multiple correlation is a statistical technique that predicts values of one variable on the basis of two or more other variables. It is the correlation between the variable's values and the best predictions that can be computed linearly from the predictive variables. The coefficient of multiple correlations takes values between .00 and 1.00; a higher value indicates high predictability of the dependent variable from the independent variables, with a value of 1 indicating that the predictions are exactly correct and a value of 0 indicating that no linear combination of the independent variables is a better predictor than is the fixed mean of the dependent variable. Conclusion: Independent variables should correlate highly with the dependent variable and with one another for estimating the maximum value of multiple correlations. Hence, option (1) will be correct.