The least squares regression line summarizes how the average value of the response (Y) depends upon the value of an explanatory variable or predictor (X). The fitted value of the response is The value b0 is the intercept and b1 is the slope. The intercept has the same units as the response, and the slope has the units of the response divided by the units of the explanatory variable. The vertical deviations from the line are residuals. The least squares criterion provides formulas for b0 and b1 that minimize the sum of the squared residuals. The r2 statistic tells the percentage of variation in the response that is described by the equation, and the residual standard deviation se gives the scale of the unexplained ...
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