Research Methods, Statistics, and Applications

4. Revised Auflage 2027
ISBN: 978-1-0719-2920-9
Verlag: Sage Publications Inc Ebooks

Buch, Englisch, 680 Seiten, Format (B × H): 187 mm x 231 mm, Gewicht: 343 g

Research Methods, Statistics, and Applications helps students actually understand how research works by integrating methods and statistics from the start, with a structure that makes it easier to teach and built-in practice that helps readers stay engaged.

Autoren/Hrsg.

Adams, Kathrynn A.

McGuire (aka: Lawrence), Eva Kung

Inhaltsverzeichnis

Preface
About the Authors
Chapter 1: Thinking Like a Researcher
Critical Thinking
The Scientific Approach
Overview of the Research Process (A.K.A. The Scientific Method
Thinking Critically About Ethics
The Big Picture: Scientific Progress, not Scientific Proof
Chapter Resources
Summary
Key Terms
Do You Understand the Chapter?
Student Research Topics
Chapter 2: Build a Solid Foundation For Your Study Based on Past Research
Types of Sources
Strategies to Identify and Find Past Research
Reading and Evaluating Primary Research Articles
Crediting Sources
The Big Picture: Use the Past to Inform the Present
Chapter Resources
Summary
Key Terms
Do You Understand the Chapter?
Chapter 3: Select Your Tools: How To Measure Your Variables
Constructs and Operational Definitions
Four Levels of Measurement
Self-Report Measures
Behavioral and Physiological Measures
Archival Research
The Big Picture: How to Choose Measures for Your Study
Chapter Resources
Summary
Key Terms
Do You Understand the Chapter?
Chapter 4: The Cornerstones of Good Research: Reliability and Validity
Reliability and Validity of Measurement
Evaluating the Reliability of Measures
Evaluating the Validity of Measures
Reliability and Validity of Results
The Big Picture: Reliability and Validity Considerations in Designing a Study
Chapter Resources
Summary
Key Terms
Do You Understand the Chapter?
Practice Dataset
Chapter 5: Basics of Research Design: Description and Sampling
Descriptive Designs
Validity in Descriptive Studies
Defining the Population and Obtaining A Sample
Random (or Probability) Sampling
Nonrandom (Nonprobability) Sampling
The Big Picture: Choosing a Sampling Method
Chapter Resources
Summary
Key Terms
Do You Understand the Chapter?
Chapter 6: Describing Your Sample
Ethical and Practical Issues in Describing Your Sample
Descriptive Statistics
Choosing the Appropriate Descriptive Statistics
Comparing Interval/Ratio Scores with z Scores and Percentiles
The Big Picture: Know Your Data and Your Sample
Chapter Resources
Summary
Key Terms
Do You Understand the Chapter?
Practice Dataset and Analyses
Chapter 7: Beyond Descriptives: Making Inferences Based on Your Sample
Inferential Statistics
Hypothesis Testing
Rejecting or Retaining the Null Hypothesis
Errors in Hypothesis Testing
Effect Size, Confidence Intervals, and Practical Significance
The Big Picture: Making Sense of Results
Chapter Resources
Summary
Key Terms
Do You Understand the Chapter?
Practice with Statistics
Chapter 8: Comparing Your Sample to a Known or Expected Score
Choosing the Appropriate Test
One-Sample t Tests
Null Hypothesis (H0)
Formulas and Calculations: One-Sample t Test
Calculating the Association Strength
Calculating a Confidence Interval
The Big Picture: Examining One Variable at a Time
Chapter Resources
Summary
Key Terms
Do You Understand the Chapter?
Practice With Statistics
Dataset
Chapter 9: Examining Relationships Among Your Variables: Correlational Design
Correlational Design
Designing Powerful, Meaningful, and Ethical Correlational Studies
Validity in Correlational Studies
Statistics to Evaluate Correlational Research
Formulas and Calculations
The Big Picture: Correlational Designs Versus Correlational Analyses
Chapter Resources
Summary
Key Terms
Do You Understand the Chapter?
Practice with Statistics
Chapter 10: Examining Causality: Experimental Design
Testing Cause and Effect
Threats to Internal Validity
Designing Powerful, Meaningful, and Ethical Experiments
Steps in Experimental Design
The Big Picture: Benefits and Limits of Experimental Design
Chapter Resources
Summary
Key Terms
Do You Understand the Chapter?
Chapter 11: Independent-Groups Designs
Designs with Two Independent Groups
Formulas and Calculations: Independent-Samples t Test
Using a Data Analysis Program to Calculate Independent Samples t Tests
Designs with More than Two Independent Groups
ETHICS TIP: Balance Inclusion with Adequate Representation
Formulas and Calculations: One-Way Between-Subjects ANOVA
Using a Data Analysis Program to Calculate One-Way Between-Subjects ANOVAS
The Big Picture: Identifying and Analyzing Independent-Groups Designs
Chapter Resources
Summary
Key Terms
Do You Understand the Chapter?
Practice with Statistics
Chapter 12: Dependent-Groups Designs
Designs With Two Dependent Groups
Formulas and Calculations: Dependent-Samples t Test
Using a Data Analysis Program to Calculate a Dependent-Samples t Test
Designs with More than Two Dependent Groups
Formulas and Calculations: One-Way Within-Subjects ANOVA
Using a Data Analysis Program to Calculate One-Way Within-Subjects ANOVAS
The Big Picture: Identifying and Analyzing Dependent-Groups Designs
Chapter Resources
Summary
Key Terms
Do You Understand the Chapter?
Practice With Design and Statistics
Chapter 13: Factorial Designs
Basic Concepts in Factorial Design
Rationale for Factorial Designs
2 × 2 Designs
Two-Way Between-Subjects ANOVA
Beyond the 2 × 2 Independent-Groups Design
The Big Picture: Embracing Complexity
Chapter Resources
Summary
Key Terms
Do You Understand the Chapter?
Practice with Statistics
Chapter 14: Nonparametric Statistics
Parametric Versus Nonparametric Statistics
Chi-Square Goodness of Fit
Chi-Square Test for Independence
Dependent-Groups Designs with Nominal Outcome Measures
Nonparametric Statistics for Ordinal Data
Spearman’s rho
The Big Picture: Selecting Parametric Versus Nonparametric Tests
Chapter Resources
Summary
Key Terms
Do You Understand the Chapter?
Practice with Statistics
Chapter 15: Focusing on The Individual: Case Studies and Single N Designs
Samples Versus Individuals
The Case Study
Qualitative Analyses
Single N Designs
The Big Picture: Choosing Between a Sample, Case Study, Or Single N Design
Chapter Resources
Summary
Key Terms
Do You Understand the Chapter?
Chapter 16: How to Decide?: Choosing a Research Design and Selecting the Correct Analysis
Choosing a Research Design
Selecting Your Statistical Analyses
The Big Picture: Beyond this Class
Chapter Resources
Summary
Do You Understand the Chapter?
Appendix A: Answers to Practice Questions
Appendix B: Apa Style and Format Guidelines
Appendix C: Statistical Tables
Appendix D: Statistical Formulas
Glossary
References
Index

Über Autor(innen)

Adams, Kathrynn A.
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.

McGuire (aka: Lawrence), Eva Kung
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.