In Professor Friedman's economics course the correlation between the students' total scores before the final examination and their final examination scores is r = 0.52. The pre-exam totals for all students in the course have mean 300 and standard deviation 37. The final exam scores have mean 70 and standard deviation 12. Professor Friedman has lost Julie's final exam but knows that her total before the exam was 284. He decides to predict Julie's final exam score from her pre-exam total. Question 1. Calculate the slope and intercept of the least squares regression line where the x-variable is pre-exam total score and the y-variable is final exam score. slope (use 4 decimal places in your answer) intercept (use 4 decimal places in your answer) Question 2. What is the value of Julie's final exam score predicted by the least squares