Question

SUMMARY OUTPUT Confidence Interval Estimate and Prediction Interval Data ression Statistics Confidence Level 95% Multiple R R Square Adjusted R Square Standard Error Observations 0.9035 iven vaue iven value Sa ED1 given value ED2 given value 400 1.7353 ANOVA Predicted Y (YHat) 11.37451 sS Significance F 4.0112E-07 MS For Average Predicted Y (YHat) Regression Residual Total Interval Half Width Confidence Interval Lower Limit Confidence Interval U 1.867459 9.507054 13.24197 60.23 327.84 24 r Limit A car manufacturer would like to develop a regression model that would predict the number of cars sold per month by a dealership employee based on the employee's number of years of sales experience (Exp), the employee's weekly base salary before commissions (Salary), and the education level of the employee. There are three levels of education in the sales force-high school degree, associate's degree, and bachelor's degree. The following dummy variables have been defined: ED1-1 for a Bachelor's degree, ED1 0 otherwise; ED2 1 for an Associate's degree, ED2 0 otherwise. The given Excel output shows the partially completed regression output from a random sample of employees from the previous month. What is the 95% prediction interval for the number of cars sold per month by a specific employee with seven years of experience, a salary of $400 per week, and a bachelor's degree? 囲Click the icon to view the Excel output. A. (7.30, 15.45) B. (8.58, 14.16) C. (9.51, 13.24) O D. (5.50, 17.24) о в

Answer 1