Required 1 Given your findings in Exercise9.19, should Raphal use multiple regression analysis to better understand the

Required 1 Given your findings in Exercise9.19, should Raphaël use multiple regression analysis to better understand the cost drivers of overhead costs? Explain your answer.

2 Raphaël decides that the simple regression analysis in Exercise9.19 should be extended to a multiple regression analysis. She finds the following result:

The coefficient of correlation between number of academic programmes and number of students is 0.60. Use the format in Exhibit9.21 to evaluate the multiple regression model. (Assume linearity, and constant variance and normality of residuals.) Should Raphaël choose the multiple regression model over the two simple regression models of Exercise9.19?
3 How might the principal of the Ecole Supérieure use these regression results to manage overhead costs?

Exercise 9.19

Pauline Raphaël, 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. Raphaël believes overhead costs incurred are generally a function of the number of different academic programmes (including different specialisations, degrees and research programmes) that the university has and the number of enrolled students.

Both have grown significantly over the years. She collects the following data:

She finds the following results for two separate simple regression models:

Exhibit 9.20

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Regression 3. Overhead costs = a + (b x Number of academic programmes) + (b2 x Number of enrolled students) Variable Coefficient Standard error t-value Constant 2779.62 3620.05 0.77 Independent variable 1: 178.37 51.54 3.46 Number of academic programmes Independent variable 2: 1.87 0.92 2.03 Number of enrolled students r = 0.81; Durbin-Watson statistic = 1.84