Research methods revision notes

Research methods

Specification context

Research methods appears in AQA A-level Psychology 7182.

Topic overview

Students demonstrate knowledge and understanding of research methods, scientific processes, data handling and inferential testing. Revise this area by separating AO1 knowledge, AO2 application and AO3 evaluation. Psychology answers need accurate terminology, relevant evidence and clear judgement, not just a list of named studies.

Learning objectives

• Explain the experimental method, including laboratory, field, natural and quasi-experiments.
• Explain observational techniques, including naturalistic, controlled, covert, overt, participant and non-participant observation.
• Explain self-report techniques, including questionnaires and structured or unstructured interviews.
• Explain correlations and distinguish correlations from experiments.
• Explain content analysis and case studies as research methods.
• Distinguish aims from hypotheses and directional from non-directional hypotheses.
• Explain sampling methods, including random, systematic, stratified, opportunity and volunteer sampling, and their implications for bias and generalisation.
• Explain experimental design, observational design, questionnaire construction, interview design, pilot studies, control, standardisation, ethical issues, reliability and validity.
• Explain features of science, including objectivity, replication, theory construction, hypothesis testing, peer review and the implications of psychological research for the economy.
• Distinguish quantitative and qualitative data and their collection techniques.
• Distinguish primary data from secondary data, including meta-analysis.
• Calculate and interpret measures of central tendency, including mean, median and mode.
• Calculate and interpret measures of dispersion, including range and standard deviation.
• Calculate percentages and interpret positive, negative and zero correlations.
• Present quantitative data using graphs, tables, scattergrams, bar charts and histograms.
• Explain normal and skewed distributions.
• Analyse and interpret correlations, including correlation coefficients.
• Distinguish nominal, ordinal and interval levels of measurement.
• Explain coding in content analysis.
• Explain the purpose of statistical testing.
• Explain when to use the sign test and how to calculate it.
• Use probability, statistical tables and critical values to interpret significance.
• Distinguish Type I errors from Type II errors.
• Explain how level of measurement affects the choice of statistical test.
• Explain how experimental design affects the choice of statistical test.
• Identify when to use Spearman's rho, Pearson's r, Wilcoxon, Mann-Whitney, related t-test, unrelated t-test and Chi-Squared test.

Objective-by-objective revision

Scientific processes: Explain the experimental method, including laboratory, field, natural and quasi-experiments.

Start with AO1: define the psychological concept, theory, study, method, treatment or data issue named in this objective. Use precise Psychology terminology and keep the wording tied to Scientific processes. Then build AO2 or AO3 where relevant. AO2 applies the idea to a scenario, practical context, qualitative data or quantitative data. AO3 analyses, interprets or evaluates by explaining why evidence, validity, reliability, bias, ethics, generalisability or methodology affects the conclusion. A strong answer avoids unsupported opinion and study-name dumping. It links claim, evidence, method and implication so the evaluation explains why the point matters.

Scientific processes: Explain observational techniques, including naturalistic, controlled, covert, overt, participant and non-participant observation.

Start with AO1: define the psychological concept, theory, study, method, treatment or data issue named in this objective. Use precise Psychology terminology and keep the wording tied to Scientific processes. Then build AO2 or AO3 where relevant. AO2 applies the idea to a scenario, practical context, qualitative data or quantitative data. AO3 analyses, interprets or evaluates by explaining why evidence, validity, reliability, bias, ethics, generalisability or methodology affects the conclusion. A strong answer avoids unsupported opinion and study-name dumping. It links claim, evidence, method and implication so the evaluation explains why the point matters.

Scientific processes: Explain self-report techniques, including questionnaires and structured or unstructured interviews.

Start with AO1: define the psychological concept, theory, study, method, treatment or data issue named in this objective. Use precise Psychology terminology and keep the wording tied to Scientific processes. Then build AO2 or AO3 where relevant. AO2 applies the idea to a scenario, practical context, qualitative data or quantitative data. AO3 analyses, interprets or evaluates by explaining why evidence, validity, reliability, bias, ethics, generalisability or methodology affects the conclusion. A strong answer avoids unsupported opinion and study-name dumping. It links claim, evidence, method and implication so the evaluation explains why the point matters.

Scientific processes: Explain correlations and distinguish correlations from experiments.

