Evaluating alternative simple regression models, not for profit.

(Chapter Appendix) (30-40 minutes) Pauline Raphael, executive assistant to the principal of Ecole Supérieure des Mines de St Etienne, is concerned about the overhead costs at her university. Cost pressures are severe, so controlling and reducing overheads is very important. Raphael believes overhead costs incurred are generally a function of the number of different academic programmes (including different specialisations, degrees and majors) that the university has and the number of enrolled students. Both have grown significantly over the years. She collects the following data: cde2

REQUIRED 1. Plot the relationship between overhead costs and each of the following variables:

(a) number of academic programmes, and

(b) number of enrolled students.
2. Compare and evaluate the two simple regression models estimated by Raphaél. Use the comparison format employed in Exhibit 9-20.
3. What insights do the analyses provide about controlling and reducing overhead costs at the Ecole Supérieure?

Transcribed Image Text:

YEAR OVERHEAD COSTS NUMBER OF (IN THOUSANDS) ACADEMIC PROGRAMMES NUMBER OF ENROLLED STUDENTS 1234 EUR 13,500 29 3,400 19,200. 36 5,000 16,800 49 2,600 20,100 53 -4,700 5 19.500 54 3,900 6 23,100 58 4.900 7 23.700 88 5,700 8 20,100 72 3,900 9 22,800 83 3,500 10 29,700 73 3,700 11 31,200 101 5,600 12 38,100 103 7.600 She finds the following results for two separate simple regression models: Regression 1: Overhead costs a + (b X Number of academic pro- grammes) VARIABLE Constant Independent variable 1: Number of academic COEFFICIENT STANDARD ERROR -VALUE EUR 7,127.75 EUR 3,335.34 2.14 programmes EUR 240.64 p=0.72;Durbin-Watson statistic = 1.81 EUR 47.33 5.08