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Research Methods, Statistics, and Applications

Research Methods, Statistics, and Applications

Second Edition

February 2018 | 672 pages | SAGE Publications, Inc
This updated Second Edition consistently integrates methods and statistics to prepare students for both graduate work and critical analysis of research as professionals and informed citizens. Maintaining the conversational writing style, multiple examples, and hands-on applications of key concepts that made the first edition so accessible, the authors enhance the new edition with additional coverage of online data collection, inferential statistics, and regression and ANOVA, as well as a wide range of diverse examples. 

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Research Methods, Statistics, and Applications, 2e + Student Study Guide With IBM® SPSS® Workbook – Bundle ISBN: 978-1-5443-3016-7

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About The Authors
Chapter 1: Thinking Like A Researcher
Critical Thinking

Thinking Critically About Ethics

The Scientific Approach

Overview of the Research Process (a.k.a. the Scientific Method)

The Big Picture: Proof and Progress in Science

Chapter 2: Build a Solid Foundation for Your Study Based On Past Research
Types of Sources

Types of Scholarly Works

Strategies to Identify and Find Past Research

Reading and Evaluating Primary Research Articles

Develop Study Ideas Based on Past Research

APA Format for References

The Big Picture: Use the Past to Inform the Present

Chapter 3: The Cornerstones of Good Research: Reliability and Validity
Using Data Analysis Programs: Measurement Reliability

Reliability and Validity Broadly Defined

Reliability and Validity of Measurement

Constructs and Operational Definitions

Types of Measures

Assessing Reliability of Measures

Assessing Validity of Measures

Reliability and Validity at the Study Level

The Big Picture: Consistency and Accuracy

Chapter 4: Basics of Research Design: Description, Measurement, and Sampling
When Is a Descriptive Study Appropriate?

Validity in Descriptive Studies

Measurement Methods

Defining the Population and Obtaining a Sample

The Big Picture: Beyond Description

Chapter 5: Describing Your Sample
Ethical Issues in Describing Your Sample

Practical Issues in Describing Your Sample

Descriptive Statistics

Choosing the Appropriate Descriptive Statistics

Using Data Analysis Programs: Descriptive Statistics

Comparing Interval/Ratio Scores with z Scores and Percentiles

The Big Picture: Know Your Data and Your Sample

Chapter 6: Beyond Descriptives: Making Inferences Based on Your Sample
Inferential Statistics

Hypothesis Testing

Errors in Hypothesis Testing

Effect Size, Confidence Intervals, and Practical Significance

Determining the Effect Size, Confidence Interval, and Practical Significance in a Study

The Big Picture: Making Sense of Results

Chapter 7: Comparing Your Sample to a Known or Expected Score
Choosing the Appropriate Test

One-Sample t Tests

Formulas and Calculations: One-Sample t Test

Using Data Analysis Programs: One-Sample t Test



The Big Picture: Examining One Variable at a Time

Chapter 8: Examining Relationships among Your Variables: Correlational Design
Correlational Design

Basic Statistics to Evaluate Correlational Research

Using Data Analysis Programs: Pearson's r and Point-Biserial r


Formulas and Calculations: Simple Linear Regression

Using Data Analysis Programs: Regression

The Big Picture: Correlational Designs Versus Correlational Analyses

Chapter 9: Examining Causality
Testing Cause and Effect

Threats to Internal Validity

Basic Issues in Designing an Experiment

Other Threats to Internal Validity

Balancing Internal and External Validity

The Big Picture: Benefits and Limits of Experimental Design

Chapter 10: Independent-Groups Designs
Designs with Independent Groups

Designing a Simple Experiment

Independent-Samples t Tests

Formulas and calculations: independent-samples t test

Using data analysis programs: independent-samples t test

Designs With More Than Two Independent Groups

Formulas and calculations: one-way independent-samples anova

Using data analysis programs: one-way independent-samples anova

The big picture: identifying and analyzing independent-groups designs

Chapter 11: Dependent-Groups Designs
Designs with dependent groups

Formulas and Calculations: Dependent-Samples t Test

Using data analysis programs: dependent-samples t test

Designs with more than two dependent groups

Formulas and calculations: within-subjects ANOVA

Using data analysis programs: within-subjects ANOVA

The big picture: selecting analyses and interpreting results for dependent-groups designs

Chapter 12: Factorial Designs
Basic Concepts in Factorial Design

Rationale for Factorial Designs

2 x 2 Designs

Analyzing Factorial Designs

Analyzing Independent-Groups Factorial Designs

Formulas and Calculations: Two-Way Between-Subjects ANOVA

Using Data Analysis Programs: Two-Way Between-Subjects ANOVA

Reporting and Interpreting Results of a Two-Way ANOVA

Dependent-Groups Factorial Designs

Mixed Designs

The Big Picture: Embracing Complexity

Chapter 13: Nonparametric Statistics
Parametric Versus Nonparametric Statistics

Nonparametric Tests for Nominal Data

Formulas and Calculations: Chi-Square Goodness of Fit

Using Data Analysis Programs: Chi-Square Goodness of Fit

Formulas and calculations: chi-square test for independence

Using data analysis programs: chi-square test for independence

Nonparametric statistics for ordinal (ranked) data

Formulas and calculations: spearman’s rho

Using data analysis programs: spearman’s rho

The big picture: selecting parametric versus nonparametric tests

Chapter 14: Focusing on the Individual Case Studies and Single N Designs
Samples Versus Individuals

The Case Study

Single N Designs

The Big Picture: Choosing Between a Sample, Case Study, or Single N Design

Chapter 15: How to Decide? Choosing a Research Design and Selecting the Correct Analysis
First and Throughout: Base Your Study on Past Research

Choosing a Research Design

Selecting Your Statistical Analyses

The Big Picture: Beyond This Class

Appendix A: Answers to Practice Questions
Appendix B: APA Style and Format Guidelines
Appendix C: Statistical Tables
Appendix D: Statistical Formulas
Author index
Subject index


Student Study Site

SAGE edge for Students provides a personalized approach to help students accomplish their coursework goals in an easy-to-use learning environment.

