Final answer:
When the correlation between study time and exam scores changes from +0.80 to +0.08, the predictive power of study time on exam scores is significantly diminished, suggesting that it's no longer a reliable predictor.
Step-by-step explanation:
When a professor finds out that the correlation between study time and exam scores is +0.08 instead of +0.80, it indicates that there is a much weaker relationship between the two variables. In terms of predictions, this lower correlation coefficient means that study time is less predictive of exam scores. Predictions based on study time will be less accurate and might not be useful for making informed decisions about student performance.
Correlation coefficient values closer to 1 suggest a strong relationship, whereas values close to 0 suggest a weak or non-existent relationship between the variables. Therefore, when the correlation is adjusted from +0.80 to +0.08, the strength of the predictive ability of the regression model is substantially reduced. The suggestion to divide results by 10 is incorrect, as the correlation coefficient does not suggest a method of adjusting predictions in that manner; instead, it indicates the degree to which variables are linearly related.
Additionally, it is crucial to consider the coefficient of determination (r-squared value), which tells us the proportion of the variance in the dependent variable that is predictable from the independent variable. A correlation of +0.08 would yield a very low coefficient of determination, signaling that very little variance in exam scores can be explained by study time.