How do correlations and case studies investigate behaviour, and what can and cannot they show?
Correlation (co-variables, positive, negative and zero correlations, correlation coefficients, scattergrams, correlation does not equal causation) and case studies (in-depth study of an individual or small group, qualitative data, strengths and weaknesses).
An Eduqas A-Level Psychology answer to correlation and case studies in Component 2. Covers co-variables, positive, negative and zero correlations, correlation coefficients and scattergrams, why correlation is not causation, and the strengths and weaknesses of case studies.
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What this dot point is asking
Component 2 covers correlation and case studies as methods. You must know what a correlation is (and why correlation is not causation), how to read coefficients and scattergrams, and the strengths and weaknesses of the case study method.
The answer
Correlation
Correlation is not causation
Case studies
A case study is an in-depth investigation of a single individual, group or event, often using several methods (interviews, observation, tests) and producing mainly qualitative data.
- Strengths. Rich, detailed data; can study rare cases (for example brain damage) impossible to create experimentally; can challenge existing theory.
- Weaknesses. Cannot be generalised (one case); data and interpretation can be subjective and biased; often retrospective and reliant on memory.
Examples in context
Example 1. Maguire and correlation. Maguire's finding that posterior hippocampal volume correlated with years of taxi driving cannot prove navigation caused the change, because people with larger hippocampi might be drawn to the job (direction) or a third factor could explain both. This shows correlation in a real study.
Example 2. Why case studies are double-edged. A case study of a brain-damaged patient can reveal what a damaged region normally does (rich, unique data), but one patient cannot tell us about everyone, and the researcher's interpretation may be biased. This is the generalisability-versus-depth trade-off.
Try this
Q1. State what a correlation coefficient of tells you. [2 marks]
- Cue. A weak negative correlation: as one co-variable increases the other tends to decrease slightly, but the relationship is weak (close to ).
Q2. Give two reasons a correlation cannot establish cause and effect. [2 marks]
- Cue. The direction of the relationship is unknown (A could cause B or vice versa), and a third (confounding) variable could cause both co-variables.
Q3. Explain one strength of the case study method. [2 marks]
- Cue. It provides rich, in-depth, detailed data and can study rare cases (for example brain damage) that could not be created experimentally.
Exam-style practice questions
Practice questions written in the style of WJEC Eduqas exam questions on this dot point, with worked answer explainers. The year tag is the paper they imitate, not the source.
Eduqas 20196 marksA study finds a correlation coefficient of between hours of sleep and reported anxiety. Explain what this tells us, and why it does not show that sleep loss causes anxiety. [6 marks]Show worked answer →
An interpretation item (AO2/AO3). Maths content.
A coefficient of is a strong negative correlation: as one co-variable increases the other decreases, so more hours of sleep is associated with lower reported anxiety (and less sleep with higher anxiety). The value is close to , so the relationship is strong.
It does not show causation because: (1) the direction of the relationship is unknown (anxiety might cause poor sleep rather than poor sleep causing anxiety); (2) a third variable (for example stress or illness) could cause both; and (3) no variable was manipulated, so confounds cannot be ruled out.
Markers reward correct interpretation of the sign and strength of the coefficient and at least two reasons correlation does not equal causation.
Eduqas 20218 marksExplain one strength and one weakness of the case study method, using an example. [8 marks]Show worked answer →
A knowledge item (AO1/AO3) with an example.
Strength: case studies provide rich, in-depth, detailed data about an individual or rare situation that other methods cannot capture (for example Freud's Little Hans gave detailed longitudinal data on one child's development), and they can study rare cases (such as brain-damaged patients) impossible to create experimentally.
Weakness: findings cannot be generalised because the sample is one person or a small group, and the data and interpretation can be subjective and prone to researcher bias (as in Little Hans, where the father collected the data and Freud interpreted it to fit his theory).
Markers reward a developed strength and weakness anchored to a named example.
Related dot points
- The experimental method: types of experiment (laboratory, field, natural, quasi), independent and dependent variables and operationalisation, hypotheses, extraneous and confounding variables and controls, and experimental designs (independent groups, repeated measures, matched pairs).
An Eduqas A-Level Psychology answer to the experimental method in Component 2. Covers laboratory, field, natural and quasi experiments, independent and dependent variables, operationalisation, hypotheses, extraneous and confounding variables, controls, and the three experimental designs with their strengths and weaknesses.
- Non-experimental methods: observation (naturalistic, controlled, participant, non-participant, overt, covert; behavioural categories and sampling) and self-report (questionnaires and interviews; open and closed questions; designing good questions).
An Eduqas A-Level Psychology answer to observation and self-report methods in Component 2. Covers types of observation, behavioural categories, event and time sampling, questionnaires and interviews, open and closed questions, and the strengths and weaknesses of each method.
- Reliability (internal and external; test-retest, inter-observer; how to assess and improve it) and validity (internal and external; face, concurrent, ecological, temporal and population validity; demand characteristics and investigator effects; how to assess and improve it).
An Eduqas A-Level Psychology answer to reliability and validity in Component 2. Covers internal and external reliability, test-retest and inter-observer reliability, internal and external validity, face, concurrent, ecological, temporal and population validity, demand characteristics and investigator effects, and how to assess and improve each.
- Descriptive statistics: measures of central tendency (mean, median, mode), measures of dispersion (range, standard deviation), levels of measurement (nominal, ordinal, interval), percentages and ratios, and presenting data (tables, bar charts, histograms, scattergrams).
An Eduqas A-Level Psychology answer to descriptive statistics in Component 2. Covers the mean, median and mode, range and standard deviation, levels of measurement, percentages and ratios, and how to present quantitative data in tables, bar charts, histograms and scattergrams, with worked calculations.
- Inferential statistics: probability and significance (), the null and alternative hypotheses, choosing the correct test (the binomial sign test, Mann-Whitney U, Wilcoxon, Spearman's rho, chi-square) from design and level of measurement, observed versus critical values, and Type I and Type II errors.
An Eduqas A-Level Psychology answer to inferential statistics in Component 2. Covers probability and the 0.05 significance level, the null hypothesis, how to choose between the binomial sign test, Mann-Whitney U, Wilcoxon, Spearman's rho and chi-square, comparing observed and critical values, and Type I and Type II errors.
Sources & how we know this
- Eduqas GCE A Level in Psychology (A290) specification — Eduqas (2015)