What can analysis of sample correlation coefficients indicate about independent variables?

The analysis of sample correlation coefficients helps to quantify the strength and direction of the linear relationship between independent variables and a dependent variable. When the correlation coefficient is strong (close to 1 or -1), it suggests that the independent variable has predictive power and may be a good predictor of the outcome being studied. Conversely, a weak correlation (close to 0) indicates that the independent variable is unlikely to be a good predictor.

This interpretation aligns with the choice indicating that independent variables may be good predictors. It signifies that if there is a notable correlation coefficient, it suggests potential usefulness in forecasting or influencing the dependent variable. Since correlation does not entail a cause-and-effect relationship, it is essential to consider further analyses to confirm their predictive abilities, but the correlation coefficients themselves can certainly indicate potential.