In one line: Reducing bias is how research earns the right to be trusted.
You have met the biases: sampling, researcher, participant, cultural, gender. Spotting them is step one. The real skill examiners reward is knowing how to fix them — how to make a study fairer and its findings more believable.
The goal is objectivity. Every method below is a tool for protecting it.
Memory hook: Spot it, then fix it. Naming a bias is half marks; explaining a fix is the rest.
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Key idea: A handful of methods control most bias. Learn what each one does.
Picture fixing our earlier study — does a meditation app lower stress? Here is the toolkit applied to it.
Representative / random sampling
Pick participants so they mirror the wider group. Here: randomly invite people, not just app fans — fixes sampling bias.
Standardised procedure
Everyone gets the same instructions and conditions. Here: identical stress measure and timing for all — stops small differences creeping in.
Blinding (single / double-blind)
Keep the aim, or the group, hidden. Here: participants don't know if they got the real app or a fake one — fixes participant and researcher bias.
Reflexivity
The researcher writes down how their own hopes might tilt the study. Here: the app's inventor names their stake — keeps interpretation honest.
Replication & peer review
Others repeat and check the study. Here: independent teams retest it — a one-off bias rarely survives.
Exam tip: Don't just list tools — say which bias each one fixes. 'Use a random sample' scores; 'use a random sample so the results represent everyone, fixing sampling bias' scores more.
See how examiners mark answers
Access past paper questions with model answers. Learn exactly what earns marks and what doesn't.
The concept behind it: Reducing bias protects objectivity — and it is also responsibility: fair, trustworthy research is part of a psychologist's duty. Different biases need different fixes.
The bias
- Sampling bias
- Participant bias
- Researcher bias
- Cultural bias
- Gender bias
- Publication bias
The best fix
- Random / representative sampling
- Single-blind design, hide the aim
- Double-blind design, reflexivity
- Emic approach, translate + back-translate
- Balanced sample, report each group
- Pre-registration, publish all results
Go further — higher-level insight: Pre-registration fights publication bias before it starts. Researchers post their plan and hypothesis before collecting data, so the study gets counted whether it 'works' or not — the failures can no longer quietly vanish into the drawer.
How this is tested: Reducing bias is core research-methods knowledge — it powers Paper 2 (designing and improving studies) and the 'reduce the bias' half of a Paper 2 Section B answer. The skill: match the right fix to each bias and explain why it works.
A researcher tests whether a new revision method improves exam scores by teaching it to their own tutor group, who know the researcher hopes it works, and comparing their scores to another class. Explain how the researcher could reduce bias in this study.
Model answer plan
See the mark-by-mark plan — for / against / judgement, with marking guidance — in study mode.
Common mistakes: 1. Listing fixes with no bias named. Pair each fix to the bias it targets.
2. No 'why'. Say why the fix reduces that bias.
3. One magic fix. Different biases need different tools.