Research Methods in Psychology

Citation

Jhangiani, R. S., Chiang, I.-C. A., Cuttler, C., & Leighton, D. C. (2019). Research Methods in Psychology (4th ed.). Kwantlen Polytechnic University. Free official edition: https://kpu.pressbooks.pub/psychmethods4e/

Chapter Summary

Chapter 1: The Science of Psychology

The opening chapter asks how we know what we know, comparing intuition, authority, rationalism, empiricism and the scientific method. It defines science by three features (systematic empiricism, empirical questions and public knowledge), separates science from pseudoscience, and sets out the goals of describing, predicting and explaining behaviour, along with the distinction between basic and applied research. Sections on common-sense myths and folk psychology argue for scepticism and tolerance of uncertainty, and the chapter ends by distinguishing experimental from clinical psychologists and introducing empirically supported treatments.

Chapter 2: Overview of the Scientific Method

This chapter walks through the research cycle as a simple model: a question drawn from the literature leads to a study whose published results return to the literature. It covers finding a topic and searching the literature (with PsycINFO), turning ideas into empirically testable questions judged for interest and feasibility, and the relation between theories and hypotheses in the hypothetico-deductive method. It then previews the rest of the book: variables and operational definitions, populations and samples, experimental versus non-experimental and laboratory versus field research, descriptive and inferential statistics, Type I and Type II errors, and why scientists avoid the word "proof".

Chapter 3: Research Ethics

Ethics is framed as four moral principles (weighing risks against benefits, acting with integrity, seeking justice, respecting rights and dignity) applied to three groups: participants, science and society. The chapter traces the history of ethics codes from the Nuremberg Code through the Declaration of Helsinki and the Belmont Report to the US Federal Policy, explains Standard 8 of the APA Ethics Code (informed consent, deception, debriefing, animal research, scholarly integrity) and the role of institutional review boards, and closes with practical steps for designing an ethical study, including writing a consent form.

Chapter 4: Psychological Measurement

Measurement is defined as assigning scores that represent a characteristic, with self-report, behavioural and physiological measures as options. The chapter explains psychological constructs (using the Big Five as an example), conceptual and operational definitions, converging operations and the four levels of measurement. It then treats reliability (test–retest, internal consistency, inter-rater) and validity (face, content, criterion, discriminant), and gives a four-step practical procedure for choosing or creating a measure, implementing it and re-evaluating it with new data.

Chapter 5: Experimental Research

An experiment is defined by manipulating an independent variable, measuring a dependent variable and controlling extraneous variables, with confounds and placebo effects explained along the way. The chapter compares between-subjects designs (random assignment, matched groups) with within-subjects designs (carryover effects and counterbalancing), introduces the "four big validities" (internal, external, construct, statistical), and finishes with practical matters: recruiting participants, standardizing procedures, experimenter expectancy, manipulation checks and pilot testing.

Chapter 6: Non-Experimental Research

This chapter covers research without manipulation and when it is the appropriate choice. It describes cross-sectional, longitudinal and cross-sequential studies; correlational research and the interpretation of correlation coefficients, with the warning that correlation does not imply causation; complex correlational techniques (correlation matrices, factor analysis, partial correlation and multiple regression); qualitative research and the quantitative–qualitative debate; and observational methods, from naturalistic and participant observation to structured observation, case studies and archival research.

Chapter 7: Survey Research

Survey research is presented as self-report measurement on carefully chosen samples, rooted in social research, market research and polling. The chapter models answering a survey item as a cognitive process, shows how wording, order and response options create context effects, and gives item-writing guidance, including Likert scales and the BRUSO principles (brief, relevant, unambiguous, specific, objective). It ends with probability sampling methods, sampling and non-response bias, and the trade-offs of in-person, telephone, mail and online surveys.

Chapter 8: Quasi-Experimental Research

Quasi-experiments manipulate an independent variable without random assignment. The chapter describes three one-group designs (posttest only, pretest–posttest, interrupted time series) and five nonequivalent-groups designs, ending with switching-replication designs, which it ranks highest in internal validity. Threats such as history, maturation, testing, instrumentation, regression to the mean and spontaneous remission are explained through examples, including the question of whether psychotherapy works.

Chapter 9: Factorial Designs

Factorial designs combine two or more independent variables so that every level of one appears with every level of the others. The chapter shows how to set up and represent such designs (including non-manipulated variables such as gender, and non-experimental factorial studies), then how to graph results and interpret main effects, interactions of different types and simple effects. An exercise asks students to sketch all eight possible outcome patterns of a 2 × 2 design.

Chapter 10: Single-Subject Research

The chapter presents single-subject research as quantitative, experimental study of a few individuals in detail, associated mainly with behaviour analysis. It explains reversal designs and multiple-baseline designs (across participants, behaviours and settings), visual analysis of graphed data by level, trend and latency, and the disagreements between single-subject and group researchers over data analysis and external validity, concluding that the approaches are complementary and that converging evidence matters.

