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Linear regression fits a line by minimizing the sum of squared residuals (least squares), then judges that line with R² (how much better it predicts than the mean) and a p-value (how often random data could look at le...
Unknown · 0:00
Linear regression fits a line by minimizing the sum of squared residuals (least squares), then judges that line with R² (how much better it predicts than the mean) and a p-value (how often random data could look at le...
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