Start with AO1: define the psychological concept, theory, study, method, treatment or data issue named in this objective. Use precise Psychology terminology and keep the wording tied to Scientific processes. Then build AO2 or AO3 where relevant. AO2 applies the idea to a scenario, practical context, qualitative data or quantitative data. AO3 analyses, interprets or evaluates by explaining why evidence, validity, reliability, bias, ethics, generalisability or methodology affects the conclusion. A strong answer avoids unsupported opinion and study-name dumping. It links claim, evidence, method and implication so the evaluation explains why the point matters.

Scientific processes: Explain content analysis and case studies as research methods.

Start with AO1: define the psychological concept, theory, study, method, treatment or data issue named in this objective. Use precise Psychology terminology and keep the wording tied to Scientific processes. Then build AO2 or AO3 where relevant. AO2 applies the idea to a scenario, practical context, qualitative data or quantitative data. AO3 analyses, interprets or evaluates by explaining why evidence, validity, reliability, bias, ethics, generalisability or methodology affects the conclusion. A strong answer avoids unsupported opinion and study-name dumping. It links claim, evidence, method and implication so the evaluation explains why the point matters.

Scientific processes: Distinguish aims from hypotheses and directional from non-directional hypotheses.

Start with AO1: define the psychological concept, theory, study, method, treatment or data issue named in this objective. Use precise Psychology terminology and keep the wording tied to Scientific processes. Then build AO2 or AO3 where relevant. AO2 applies the idea to a scenario, practical context, qualitative data or quantitative data. AO3 analyses, interprets or evaluates by explaining why evidence, validity, reliability, bias, ethics, generalisability or methodology affects the conclusion. A strong answer avoids unsupported opinion and study-name dumping. It links claim, evidence, method and implication so the evaluation explains why the point matters.

Scientific processes: Explain sampling methods, including random, systematic, stratified, opportunity and volunteer sampling, and their implications for bias and generalisation.

Start with AO1: define the psychological concept, theory, study, method, treatment or data issue named in this objective. Use precise Psychology terminology and keep the wording tied to Scientific processes. Then build AO2 or AO3 where relevant. AO2 applies the idea to a scenario, practical context, qualitative data or quantitative data. AO3 analyses, interprets or evaluates by explaining why evidence, validity, reliability, bias, ethics, generalisability or methodology affects the conclusion. A strong answer avoids unsupported opinion and study-name dumping. It links claim, evidence, method and implication so the evaluation explains why the point matters.

Scientific processes: Explain experimental design, observational design, questionnaire construction, interview design, pilot studies, control, standardisation, ethical issues, reliability and validity.

Start with AO1: define the psychological concept, theory, study, method, treatment or data issue named in this objective. Use precise Psychology terminology and keep the wording tied to Scientific processes. Then build AO2 or AO3 where relevant. AO2 applies the idea to a scenario, practical context, qualitative data or quantitative data. AO3 analyses, interprets or evaluates by explaining why evidence, validity, reliability, bias, ethics, generalisability or methodology affects the conclusion. A strong answer avoids unsupported opinion and study-name dumping. It links claim, evidence, method and implication so the evaluation explains why the point matters.

Scientific processes: Explain features of science, including objectivity, replication, theory construction, hypothesis testing, peer review and the implications of psychological research for the economy.

Start with AO1: define the psychological concept, theory, study, method, treatment or data issue named in this objective. Use precise Psychology terminology and keep the wording tied to Scientific processes. Then build AO2 or AO3 where relevant. AO2 applies the idea to a scenario, practical context, qualitative data or quantitative data. AO3 analyses, interprets or evaluates by explaining why evidence, validity, reliability, bias, ethics, generalisability or methodology affects the conclusion. A strong answer avoids unsupported opinion and study-name dumping. It links claim, evidence, method and implication so the evaluation explains why the point matters.

Data handling and analysis: Distinguish quantitative and qualitative data and their collection techniques.

Start with AO1: define the psychological concept, theory, study, method, treatment or data issue named in this objective. Use precise Psychology terminology and keep the wording tied to Data handling and analysis. Then build AO2 or AO3 where relevant. AO2 applies the idea to a scenario, practical context, qualitative data or quantitative data. AO3 analyses, interprets or evaluates by explaining why evidence, validity, reliability, bias, ethics, generalisability or methodology affects the conclusion. A strong answer avoids unsupported opinion and study-name dumping. It links claim, evidence, method and implication so the evaluation explains why the point matters.

Data handling and analysis: Distinguish primary data from secondary data, including meta-analysis.