Chapter 11: Presenting Your Research

This chapter teaches APA style at three levels (organization, high-level style and low-level rules), with formats for references and citations. It explains each section of an empirical research report (title page and abstract, introduction with its opening, literature review and closing, method, results, discussion, references) and includes a sample APA-style report. It also covers review and theoretical articles, theses and student papers, and conference talks and posters.

Chapter 12: Descriptive Statistics

Students learn to describe distributions with frequency tables and histograms, central tendency (mean, median, mode) and variability (range, standard deviation), and to locate scores with percentile ranks and z scores. Group differences are expressed with Cohen's d and relationships with Pearson's r, each with conventional benchmarks for small, medium and large effects. Further sections show how to report results in APA-style text, figures and tables, and how to prepare data and separate planned from exploratory analyses.

Chapter 13: Inferential Statistics

The final chapter explains the logic of null hypothesis testing, the frequently misunderstood p value, and how relationship strength and sample size jointly determine significance, distinguishing statistical from practical significance. It works through one-sample, dependent-samples and independent-samples t-tests, one-way, repeated-measures and factorial ANOVA, and tests of Pearson's r, then covers Type I and II errors, statistical power and criticisms of null hypothesis testing. A closing section on the "replicability crisis" discusses the Reproducibility Project, questionable research practices such as p-hacking and HARKing, and open science responses such as preregistration, open data and the TOP guidelines.

Key Concepts

Chapter 1: The Science of Psychology

• Three features of science: systematic empiricism, empirical questions and public knowledge, which together distinguish science from pseudoscience.
• Goals of science: describing, predicting and explaining behaviour, pursued through basic or applied research.
• Empirically supported treatment: a clinical intervention shown to be effective through scientific research.

Chapter 2: Overview of the Scientific Method

• Research literature: published research, mainly in professional journals and scholarly books, searched through databases such as PsycINFO.
• Theory versus hypothesis: a theory explains a broad body of findings; a hypothesis is a specific, testable prediction derived from it.
• Type I and Type II errors: rejecting a true null hypothesis, or failing to reject a false one.

Chapter 3: Research Ethics

• Informed consent: obtaining and documenting agreement after telling people everything that might reasonably affect their decision to take part.
• Deception and debriefing: deception is permitted only under strict conditions, and participants must be told the truth as soon as possible.
• Institutional review board (IRB): the committee that reviews research protocols for conformity with ethical standards.

Chapter 4: Psychological Measurement

• Construct and operational definition: an unobservable variable such as self-esteem, made measurable by a specific procedure.
• Levels of measurement: nominal, ordinal, interval and ratio, which determine the statistics that can be used.
• Reliability and validity: consistency of scores, and the extent to which scores represent the intended variable.

Chapter 5: Experimental Research

• Confounding variable: an extraneous variable that varies systematically with the independent variable.
• Random assignment and counterbalancing: the techniques that stop extraneous variables becoming confounds in between- and within-subjects designs.
• Internal and external validity: support for a causal conclusion versus generalizability to other people and situations.

Chapter 6: Non-Experimental Research

• Correlation does not imply causation: a relationship between X and Y may reflect Y causing X or a third variable causing both.
• Partial correlation and multiple regression: statistical control of third variables in complex correlational designs.
• Qualitative research: broad questions, rich data such as interviews, and non-statistical analysis, often used to generate hypotheses.

Chapter 7: Survey Research

• Context effects: the influence of wording, item order and response options on answers.
• BRUSO: items should be brief, relevant, unambiguous, specific and objective.
• Non-response bias: distortion arising when non-respondents differ from respondents, reduced by maximizing response rates.

Chapter 8: Quasi-Experimental Research

• Quasi-experiment: manipulation of an independent variable without random assignment or counterbalancing.
• Nonequivalent groups: comparison groups that may differ before treatment.
• Switching replication: a design in which the treatment is later given to the comparison group, strengthening internal validity.

Chapter 9: Factorial Designs

• Factorial design: a study in which each level of one independent variable is combined with each level of the others.
• Main effect and interaction: the overall effect of one variable, versus an effect of one variable that depends on the level of another.
• Simple effects: the effect of one variable at each level of another, used to break down interactions.

Chapter 10: Single-Subject Research

• Reversal (ABA) design: baseline, treatment and return to baseline to show that changes follow the treatment.
• Multiple-baseline design: treatment introduced at different times across participants, behaviours or settings.
• Visual analysis: judging effects from graphs by changes in level, trend and latency.

Chapter 11: Presenting Your Research

• APA style: guidelines for writing in psychology, at the levels of organization, high-level style and low-level rules.
• Structure of an empirical report: abstract, introduction, method, results, discussion and references, with the literature review arguing for the study.

