Logistic Regression
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:
- Say when to use logistic instead of linear regression.
- Interpret coefficients as log-odds / odds ratios.
When the outcome is binary (yes/no), logistic regression models the log-odds of the outcome as a linear function of predictors, squashing predictions to 0–1 with the logistic function. Coefficients are log-odds; exponentiate them for odds ratios.
[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
TODO — a short question.
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.