In one line: Bias is anything that pulls research away from the truth.
You already know how bias works.
Picture watching a match next to someone who supports the other team. The same tackle goes in — you see a clear foul, they see a fair challenge.
Neither of you is lying. You each honestly notice the version that fits what you already believe.
Researchers are people too. What they hope to find can quietly shape a study, without them ever meaning it to.
In psychology, bias is any influence that stops research being objective.
Memory hook: Bias = a filter on the truth.
It is not lying. It is an honest tilt that skews what we see or report.
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Key idea: Different biases sneak in at different stages.
Learn to spot the main five.
Imagine a study asking: does a new energy drink make people run faster?
Watch how bias could creep in at each step.
Sampling bias
The people studied don't represent the wider group.
Here: only keen runners who already love energy drinks volunteer — so the result may not apply to anyone else.
Researcher bias
The researcher's hopes shape how they run or read the study.
Here: the drink company is paying for the study, so the researcher is quick to see a good result.
Participant bias
People act differently because they know they are being studied.
Here: the runners push harder than they normally would, simply because someone is standing there timing them.
Confirmation bias
You notice what fits your expectation and ignore what doesn't.
Here: the researcher counts every fast run as proof, but explains away the slow ones as "just a bad day".
Publication bias
Mostly positive results get published.
Here: "Energy drink boosts speed!" gets printed — the ten studies where it did nothing are never seen.
Exam tip: Name the type, then say how it would affect this study.
"There is bias" scores little. "Sampling bias means the result only applies to keen runners" scores well.
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The concept behind it: Bias threatens objectivity — the whole point of research.
If bias is not controlled, we cannot trust that the findings are really true.
So psychologists build in controls to keep themselves honest. Everyone gets the same standard instructions, so no group is nudged differently.
A double-blind design goes further. In the energy-drink study, neither the runner nor the person holding the stopwatch would know who got the real drink and who got plain water — so neither can tilt the result.
Researchers also check their own thinking, which is called reflexivity.
Repeating a study (replication) is the biggest safeguard of all.
If a biased result was a one-off, other researchers usually fail to repeat it.
Go further — higher-level insight: Publication bias hides the failures.
Because journals prefer exciting "it works" results, the studies where nothing happened sit unseen in a drawer — the file-drawer problem.
So the published picture can look stronger than the truth.
How this is tested: Bias is one of the four named concepts for Paper 2 Section B (bias · causality · measurement · responsibility). There you are given a study and asked to discuss it with reference to a concept. Bias also frames Paper 1 Section C essays and Paper 3.
The skill: spot where bias enters, and explain how it weakens the study.
A researcher advertises for volunteers to test whether their new meditation app lowers stress. Volunteers rate their own stress before and after using the app for a week. The researcher reports that stress fell and concludes the app works. Discuss this study with reference to bias.
Model answer plan
See the mark-by-mark plan — for / against / judgement, with marking guidance — in study mode.
Common mistakes: 1. Just saying 'there is bias'. Always name the TYPE and its effect on the study.
2. Only listing biases. A [15] answer must weigh and reach a judgement.
3. Ignoring the concept. Keep the word 'bias' and objectivity central.