Question

(Q1-Q8)

Excel Project 1 Purchasing Merchandise Number of Department Purchased Purchase Number cost in SIA] inSIBI Orders IC] Suppliers IDI 2,059,000 119,566,000 5,944 1,533,000 68,315,000 4,357 1,066,000 33,505,000 2,793 1,622,000 139,312,000 1,707 875,000 128,811,000 2,125 1,110,000 33,456,000 2,550 1,755,000 38,674,000 3,617 539,000 29,854,000 1,327 557,000 1,729,000 2,523,000 877 1,519,000 86,225,000 1,954 1,548,000 102,875,000 7,586 1,267,000 130,944,000 4,731 190 132 Miami Baltimore New York Toronto Detroit Chicago St. Louis Phoenix Los Angeles Houston San Francisco Seattle Vancouver 208 121,160,000 1,433 168 168 104 201 Q1. Run an OLS regression of A on B. Q2. Run an OLS regression of A on C. Q3. Run an OLS regression of A on D. Q4. Find the best cost driver for the cost of the Purchasing Department. Q5. What are your decision criteria? Q6. According to your regression model, what is a variable cost and a fixed cost of A? Q7. How much variations in A were explained by your cost driver? Q8. What is the relevant range of your model?

Answer 1

The procedure is - select 'data' tab -> select 'data analysis' -> select 'regression' - > Put variable A as 'Input Y range' and appropriate variable at 'Input X range' and press ok.

Q.1. regression of A on B

Regression Statistics
Multiple R	0.023933
R Square	0.000573
Adjusted R Square	-0.09028
Standard Error	489046.3
Observations	13

	Coefficients
Intercept	1302646
B	0.000236

Q.2. OLS regression of A on C

Regression Statistics
Multiple R	0.466848039
R Square	0.217947092
Adjusted R Square	0.146851373
Standard Error	432605.9498
Observations	13

	Coefficients
Intercept	977182.6025
C	109.1589514

Q.3. OLS regression of A on D

Regression Statistics
Multiple R	0.678408
R Square	0.460237
Adjusted R Square	0.411168
Standard Error	359398.2
Observations	13

	Coefficients
Intercept	800753.1
D	4181.106

Q. 4 Best cost driver for the cost of purchasing department (A) is Number of Suppliers (D).

Q.5. The decision criteria is to select the OLS regression model having largest R square and Adjusted R Square values among all 3 models. Thus, the decision in Q.4. is reached. Thus, the model becomes -

A = 800753.1 + 4181.106*D

i.e. cost of purchasing dept. = 800753.1 + 4181.106*Number of Suppliers

Q.6. The fixed cost A is intercept term of the model, i.e. 800753.1 and the variable cost is slope of the model i.e. 4181.106

Q.7. 46% of the variation in A is explained by the cost driver (i.e. D) as observed by R-square of the model.