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examBoard: AQA
examType: GCSE
lessonTitle: Reliability in Research
Imagine you're weighing yourself on a bathroom scale. If you step on and off five times and get five completely different readings, would you trust that scale? Probably not! In psychology research, we need our measurements to be consistent too - this is what we call reliability.
Key Definitions:
Reliability is crucial because without it, we can't trust our findings. If a researcher develops a questionnaire to measure anxiety but the scores bounce around randomly when the same person takes it multiple times, any conclusions drawn would be meaningless. Reliability is the foundation of good research!
Think of reliability like this: If your research is reliable, then any differences you observe are likely due to actual differences between participants or conditions, not random errors or inconsistencies in your measurement tools.
Psychologists assess reliability in different ways depending on what they're measuring. Here are the main types you need to know:
This measures whether a test produces consistent results when given to the same people at different times. It answers the question: "Will we get the same results if we repeat the test?"
If a person scores 115 on an IQ test and then takes the same test two weeks later and scores 75, the test would have poor test-retest reliability. A good IQ test should produce similar scores when the same person takes it multiple times (assuming no significant learning or changes have occurred).
How it's measured: Researchers calculate a correlation coefficient between the first and second set of scores. A correlation close to 1.0 indicates high reliability.
This measures how consistent different observers or judges are when rating the same behaviour or phenomenon. It answers the question: "Will different people agree when observing the same thing?"
In a study of classroom behaviour, two researchers observe the same class and count instances of disruptive behaviour. If one observer counts 12 instances while the other counts 35, there's poor inter-rater reliability. They need clearer definitions of what counts as "disruptive"!
How it's measured: Using statistics like Cohen's Kappa or simple percentage agreement between raters.
This measures whether all items in a test or questionnaire measure the same thing. It answers the question: "Do all parts of our test work together consistently?"
A 10-question anxiety scale should have all questions measuring aspects of anxiety. If some questions seem to measure depression instead, the questionnaire lacks internal consistency.
How it's measured: Usually with Cronbach's alpha, a statistical test that produces a number between 0 and 1. Values above 0.7 typically indicate good internal consistency.
This involves splitting a test into two halves and comparing the results. It answers the question: "Do different parts of our test give consistent results?"
How it's measured: The test is split into two parts (often odd vs. even questions) and the correlation between scores on both halves is calculated.
Reliability is often expressed as a correlation coefficient between 0 and 1. Higher values (closer to 1) indicate greater reliability. Generally:
When reading studies, look for:
In your own research, always:
If you're conducting psychological research, here are practical ways to enhance reliability:
It's important to understand that reliability and validity are related but different concepts:
Imagine throwing darts at a dartboard:
Key point: A measure must be reliable to be valid, but reliability alone doesn't guarantee validity. Think of reliability as a necessary but not sufficient condition for validity.
Exam boards must ensure their GCSE and A-level exams are reliable. If a student would get a grade 7 one day but a grade 4 the next day on the same test, the exam would be useless for measuring achievement. This is why exam boards conduct extensive reliability testing and standardisation.
Psychologists need reliable tools to diagnose mental health conditions. Unreliable assessments could lead to misdiagnosis, inappropriate treatment, or missing serious conditions. This is why clinical tools undergo rigorous reliability testing before being approved for use.
Mary Ainsworth's Strange Situation procedure assesses attachment styles in infants. To ensure reliability, researchers:
This careful attention to reliability helped make the Strange Situation one of the most influential procedures in developmental psychology.
Remember: Without reliability, research findings are like building a house on sand – they simply can't be trusted!
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