  • Mobile-friendly eFlashcards strengthen understanding of key terms and concepts.
  • Mobile-friendly practice quizzes allow for independent assessment by students of their mastery of course material.
  • Multimedia content includes videos that appeal to students with different learning styles plus links to relevant websites for additional resources for further research on important topics.
  • EXCLUSIVE! Access to full-text SAGE journal articles that have been carefully selected to support and expand on the concepts presented in each chapter is included.
  • Datasets for accompanying material in the book are available for download.
Instructor Teaching Site

SAGE edge for Instructors supports your teaching by making it easy to integrate quality content and create a rich learning environment for students.

  • Test banks provide a diverse range of pre-written options as well as the opportunity to edit any question and/or insert your own personalized questions to effectively assess students’ progress and understanding.
  • Sample course syllabi for semester and quarter courses provide suggested models for structuring your courses.
  • A robust Instructor’s Manual contains a wealth of resources for instructors to draw on for each chapter, including lesson plans, class activities, and homework assignments designed by the authors.
  • Editable, chapter-specific PowerPoint® slides offer complete flexibility for creating a multimedia presentation for your course.
  • EXCLUSIVE! Access to full-text SAGE journal articles that have been carefully selected by the authors to support and expand on the concepts presented in each chapter, including accompanying exercises.
  • Multimedia content includes videos that appeal to students with different learning styles plus links to relevant websites for additional resources for further research on important topics.
  • Data sets for accompanying material in the book are available for download.
  • Solutions to the end-of-chapter exercises help assess student understanding of the material.

"The authors have constructed a manuscript that utilizes real life research questions and takes the reader through a detailed process of how a researcher would construct a study to answer the question, select the appropriate statistics to answer the question, and disseminate the results in how to write up the results/discussion."

Charles Fountaine
University of Minnesota, Duluth

"It outlines the bare necessities of research. It’s not full of definitions, it more so teaches students about the application of materials. The book comes across as task-oriented."

Derrick Bryan
Morehouse College

"In our sections of research methods & statistics, students are asked to buy two books (methods + stats). I appreciate that this textbook is able to unite the two domains in such a clear way. This book really stands out as a detailed "field manual" for psychological research, and it's the kind of book that students might be more likely to hang on to for future reference. The integration of SPSS & APA style conventions throughout was nice to see. Also nice to see effect sizes and power analysis show up so students don't have a simple view of null hypothesis statistical tests."

Ben Denkinger
Augsburg College

"I like the combination of the methods and stats. I believe that this book would be beneficial for an advanced research methods/stats class at the undergraduate level. I like that the book provides adequate coverage to case studies and single case research design."

Erin Fekete
University of Indianapolis

"Some good thorough discussion of aspects of each kind of research and statistical approach. Workbook pretty thorough."

Kevin E. Lawson
Talbot School of Theology, Biola University

"The simplicity and relevance of the supplemental materials built in to illustrate the concepts are the key strengths of this text."

Malaika Brown
Citrus College

Covered the subject better than others.

Professor James Bishop
Management Dept, New Mexico State University-Las Cruces
October 1, 2019

Rigor is at the correct level for our educational researches; good examples for APA write-up; easy to understand explanations for statistical concepts

Dr Benny Hoiwah Fong
Graduate School of Education, Southwest Baptist University
March 5, 2020

Easy to read for students

Dr Olu Awosoga
Health Sciences Dept, University Of Lethbridge
December 31, 2019

I can say that this is one of the best textbooks in the market.

Dr Durmus Alper Camlibel
Criminal Justice Dept, Northern Michigan University
June 14, 2019
Key features


  • New, diverse examples from current research literature in criminal justice, politics, education, and counseling expose students to examples of different research designs in the social sciences and demonstrate commonalities. 
  • New chapter-ending The Big Picture sections with appropriate charts and tables encourage students to consider decisions about specific statistical analyses.
  • Two separate chapters (Inferential Statistics and Comparing your Sample to a Known or Expected Score) now allow instructors to focus on the theoretical concepts associated with inferential statistics before introducing each specific inferential statistic to enhance student understanding.
  • Expanded coverage of inferential statistics includes more discussion of APA guidelines for appropriate statistics and more focus on effect sizes and confidence intervals.
  • New consistent headings make it easy for students to quickly locate information and for instructors to identify sections they may wish to focus on, skip, or present in a different order.
  • An updated, user-friendly SAGE edge companion website provides videos, web resources, and practice datasets, as well flashcards and web quizzes for students, and in-class activities, lecture slides, homework assignments, answers to statistics exercises, and test banks for instructors.


  • Thorough integration of research methods and statistics helps students gain a full picture of the research process.
  • Examples from current research literature provide a real-life context for understanding methods and statistics and demonstrate how a research topic can be examined in multiple ways.
  • Directions for calculating statistics using formulas, as well as data analysis programs (specifically SPSS), enhance student understanding of analyses.
  • Ethics are discussed throughout the book— with tips for how to conduct ethical research in every chapter— to reinforce its importance in all stages of the research process.
  • Practice boxes in every chapter and end-of-chapter Review of Key Concepts provide repeated exposure to important ideas, as well as opportunities to apply concepts soon after learning about them.
  • A final “putting it all together” chapter provides a summary of the major questions to answer when designing and carrying out research.
  • A focus on academic honesty is woven throughout the book and reinforced in an APA-style research paper and published manuscript in the appendix. 

For instructors

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