Suppose you plotted a scatter plot between the residuals and predicted values in linear regression and you found that there is a relationship between them. Which of the following conclusion do you make about this situation?

The correct answer is: C. Can’t say.

A relationship between the residuals and predicted values does not necessarily mean that the model is good or bad. It could be that the model is capturing the relationship between the variables well, but there is still some random error in the data. Alternatively, it could be that the model is not capturing the relationship between the variables well, and the relationship between the residuals and predicted values is due to overfitting or other problems.

To determine whether the model is good or bad, we need to look at other evidence, such as the coefficient of determination, the p-values of the coefficients, and the distribution of the residuals.

Here is a brief explanation of each option:

• Option A: Since the there is a relationship means our model is not good. This is not necessarily true. A relationship between the residuals and predicted values could be due to random error, or it could be due to the model not capturing the relationship between the variables well.
• Option B: Since the there is a relationship means our model is good. This is also not necessarily true. A relationship between the residuals and predicted values could be due to random error, or it could be due to the model overfitting the data.
• Option C: Can’t say. This is the correct answer. We cannot say whether the model is good or bad based on the information given.
• Option D: None of these. This is not a correct answer.