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Research Methods, Statistics, and Applications

Research Methods, Statistics, and Applications

Second Edition

February 2018 | 672 pages | SAGE Publications, Inc
One of the greatest strengths of this text is the consistent integration of research methods and statistics so that students can better understand how the research process requires the combination of these elements. The end goal is to spark students' interest in conducting research and to increase their ability to critically analyze it.

In the new second edition of the text, Katherine Adams and Eva Lawrence have integrated additional information on online data collection and research methods, additional coverage of regression and ANOVA, and new examples to engage students. 
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

Kathrynn Ann Adams

Kathrynn (Kathy) A. Adams earned her PhD in general experimental psychology from the University of Alabama in 1977. She was a Charles A. Dana Professor of Psychology at Guilford College when she retired in 2017 after 37 years of teaching. Her professional interests include gender issues, relationships, and teaching pedagogy. She worked with the Preparing Future Faculty Program for 20 years and helped establish the Early College at Guilford, a nationally ranked high school. In her spare time, she spends as much time as possible outdoors, practices yoga, and bakes chocolate desserts. More About Author

Eva K. McGuire

Eva K. McGuire earned her PhD in clinical psychology from Virginia Commonwealth University in 2002. She is a Charles A. Dana Professor of Psychology at Guilford College, where she has taught since 2003. Her research interests include environmental psychology and computer-mediated communication. Eva enjoys walking, yoga, and bike riding, and she loves to listen to live music. More About Author

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ISBN: 9781506350455