that a school is trying to predict how many fall applicants it will have. The administrator thinks that the two biggest factors driving applicants are number of high school seniors in the school's recruiting territory (Applicant Pool) and the Tuition Cost. (a) Use Excel to perform a Linear Regression using Applicant Pool to predict Fall Applicants. Write down the equation. What is the R Square? (b) Use Excel to then perform a Multiple Linear Regression using both Applicant Pool and Tuition Cost to predict Fall Applicants. What is the equation and R Square? (c) Suppose that the school has estimated that there will be 65000 students in the Applicant Pool in the next year. They are currently planning to charge $20000 in Tuition Cost. How many Fall Applicants will they have? Use your results in (b) to predict this. x1 x2 Tuition Cost Applicant Pool Fall Applicants 9000 76200 11060 12500 78050 10900 13750 67420 8670 14000 70390 9050 15500 62550 7400 16250 59230 7100 17500 57900 6300 19300 60080 6100 that a school is trying to predict how many fall applicants it will have. The administrator thinks that the two biggest factors driving applicants are number of high school seniors in the school's recruiting territory (Applicant Pool) and the Tuition Cost. (a) Use Excel to perform a Linear Regression using Applicant Pool to predict Fall Applicants. Write down the equation. What is the R Square? (b) Use Excel to then perform a Multiple Linear Regression using both Applicant Pool and Tuition Cost to predict Fall Applicants. What is the equation and R Square? (c) Suppose that the school has estimated that there will be 65000 students in the Applicant Pool in the next year. They are currently planning to charge $20000 in Tuition Cost. How many Fall Applicants will they have? Use your results in (b) to predict this. x1 x2 Tuition Cost Applicant Pool Fall Applicants 9000 76200 11060 12500 78050 10900 13750 67420 8670 14000 70390 9050 15500 62550 7400 16250 59230 7100 17500 57900 6300 19300 60080 6100