Power & Effect Size
Info sheet · Statistics for Psychology & Neuroscience
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What you’ll get from this sheet
By the end you should be able to:
- Define effect size and statistical power.
- Run a power analysis to plan a sample size.
Effect size measures how big an effect is, independent of n; power is the chance of detecting a real effect. Power rises with effect size, α, and — crucially — sample size. Underpowered studies miss real effects and produce flukier significant ones.
[Main idea]
TODO — write the core explanation in transcript voice.
[Interactive demo]
TODO — native <input> + string-built SVG / OJS widget (see any built sheet for the pattern).
See it in code
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TipCheck your understanding
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TODO — the worked answer.
TODO — a common mistake and how to avoid it.
Where this shows up next
TODO — link to the relevant book chapter.