Regression is used when you have a clear outcome, and you want to (a) know what causes it and (b) predict the outcome based on the values for the causes. The goal of multiple regression is to find the model with the most predictive power and as few predictors as possible. An example shows the prediction of peak bloom time for Washington DC’s cherry trees.
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