Place points on the scatter plot, drag them, and watch the OLS regression line, residuals, R², and prediction intervals update in real time.
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R² = 0.91
90.5% of variance in y explained by x
Model Coefficients
For each unit ↑ in x, y changes by 1.821
Typical residual size: ±1.911 (sqrt of SSE/(n−2))
Prediction Tool
Enter an x value to see predictions
Residual Diagnostics
Inspect residual patterns to check OLS assumptions
OLS Principle
Ordinary Least Squares minimises the sum of squared residuals: the total vertical distance² between each point and the fitted line.
R² Explained
R² = 1 − SSE/SST. It measures the proportion of variance in y explained by x. A value near 1 means the model fits well.
PI vs CI
The 95% CI covers the true mean response at x*. The 95% PI covers where a new individual observation will fall, and is always wider.