The Regression Coefficient in the Best Linear Prediction Rule Is

Multiple Choice

The regression coefficient in the best linear prediction rule is

A) the product of the sum of the deviation scores on the predictor variable,multiplied by the sum of the deviation scores on the criterion variable,divided by the predictor variable's sum of squared deviations from the mean.
B) the sum of the products of the deviation scores,divided by the predictor variable's sum of squared deviations from the mean.
C) the product of the sum of the deviation scores on the predictor variable,multiplied by the sum of the deviation scores on the criterion variable,divided by the criterion variable's sum of squared deviations from the mean.
D) the sum of the product of the deviation scores,divided by the criterion variable's sum of squared deviations from the mean.