The following data are the monthly salaries y and the grade point averages x for students who obtained a bachelor's degree in business administration.

GPA	Monthly Salary ($)
2.6	3,700
3.4	3,900
3.6	4,200
3.2	3,800
3.5	4,100
2.9	3,900

The estimated regression equation for these data is

= 2,636.04 + 405.41x

and MSE = 12,927.93.(a)Develop a point estimate of the starting salary (in dollars) for a student with a GPA of 2.7. (Round your answer to the nearest cent).$ (b)Develop a 95% confidence interval for the mean starting salary (in dollars) for all students with a 2.7 GPA. (Round your answers to the nearest cent).$ to $ (c)Develop a 95% prediction interval (in dollars) for Ryan Dailey, a student with a GPA of 2.7. (Round your answers to the nearest cent).$ to $ (d)Discuss the differences in your answers to parts (b) and (c).The confidence interval is wider than the prediction interval, because you use a different critical value when developing a prediction of the starting salary for one new student with a GPA of 2.7 than when developing an estimate of the mean for all students with a GPA of 2.7.The prediction interval is wider than the confidence interval, because you use a different critical value when developing a prediction of the starting salary for one new student with a GPA of 2.7 than when developing an estimate of the mean for all students with a GPA of 2.7. The prediction interval is wider than the confidence interval, because there is more variability associated with predicting the starting salary for one new student with a GPA of 2.7 than there is with estimating the mean for all students with a GPA of 2.7. The confidence interval is wider than the prediction interval, because there is less variability associated with predicting the starting salary for one new student with a GPA of 2.7 than there is with estimating the mean for all students with a GPA of 2.7.The confidence interval is wider than the prediction interval, because confidence intervals are used to predict values of y for new observations corresponding to given values of x, and prediction intervals give an estimate of the mean value of y for a given value of x.