In one line: A reliable measure gives you the same answer when nothing has really changed.
Part of the concept of measurement is asking whether a measure is trustworthy. Reliability is the first test: does it give steady, repeatable results?
Think of a bathroom scale. If it reads 60 kg, then 64 kg, then 61 kg for the same person in one minute, it is unreliable — you cannot trust any single reading. A psychological measure can be wobbly in exactly the same way.
Memory hook: Reliable = repeatable. Same conditions in, same result out.
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Key idea: Psychologists mainly check two things: is the measure steady over time, and do different people using it agree?
Checking reliability
Test-retest
Give the same test to the same people twice, a while apart. If scores are stable (and nothing changed), the measure is reliable over time.
Inter-rater
Two observers rate the same behaviour independently. If they closely agree, the measure does not depend on who is using it.
Internal consistency
On a questionnaire, items meant to measure the same thing should give similar answers — the parts hang together.
Same test, later · Different raters, same time
Take a new aggression checklist. Test-retest: the same children are rated two weeks apart and scores match. Inter-rater: two teachers rate the same playground session and closely agree. Internal consistency: the checklist's items all point the same way. Now the measure looks reliable.
Go further — higher-level insight: Reliability is necessary but not sufficient. A measure can be perfectly consistent yet consistently measure the wrong thing — a scale that always reads 5 kg heavy is reliable but wrong. Reliability is only half the story; validity is the other half.
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How this is tested: Reliability is a go-to evaluation point. When a question asks you to evaluate a study or a measure, you can ask: would it give the same result again? Name the type of reliability and how you would check it.
As a researcher, explain how you would check that a new observation-based measure of classroom anxiety is reliable.
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Common mistakes: 1. Confusing reliability with validity. Reliability is consistency, not correctness.
2. No method. Say how you would check (two raters, retest).
3. Forgetting 'no real change'. Test-retest only works if the thing itself hasn't changed.