Answer Happy

In Professor Friedman's economics course the correlation between
the students' total scores before the finals and their
finals scores is r = 0.7. The
pre-finals totals for all students in the course have
mean 293 and standard deviation 25. The
finals scores have mean 62 and standard
deviation 10. Professor Friedman has lost Julie's
final but knows that her total before the
final was 296. He decides to predict Julie's
final score from her pre-final total.
Question 1. Calculate the slope and intercept
of the least squares regression line where
the x-variable is pre-final total score and
the y-variable is final 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 score predicted by the least squares regression
line?
(use 4 decimal places in your answer)
Question 3. Julie complains to Professor
Friedman that her final score could have been much higher than
what is predicted by the least squares regression line. Calculate
the proportion of the variation in final scores that is
explained by the linear relationship between pre-final scores and
final scores. (Express your answer as a decimal, not as a
percent).
(use 3 decimal places in your answer)