The regression constant in the best linear prediction rule is
A) the mean of the criterion variable minus the result of multiplying the regression coefficient by the mean of the predictor variable.
B) the mean of the criterion variable plus the result of multiplying the regression coefficient by the mean of the predictor variable.
C) the mean of the criterion variable minus the result of dividing the regression coefficient by the mean of the predictor variable.
D) the mean of the criterion variable plus the result of dividing the regression coefficient by the mean of the predictor variable.
Correct Answer:
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