Chapter Summary
Scatterplots show association between two numerical variables. The response goes on the y-axis, and the explanatory variable goes on the x-axis. The visual test for association compares the observed scatterplot to artificial plots that remove any pattern. To describe the pattern in a scatterplot, indicate its direction, curvature, variation, and other surprising features such as outliers. Covariance measures the amount of linear association between two numerical variables. The correlation r scales the covariance so that the resulting measure of association is always between − 1 and +1. The correlation is also the slope of a line that relates the standardized deviations from the mean on the x-axis to the standardized deviations ...
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