Chapter 12: Descriptive Statistics

• Central tendency and variability: mean, median and mode; range and standard deviation.
• z score: the distance of a score from the mean in standard-deviation units.
• Effect size: Cohen's d for differences between means and Pearson's r for relationships between quantitative variables.

Chapter 13: Inferential Statistics

• p value: the probability of a result at least as extreme as the sample result if the null hypothesis were true, not the probability that the null hypothesis is true.
• Statistical power: the probability of rejecting a false null hypothesis given the expected effect and sample size.
• Questionable research practices: selective reporting, HARKing, p-hacking and similar practices that inflate false findings.
• Open science: preregistration, open materials and open data to improve transparency and replicability.

Critical Analysis

Strengths

• Takes the replication crisis seriously. The preface promises not to present psychological "knowledge" as settled truth, and the book follows through: Chapter 1 introduces the Many Labs replication project, Chapter 3 opens with a recent fraud case, and Chapter 13 explains questionable research practices and open science reforms. Students meet methods in the context of current debates.
• Systematic pedagogy. Every section begins with learning objectives, and every chapter ends with key takeaways and exercises that mix practice tasks (for example designing a single-subject study or sketching the eight patterns of a 2 × 2 design) with discussion questions. A glossary and a list of instructor resources (slides, test banks, a student lab guide) support course use.
• Broad coverage of designs. Beyond experiments and correlations, the book gives full chapters to surveys, quasi-experiments, factorial designs and single-subject research, and it includes qualitative and observational methods, so students see the range of designs used in psychology.
• Practical research skills. Literature searching with PsycINFO, writing consent forms, building questionnaires, pilot testing and a full sample APA-style report prepare students to carry out and write up their own projects.

Limitations

• Statistics are introductory. The two statistics chapters cover descriptive measures, t-tests, ANOVA and tests of r conceptually and with worked examples, but not regression modelling, nonparametric tests, confidence-interval estimation in depth or Bayesian approaches; there is no software instruction.
• US-centred ethics and style. The ethics chapter is built around the APA Ethics Code, IRBs and US federal policy, and APA style rules may have changed since 2019; students in other countries need local guidance.
• Uneven depth. Qualitative research receives a single section within the non-experimental chapter, and some topics (for example factor analysis) are only sketched.
• Traces of adaptation. The text has passed through several editions and authors; the 2019 edition notes many moved sections and removed links, and some examples and web resources may still be dated.

Where It Fits in the Course

In a research methods and statistics course this is the methods-first introduction. The other listed books concentrate on statistics: Reidy and Dancey's Statistics without Maths for Psychology and Field's Discovering Statistics Using IBM SPSS Statistics are described as teaching statistical analysis, the latter with SPSS; Maxwell, Delaney and Kelley's Designing Experiments and Analyzing Data develops the analysis of experimental designs through model comparison; and McElreath's Statistical Rethinking teaches Bayesian modelling in R and Stan.

Jhangiani and colleagues should come first. Chapters 1–11 give the design, measurement and ethics background that the statistics books assume, and Chapters 12–13 provide a conceptual introduction to descriptive statistics and null hypothesis testing. Students can then move to Reidy and Dancey or Field for hands-on analysis, and later to Maxwell et al. or McElreath; the replicability material in Chapter 13 is a useful bridge to the critiques of p values that motivate those books.

How to Use This Book

The book is written for undergraduates taking their first research methods course in psychology. An introductory psychology course helps with examples, and only school-level algebra is needed for the statistics chapters.

For a one-semester methods course, read Chapters 1–5 in order, since measurement and experimental design underpin everything else, then select from Chapters 6–10 according to the designs the course emphasizes. Read Chapter 11 when writing a lab report, using the sample APA-style paper as a template, and Chapters 12–13 alongside or before a statistics module. Courses with a separate statistics course can treat Chapters 12–13 as review.

Use the learning objectives as a checklist before reading each section and the key takeaways for revision. Do at least the "Practice" exercises at the end of each chapter, and use the discussion exercises in study groups. The online edition embeds videos and links to tools (for example online power calculators); the back matter lists slide sets, test banks and a student lab guide that instructors can adopt.

Edition and Sources

This guide is based on the fourth edition of Research Methods in Psychology (2019, Kwantlen Polytechnic University; CC BY-NC-SA 4.0), read in the official free online Pressbooks edition at https://kpu.pressbooks.pub/psychmethods4e/. It draws on the acknowledgements, "About this Book" (edition history and fourth-edition changes), author biographies, preface, all 13 chapters (every section's learning objectives and headings, the opening of each section, and every chapter's key takeaways and exercises), the section on the replicability crisis and open science read in full, and the back-matter list of instructor resources.