wunder beta📘 R-squared describes variation accounted for by a model
R-squared, written R2 or R-squared, is the coefficient of determination. In an ordinary regression with an intercept, it compares variation around the fitted model with total variation around the response mean. An R-squared of 0.64 means th
What you’ll learn
- Name the statistic
- Read the percentage
- Connect the sums of squares
- Separate association from cause
- Question accuracy claims
- Inspect the residuals
- Compare models carefully
- Mind the data range
- Use a reporting checklist
- Practice the sentence
Questions this course answers
What does R-squared summarize in ordinary regression?
R-squared compares model-accounted variation with total response variation in the fitted data.
What does R-squared = 0.64 mean?
The interpretation is about variation across the observed response values, not individual correctness or causation.
Why does a high R-squared not establish causation?
Fit to an association does not identify the assignment mechanism or rule out alternative causes.
What should you inspect alongside R-squared?
Diagnostics and context reveal curvature, changing spread, outliers, uncertainty, and range limits.
Why can adding predictors make in-sample R-squared rise mechanically?
Ordinary least squares can fit at least as closely in-sample when extra predictors are available.
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