Start with AO1: define the psychological concept, theory, study, method, treatment or data issue named in this objective. Use precise Psychology terminology and keep the wording tied to Data handling and analysis. Then build AO2 or AO3 where relevant. AO2 applies the idea to a scenario, practical context, qualitative data or quantitative data. AO3 analyses, interprets or evaluates by explaining why evidence, validity, reliability, bias, ethics, generalisability or methodology affects the conclusion. A strong answer avoids unsupported opinion and study-name dumping. It links claim, evidence, method and implication so the evaluation explains why the point matters.

Data handling and analysis: Calculate and interpret measures of central tendency, including mean, median and mode.

Start with AO1: define the psychological concept, theory, study, method, treatment or data issue named in this objective. Use precise Psychology terminology and keep the wording tied to Data handling and analysis. Then build AO2 or AO3 where relevant. AO2 applies the idea to a scenario, practical context, qualitative data or quantitative data. AO3 analyses, interprets or evaluates by explaining why evidence, validity, reliability, bias, ethics, generalisability or methodology affects the conclusion. A strong answer avoids unsupported opinion and study-name dumping. It links claim, evidence, method and implication so the evaluation explains why the point matters.

Data handling and analysis: Calculate and interpret measures of dispersion, including range and standard deviation.

Start with AO1: define the psychological concept, theory, study, method, treatment or data issue named in this objective. Use precise Psychology terminology and keep the wording tied to Data handling and analysis. Then build AO2 or AO3 where relevant. AO2 applies the idea to a scenario, practical context, qualitative data or quantitative data. AO3 analyses, interprets or evaluates by explaining why evidence, validity, reliability, bias, ethics, generalisability or methodology affects the conclusion. A strong answer avoids unsupported opinion and study-name dumping. It links claim, evidence, method and implication so the evaluation explains why the point matters.

Data handling and analysis: Calculate percentages and interpret positive, negative and zero correlations.

Start with AO1: define the psychological concept, theory, study, method, treatment or data issue named in this objective. Use precise Psychology terminology and keep the wording tied to Data handling and analysis. Then build AO2 or AO3 where relevant. AO2 applies the idea to a scenario, practical context, qualitative data or quantitative data. AO3 analyses, interprets or evaluates by explaining why evidence, validity, reliability, bias, ethics, generalisability or methodology affects the conclusion. A strong answer avoids unsupported opinion and study-name dumping. It links claim, evidence, method and implication so the evaluation explains why the point matters.

Data handling and analysis: Present quantitative data using graphs, tables, scattergrams, bar charts and histograms.

Start with AO1: define the psychological concept, theory, study, method, treatment or data issue named in this objective. Use precise Psychology terminology and keep the wording tied to Data handling and analysis. Then build AO2 or AO3 where relevant. AO2 applies the idea to a scenario, practical context, qualitative data or quantitative data. AO3 analyses, interprets or evaluates by explaining why evidence, validity, reliability, bias, ethics, generalisability or methodology affects the conclusion. A strong answer avoids unsupported opinion and study-name dumping. It links claim, evidence, method and implication so the evaluation explains why the point matters.

Data handling and analysis: Explain normal and skewed distributions.

Start with AO1: define the psychological concept, theory, study, method, treatment or data issue named in this objective. Use precise Psychology terminology and keep the wording tied to Data handling and analysis. Then build AO2 or AO3 where relevant. AO2 applies the idea to a scenario, practical context, qualitative data or quantitative data. AO3 analyses, interprets or evaluates by explaining why evidence, validity, reliability, bias, ethics, generalisability or methodology affects the conclusion. A strong answer avoids unsupported opinion and study-name dumping. It links claim, evidence, method and implication so the evaluation explains why the point matters.

Data handling and analysis: Analyse and interpret correlations, including correlation coefficients.

Start with AO1: define the psychological concept, theory, study, method, treatment or data issue named in this objective. Use precise Psychology terminology and keep the wording tied to Data handling and analysis. Then build AO2 or AO3 where relevant. AO2 applies the idea to a scenario, practical context, qualitative data or quantitative data. AO3 analyses, interprets or evaluates by explaining why evidence, validity, reliability, bias, ethics, generalisability or methodology affects the conclusion. A strong answer avoids unsupported opinion and study-name dumping. It links claim, evidence, method and implication so the evaluation explains why the point matters.

Data handling and analysis: Distinguish nominal, ordinal and interval levels of measurement.

