(5.33) In Professor Friedman's economics course the correlation between the students' total scores prior to the final examination and their final-examination scores is r = 0.6. The pre-exam totals for all students in the course have mean 294 and standard deviation 31. The final-exam scores have mean 76 and standard deviation 8. Professor Friedman has lost Julie's final exam but knows that her total before the exam was 301. He decides to predict her final-exam score from her pre-exam total.

What is the slope and intercept of the least-squares regression line of final-exam scores on pre-exam total scores in this course? (Round the answers to at least three decimal places.)

slope: intercept:

Use the regression line to predict Julie's final-exam score ( 1 point):

Julie doesn't think this method accurately predicts how well she did on the final. Using , can she argue that her actual score could have been much higher than the predicted value?

Yes

No