Univariate Descriptive Statistics

Chapter 2 Basic Descriptive Statistics: Percentages, Ratios and Rates, Tables, Charts, and Graphs

Chapter 3 Measures of Central Tendency and Dispersion

Chapter 4 The Normal Curve and Probability

Part 2 From Description to Inference

Chapter 5 Introduction to Inferential Statistics: Sampling and the Sampling Distribution

Chapter 6 Estimation Procedures for Sample Means and Proportions

Part 3 Bivariate Relationships: Hypothesis Testing and Measuring Association

Chapter 7 Testing Significance and Association with Categorical Variables

Chapter 8 Testing Significance and Association with Ordinal Variables

Chapter 9 Hypothesis Testing with One Sample

Chapter 10 Hypothesis Testing with Two Samples

Chapter 11 Hypothesis Testing with More than Two Samples

Chapter 12 Regression and Correlation

Part 4 Multivariate Techniques

Chapter 13 Multiple Regression and Correlation

Appendix A Area Under the Normal Curve

Appendix B Distribution of t

Appendix C Distribution of Chi Square

Appendix D Distribution of F

Appendix E Using Statistics: Ideas for Research Projects

Answers to Odd-Numbered Computational Problems

Glossary

Index