Evaluate two simple regression models estimated by raphael

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Managerial Accounting Assignment

Cost estimation and management of overhead costs

Pauline Raphael, executive assistant to the principal of Ecole Superieure 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 specializations, 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:

Year	Overhead costs ('000)	Number of academic programmes	Number of enrolled students
1	£ 13500	29	3400
2	19200	36	5000
3	16800	49	2600
4	20100	53	4700
5	19500	54	3900
6	23100	58	4900
7	23700	88	5700
8	20100	72	3900
9	22800	83	3500
10	29700	73	3700
11	31200	101	5600
12	38100	103	7600

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

Regression 1: Overhead costs = a + (b* Number of academic programmes)

Variable	Coefficient	Standard error	t-value
Constant	£ 7127.75	£ 3335.34	2.14
Independent variable 1: number of academic programmes	£ 240.64	£ 47.33	5.08

R² = 0.72; Durbin-Watson statistic = 1.81

Regression 2: Overhead costs = a + (b* Number of enrolled students)

Variable	Coefficient	Standard error	t-value
Constant	£ 5991.75	£ 5067.88	1.18
Independent variable 1: number of enrolled students	£ 3.78	£ 1.07	3.53

R² = 0.55; Durbin-Watson statistic = 0.77

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 Raphael.

3. What insights do the analyses provide about controlling and reducing overhead costs at the Ecole Superieure?

4. Given the findings from the simple regression analysis, should Raphael use multiple regression analysis to better understand the cost drivers of overhead costs? Explain your answer.

5. Suppose that Raphael decides that the simple regression analysis should be extended to a multiple regression analysis. She finds the following result:

Regression 3: Overhead costs = a + (b₁*Number of academic programmes) + (b₂*Number of enrolled students)

Variable	Coefficient	Standard error	t-value
Constant	£ 2779.62	£ 3620.05	0.77
Independent variable 1: number of academic programmes	£ 178.37	£ 51.54	3.46
Independent variable 2: number of enrolled students	£ 1.87	£ 0.92	2.03

R² = 0.81; Durbin-Watson statistic = 1.84

The coefficient of correlation between number of academic programmes and number of students is 0.60. Evaluate the multiple regression models. Assume linearity and constant variance and normality of residuals. Should Raphael choose the multiple regression models over the two simple regression models?

6. How might the principal of the Ecole Superieure use these regression results to manage overhead costs?

Reference no: EM131263397

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Reviews

len1263397

11/2/2016 6:19:17 AM

Hi, I need help in comparing the standard errors and t-values for the 2 simple regression models for my coursework assessment. This is a group work assignment. You are encouraged to use textbooks, articles and other sources of information to support your argument. Font: Times New Roman, size 12, double-spaced). The assignment should not exceed 2,000 words in length. (Excessive length will be penalized). Appendices (containing tables or illustrative material) and references will not be counted as part of the 2,000 words.

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