Start with AO1: define the psychological concept, theory, study, method, treatment or data issue named in this objective. Use precise Psychology terminology and keep the wording tied to Data handling and analysis. Then build AO2 or AO3 where relevant. AO2 applies the idea to a scenario, practical context, qualitative data or quantitative data. AO3 analyses, interprets or evaluates by explaining why evidence, validity, reliability, bias, ethics, generalisability or methodology affects the conclusion. A strong answer avoids unsupported opinion and study-name dumping. It links claim, evidence, method and implication so the evaluation explains why the point matters.

Data handling and analysis: Explain coding in content analysis.

Start with AO1: define the psychological concept, theory, study, method, treatment or data issue named in this objective. Use precise Psychology terminology and keep the wording tied to Data handling and analysis. Then build AO2 or AO3 where relevant. AO2 applies the idea to a scenario, practical context, qualitative data or quantitative data. AO3 analyses, interprets or evaluates by explaining why evidence, validity, reliability, bias, ethics, generalisability or methodology affects the conclusion. A strong answer avoids unsupported opinion and study-name dumping. It links claim, evidence, method and implication so the evaluation explains why the point matters.

Inferential testing: Explain the purpose of statistical testing.

Start with AO1: define the psychological concept, theory, study, method, treatment or data issue named in this objective. Use precise Psychology terminology and keep the wording tied to Inferential testing. Then build AO2 or AO3 where relevant. AO2 applies the idea to a scenario, practical context, qualitative data or quantitative data. AO3 analyses, interprets or evaluates by explaining why evidence, validity, reliability, bias, ethics, generalisability or methodology affects the conclusion. A strong answer avoids unsupported opinion and study-name dumping. It links claim, evidence, method and implication so the evaluation explains why the point matters.

Inferential testing: Explain when to use the sign test and how to calculate it.

Start with AO1: define the psychological concept, theory, study, method, treatment or data issue named in this objective. Use precise Psychology terminology and keep the wording tied to Inferential testing. Then build AO2 or AO3 where relevant. AO2 applies the idea to a scenario, practical context, qualitative data or quantitative data. AO3 analyses, interprets or evaluates by explaining why evidence, validity, reliability, bias, ethics, generalisability or methodology affects the conclusion. A strong answer avoids unsupported opinion and study-name dumping. It links claim, evidence, method and implication so the evaluation explains why the point matters.

Inferential testing: Use probability, statistical tables and critical values to interpret significance.

Start with AO1: define the psychological concept, theory, study, method, treatment or data issue named in this objective. Use precise Psychology terminology and keep the wording tied to Inferential testing. Then build AO2 or AO3 where relevant. AO2 applies the idea to a scenario, practical context, qualitative data or quantitative data. AO3 analyses, interprets or evaluates by explaining why evidence, validity, reliability, bias, ethics, generalisability or methodology affects the conclusion. A strong answer avoids unsupported opinion and study-name dumping. It links claim, evidence, method and implication so the evaluation explains why the point matters.

Inferential testing: Distinguish Type I errors from Type II errors.

Start with AO1: define the psychological concept, theory, study, method, treatment or data issue named in this objective. Use precise Psychology terminology and keep the wording tied to Inferential testing. Then build AO2 or AO3 where relevant. AO2 applies the idea to a scenario, practical context, qualitative data or quantitative data. AO3 analyses, interprets or evaluates by explaining why evidence, validity, reliability, bias, ethics, generalisability or methodology affects the conclusion. A strong answer avoids unsupported opinion and study-name dumping. It links claim, evidence, method and implication so the evaluation explains why the point matters.

Inferential testing: Explain how level of measurement affects the choice of statistical test.

Start with AO1: define the psychological concept, theory, study, method, treatment or data issue named in this objective. Use precise Psychology terminology and keep the wording tied to Inferential testing. Then build AO2 or AO3 where relevant. AO2 applies the idea to a scenario, practical context, qualitative data or quantitative data. AO3 analyses, interprets or evaluates by explaining why evidence, validity, reliability, bias, ethics, generalisability or methodology affects the conclusion. A strong answer avoids unsupported opinion and study-name dumping. It links claim, evidence, method and implication so the evaluation explains why the point matters.

Inferential testing: Explain how experimental design affects the choice of statistical test.

Start with AO1: define the psychological concept, theory, study, method, treatment or data issue named in this objective. Use precise Psychology terminology and keep the wording tied to Inferential testing. Then build AO2 or AO3 where relevant. AO2 applies the idea to a scenario, practical context, qualitative data or quantitative data. AO3 analyses, interprets or evaluates by explaining why evidence, validity, reliability, bias, ethics, generalisability or methodology affects the conclusion. A strong answer avoids unsupported opinion and study-name dumping. It links claim, evidence, method and implication so the evaluation explains why the point matters.

