1. The problem asks why it does not make sense to find the least-squares regression line for the given data of total compensation and stock performance for 12 CEOs. 2. The least-squares regression line is meaningful only if there is a significant linear relationship between the two variables. 3. To determine if a linear relationship exists, we check the correlation coefficient $r$ and compare its absolute value $|r|$ to the critical value from a correlation table. 4. If $|r|$ is less than the critical value, it means the correlation is not statistically significant, and the variables are not linearly related. 5. Without a significant linear relationship, fitting a regression line is not appropriate because it would not reliably describe the data. 6. The other options are incorrect because: - B: Having 12 data points is generally sufficient for regression. - C: The question states it does not make sense, so this is false. - D: Positive and negative values do not prevent fitting a regression line. 7. Therefore, the correct answer is: **A. It does not make sense to find the regression line because the absolute value of the correlation coefficient is less than the critical value, which suggests the two variables are not linearly related.**