The higher the absolute value of the correlation coefficient, regardless of whether it is direct or indirect (positive or negative), the more accurate the prediction is of one variable from the other based on that correlation. That’s because the more two variables share in common, the more you know about the second variable based on your knowledge of the first variable. And you may already surmise that when the correlation is perfect (+1.0 or −1.0), then the prediction is perfect as well. If rxy = −1.0 or +1.0 and if you know the value of X, then you also know the exact value of Y. Likewise,
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