University of Southeastern Philippines
eBA 201 Managerial Statistics
Exercise 6.3 – Multiple Correlation and Regression Analysis
Name: Nathan Kit A. Berro
Instruction: Use SPSS or Excel or any other Statistical software to run the data
The district sales manager for a major automobile manufacturer is studying car sales.
Specifically, he would like to determine what factors affect the number of cars sold at a dealership.
To investigate, he randomly selects 14 dealers and obtains data on the number of cars sold last
quarter, the minutes of radio advertising purchased last quarter, the number of full-time salespeople
employed in the dealership, and whether or not the dealer is located in the city (1 if city, 0 if not).
The data are as follows:
No. of CarsAdvertising Sales ForceLocation No. of CarsAdvertising Sales ForceLocation
sold, Y X1 X2 X3 sold, Y X1 X2 X3
150 20 11 1 170 30 15 1
127 18 10 0 161 25 14 1
138 15 15 1 180 26 17 0
159 22 14 1 102 15 7 1
144 23 13 0 163 24 16 1
139 17 12 1 106 18 10 0
128 16 12 0 149 25 11 1
a. Develop a correlation matrix. Which independent variable has the strongest correlation
with the dependent variable? Is there any multicollinearity problem?
The independent variable which has the strongest relation to the dependent variable is the
variable X2 = .8523 which is the Salesforce. This could mean that the Salesforce is the
major factor that affects the cars being sold. However, the data suggest that there is no
multicollinearity as there is insufficient strong relation among two independent variables.
eBA 201 Managerial Statistics
Exercise 6.3 – Multiple Correlation and Regression Analysis
Name: Nathan Kit A. Berro
Instruction: Use SPSS or Excel or any other Statistical software to run the data
The district sales manager for a major automobile manufacturer is studying car sales.
Specifically, he would like to determine what factors affect the number of cars sold at a dealership.
To investigate, he randomly selects 14 dealers and obtains data on the number of cars sold last
quarter, the minutes of radio advertising purchased last quarter, the number of full-time salespeople
employed in the dealership, and whether or not the dealer is located in the city (1 if city, 0 if not).
The data are as follows:
No. of CarsAdvertising Sales ForceLocation No. of CarsAdvertising Sales ForceLocation
sold, Y X1 X2 X3 sold, Y X1 X2 X3
150 20 11 1 170 30 15 1
127 18 10 0 161 25 14 1
138 15 15 1 180 26 17 0
159 22 14 1 102 15 7 1
144 23 13 0 163 24 16 1
139 17 12 1 106 18 10 0
128 16 12 0 149 25 11 1
a. Develop a correlation matrix. Which independent variable has the strongest correlation
with the dependent variable? Is there any multicollinearity problem?
The independent variable which has the strongest relation to the dependent variable is the
variable X2 = .8523 which is the Salesforce. This could mean that the Salesforce is the
major factor that affects the cars being sold. However, the data suggest that there is no
multicollinearity as there is insufficient strong relation among two independent variables.
