What you'll learn

• The purpose of each main section in a psychology practical report.
• How to organise method, results, discussion, references and appendices clearly.
• How Harvard referencing works in OCR A-Level Psychology.
• Why peer review matters for making psychology more scientific and trustworthy.

Why report writing matters

A practical report is a formal write-up of a psychological investigation. It follows a standard structure so another psychologist can understand what was done, check whether the conclusions are justified, and potentially replicate the study — meaning repeat it using the same procedure to see whether similar findings occur.

The report is a fixed route: summary first, then background, then method, then evidence, then interpretation, then sources and supporting material.

The main sections of a practical report

Abstract

The abstract is a brief overview of the whole report. It usually summarises the aim, method, key results and conclusion.

Although it appears first, it is often easiest to write last because you need to know exactly what your study found before you can summarise it.

Introduction

The introduction explains the background to the study. It moves from wider psychological theory and previous research to your specific aim and hypotheses.

For OCR H567, this is where you might cite relevant core studies, such as Bandura et al. (1961) on aggression, Milgram (1963) on obedience, Sperry (1968) on split-brain research, or Loftus and Palmer (1974) on eyewitness testimony.

An aim states what the study is trying to investigate. A hypothesis is a testable prediction. The null hypothesis predicts no significant effect, difference or relationship.

Method

The method explains exactly how the study was carried out. It should be clear enough for replication.

Design

The design describes the type of study and how variables were organised. For example, in an experiment you would identify the independent variable, which is manipulated, and the dependent variable, which is measured. You may also state whether the design was independent measures, repeated measures or matched pairs.

Sample

The sample is the group of participants used in the study. This subsection should include the number of participants, relevant characteristics, and the sampling method, such as opportunity sampling or volunteer sampling.

Materials/apparatus

Materials or apparatus are the items used to conduct the study, such as questionnaires, word lists, consent forms, standardised instructions, debrief sheets or computer tasks.

Procedure

The procedure gives a step-by-step account of what participants experienced. It should include ethical features such as informed consent, right to withdraw, confidentiality, protection from harm and debriefing, in line with the BPS Code of Human Research Ethics.

Results

The results section presents the findings clearly and objectively. It should not turn into a long interpretation — save that for the discussion.

Results may include:

• Descriptive statistics: summaries of data, such as mode, median, mean, range, variance and standard deviation.
• Percentages, fractions and ratios: ways of showing proportions, such as 60%, 3/5 or 3:2.
• Graphs: bar charts for categories, histograms for continuous interval data, line graphs for change over time or conditions, pie charts for proportions, and scatter diagrams for correlations.
• Inferential statistics: tests used to judge whether findings are likely to be due to chance.

You also need to understand levels of measurement. Nominal data are categories, such as “male/female” or “yes/no”. Ordinal data are ordered or ranked, but the gaps are not necessarily equal. Interval data use equal intervals between scores, such as scores on a memory test.

If reporting inferential statistics, state the statistical test, the observed value, the critical value from a statistical table, the significance level, and whether the result is significant. A common significance level is 0.05, meaning a 5% probability of the result occurring by chance if the null hypothesis is true.

Non-parametric tests you should recognise include:

• Mann-Whitney U: difference test for independent groups.
• Wilcoxon Signed Ranks: difference test for related groups.
• Chi-square: test of association or difference using nominal data.
• Binomial Sign Test: difference test for related nominal data.
• Spearman’s Rho: correlation test for ranked or ordinal data.

A parametric test is usually considered when data are interval level, approximately normally distributed, have no major outliers, and meet assumptions such as similar variance across groups.

Discussion

The discussion interprets the results. It explains whether the hypothesis was supported, links findings back to previous research, and considers the wider meaning.

This is also where you evaluate the study. You might discuss validity, reliability, sampling bias, ethics, demand characteristics, researcher bias, usefulness, and possible improvements.

You should also show awareness of statistical errors. A Type I error is a false positive: rejecting the null hypothesis when it is actually true. A Type II error is a false negative: failing to reject the null hypothesis when it is actually false.

References

The references section lists every source cited in the report. It allows readers to check where ideas came from and helps avoid plagiarism.

Appendices

Appendices contain supporting material that would interrupt the main report if included in full. This might include raw data, consent forms, standardised instructions, questionnaires, calculations, debrief sheets or extra tables.

Harvard referencing

Harvard referencing is an author-date system. In the main text, you cite the author surname and year. At the end, you give the full reference.

For example:

• In-text citation: Milgram (1963) investigated obedience to authority.
• Parenthetical citation: Obedience may be affected by authority figures (Milgram, 1963).
• Reference list entry: Milgram, S. (1963) Behavioral study of obedience. Journal of Abnormal and Social Psychology, 67, (4), 371–378.

Peer review

Peer review is the process where other experts in psychology check a piece of research before publication. Reviewers examine whether the aims are clear, the method is valid, the statistics are appropriate, the conclusions are justified, and ethical issues have been considered.

Peer review helps the psychological community validate new knowledge and maintain integrity. It can reduce errors, exaggeration and weak reasoning.

However, it is not perfect. Reviewers may miss fraud or mistakes, popular theories may be favoured, and publication bias can mean significant findings are more likely to be published than non-significant findings.