Correlation is a measure of linear association between two variables X and Y, while linear regression is a technique to make predictions, using the following model: Y = a0 + a1 X1 + ... + ak Xk + Error Here Y is the response (what we want to predict, for instance revenue) while the Xi's are the predictors (say gender, with 0 = male, 1 = female, education level, age, etc.) The predictors are somet…
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