Inferential testing: Identify when to use Spearman's rho, Pearson's r, Wilcoxon, Mann-Whitney, related t-test, unrelated t-test and Chi-Squared test.

Start with AO1: define the psychological concept, theory, study, method, treatment or data issue named in this objective. Use precise Psychology terminology and keep the wording tied to Inferential testing. Then build AO2 or AO3 where relevant. AO2 applies the idea to a scenario, practical context, qualitative data or quantitative data. AO3 analyses, interprets or evaluates by explaining why evidence, validity, reliability, bias, ethics, generalisability or methodology affects the conclusion. A strong answer avoids unsupported opinion and study-name dumping. It links claim, evidence, method and implication so the evaluation explains why the point matters.

Key terms

• experiments
• observational
• techniques
• including
• naturalistic
• controlled
• questionnaires
• interviews
• correlations
• research methods
• content analysis
• case studies

Exam focus

For shorter answers, define the concept and use the command word precisely. For extended answers, build a chain: point, evidence, explanation, evaluation and conclusion. If the topic uses research methods or statistics, distinguish experiment from correlation, validity from reliability, qualitative from quantitative data, and significance from practical importance.

AO1 knowledge routine

AO1 is secure when the answer names the psychological concept, gives a precise definition and uses the vocabulary expected by the specification. In this topic, students should avoid writing broad everyday explanations. Each definition should connect to a theory, study, method, biological process, cognitive process, treatment or data issue where the learning objective requires it. Strong AO1 also means selecting relevant detail: a short answer may only need one accurate term, while an extended answer may need a sequence of linked ideas.

AO2 application routine

AO2 is needed when the question gives a stem, scenario, practical context, qualitative material or quantitative data. The answer should not repeat the scenario. It should select the relevant detail and explain how the psychological concept applies to it. If the question includes behaviour, participants, results or data, use those details directly before moving into evaluation. This keeps application separate from description and helps the answer stay anchored to the question.

AO3 evaluation routine

AO3 should explain the impact of evidence rather than merely naming a strength or limitation. A useful structure is: make the evaluative point, give the evidence or method detail, explain why it matters and finish with a judgement. For example, a validity issue matters because it affects whether the findings measure what they claim to measure. A reliability issue matters because it affects consistency. Bias matters because it can limit generalisability or create an unbalanced conclusion.

Common mistakes to avoid

• Do not describe a study and assume that counts as AO3 evaluation.
• Do not claim correlation proves causation.
• Do not treat explanation and treatment as the same thing.
• Do not use generic evaluation words unless you explain why the limitation or strength matters.
• Do not mix Paper 3 option groups when answering an option question.

Revision strategy

Use flashcards for AO1 definitions, MCQs for misconceptions, and short written answers for evidence-evaluation chains. After each answer, check whether you have separated description from evaluation and whether your conclusion follows from the evidence.

Final self-check

Before leaving this topic, write one answer that only describes, one answer that applies and one answer that evaluates. Label the AO used in each sentence. If an evaluation sentence could fit any Psychology topic, make it more specific by adding the study, method, validity issue, reliability issue, ethical issue or data implication. This final check prevents generic writing and prepares students for questions that combine knowledge, application and evaluation in one response.

Building stronger paragraphs

A reliable paragraph structure is point, evidence, reasoning and judgement. The point should name the psychological idea. The evidence should be specific enough to show that the answer is not guessing. The reasoning should explain how the evidence supports, challenges or limits the claim. The judgement should say what this means for confidence in the explanation, method or treatment. This structure is especially useful when the question asks students to discuss or evaluate, because it prevents long descriptive paragraphs that never become analytical.

Method and evidence checks

When evidence comes from research, check the method before writing the conclusion. Experiments can support cause-and-effect reasoning when variables are controlled, but correlations only show relationships. Samples affect generalisability, controls affect internal validity, and repeated or standardised procedures affect reliability. These checks help students explain why evidence is strong or limited rather than simply saying that a study supports the topic.

Making conclusions precise

A conclusion should follow from the evidence already used. If the evidence is limited by bias or weak validity, the conclusion should be cautious. If the evidence is consistent and methodologically strong, the conclusion can be more confident. This does not mean writing a long final paragraph every time; it means ending the answer with a clear implication that matches the quality of the evidence.