Research Methods in Psychology: Evaluating a World of Information

Citation

Morling, B. (2025). Research Methods in Psychology: Evaluating a World of Information (5th ed.). W. W. Norton & Company.

Chapter Summary

The fifth edition has fourteen chapters in six parts, followed by three supplemental chapters on statistics and presenting results. Norton describes the book as teaching students to evaluate research as consumers of information while learning to produce research themselves. The listing below follows the publisher's contents and its notes on what is new in this edition; it shows chapter titles and a few topics, not the full text of each chapter.

Part 1, Chapters 1–3: Introduction to Scientific Reasoning

Chapter 1 is "Psychology Is a Way of Thinking". Norton notes that the fifth edition adds coverage of the historical lack of diversity in psychological research and the advantages of a more diverse range of participants, as well as an introduction to qualitative methods and their role. Chapter 2 is "Sources of Information: Why Research Is Best and How to Find It". Chapter 3, "Three Claims, Four Validities: Interrogation Tools for Consumers of Research", presents the framework that gives the book its structure and is announced in the book's description.

Part 2, Chapters 4–5: Research Foundations for Any Claim

Chapter 4, "Ethical Guidelines for Psychology Research", has entirely revised coverage of animal research in this edition. Chapter 5, "Identifying Good Measurement", addresses the quality of measures that every later design depends on.

Part 3, Chapters 6–7: Tools for Evaluating Frequency Claims

Chapter 6, "Surveys and Observations: Describing What People Do", adds new sections introducing qualitative methods. Chapter 7, "Sampling: Estimating the Frequency of Behaviors and Beliefs", turns to how samples support claims about how common a behaviour or belief is.

Part 4, Chapters 8–9: Tools for Evaluating Association Claims

Chapter 8 is "Bivariate Correlational Research" and Chapter 9 is "Multivariate Correlational Research".

Part 5, Chapters 10–12: Tools for Evaluating Causal Claims

Chapter 10, "Introduction to Simple Experiments", is followed by Chapter 11, "More on Experiments: Confounding and Obscuring Variables", and Chapter 12, "Experiments with More Than One Independent Variable". Norton says that the fifth edition's new examples by BIPOC researchers include studies by Okonofua and colleagues covered extensively in Chapter 12.

Part 6, Chapters 13–14: Balancing Research Priorities

Chapter 13 is "Quasi-Experiments and Small-N Designs". Chapter 14, "Replication, Credibility, and Wider Importance", adds a new section on diversity in psychological samples and in psychological scientists.

Supplemental Chapters S1–S3

S1 is "Descriptive Statistics". S2, "Inferential Statistics", has a revised treatment covering the "new statistics" (confidence intervals and effect size) alongside null-hypothesis significance testing. S3, "Presenting Results", adds coverage of generative AI, including effective and ethical use and citation guidelines.

Key Concepts

Parts 1–3

• Three claims, four validities: the book's framework for questioning research, introduced in Chapter 3.
• Research ethics: the guidelines treated in Chapter 4, including animal research.
• Measurement quality: what makes a measure good, the topic of Chapter 5.
• Frequency claims: surveys, observations and sampling.

Parts 4–6 and supplements

• Association claims: bivariate and multivariate correlational research.
• Causal claims: simple experiments, confounds and obscuring variables, and factorial designs.
• Quasi-experiments and small-N designs: alternatives to the standard experiment.
• Replication and credibility: the focus of Chapter 14.
• Effect size and confidence intervals: the "new statistics" in S2.

Critical Analysis

Strengths

• A claim-based organisation. The book is arranged by the kind of claim being made: frequency, association and causal claims each get their own part, which ties methods to the question a reader actually meets in news and journals.
• Ethics, measurement and credibility are structural. Ethics and measurement sit in Part 2 before any design, and the book closes with a chapter on replication, credibility and wider importance rather than treating them as afterthoughts.
• Statistics as supplements. Statistics are placed in separate chapters (S1–S2), so instructors can fit them to a separate statistics course, and the fifth edition updates S2 to include the new statistics alongside significance testing.
• Kept current. The publisher lists a revised treatment of animal research, qualitative methods, diversity in samples and in researchers, and generative AI.

Limitations

• Qualitative methods have limited space. The publisher presents them as new sections within Chapters 1 and 6 rather than as a chapter of their own, while the parts on frequency, association and causal claims are built around quantitative designs.
• Statistics are covered briefly. Three supplemental chapters cannot replace a statistics textbook; students who will analyse their own data need a dedicated text.

Where It Fits in the Course

Morling is an undergraduate research-methods text aimed at students new to the subject. Jhangiani, Chiang, Cuttler and Leighton's Research Methods in Psychology is a free, openly licensed alternative that also runs from scientific thinking through measurement and designs to statistics and writing in APA style, and is a good choice where cost matters or for supplementary reading.

For statistics, Reidy and Dancey's Statistics without Maths for Psychology explains the logic of analysis in words and graphs, and Field's Discovering Statistics Using IBM SPSS Statistics teaches analysis together with SPSS. For advanced work, Maxwell, Delaney and Kelley's Designing Experiments and Analyzing Data is a graduate text on model comparison, and McElreath's Statistical Rethinking is a Bayesian course for researchers. Morling's book is a sensible first read, since it explains what kinds of claims research can support before those tools are needed.

How to Use This Book

A first course in psychology helps, and no statistics background is needed to start. It suits undergraduates in a methods course, and any student who needs to read psychological research critically.

A practical plan: read Parts 1 and 2 (Chapters 1–5) first, because Chapter 3's framework is used throughout; then follow the claims sequence of Parts 3–5 with a journal article in hand for each type of claim. Read S1 and S2 when the course reaches statistics, then Chapter 13 and 14 for designs beyond the simple experiment and for questions of replication. When writing a report, use S3 and the ethics chapter. Pair the book with a statistics text if the course includes data analysis.