Regression Analysis with a Minitab output
Assume that your company owns multiple retail outlets in cities across the United States. You conduct a study to determine if daily sales levels (in hundreds of dollars) can be predicted by the number of competitors that are located within a one-mile radius of each location and city population (in thousands of people). Therefore, the dependent variable is SALES and the two independent variables are NUMBER OF COMPETITORS and CITY POPULATION. Your research team utilized Minitab software to create a Regression model. The results are shown below.
Regression Analysis: SALES vs. NUMBER OF COMPETITORS, CITY POPULATION
Analysis of Variance
Source |
DF |
Adj SS |
Adj MS |
F-Value |
|
Regression |
2 |
160.362 |
80.181 |
15.93 |
|
NUMBER OF COMPETITORS |
1 |
138.093 |
138.093 |
27.43 |
|
CITY POPULATION |
1 |
2.576 |
2.576 |
0.51 |
|
Error |
7 |
35.238 |
5.034 |
||
Total |
9 |
195.600 |
Model Summary
S |
R-sq |
||
2.24365 |
81.98% |
Coefficients
Term |
Coef |
SE Coef |
T-Value |
P-Value |
VIF |
NUMBER OF COMPETITORS |
-3.245 |
0.620 |
-5.24 |
0.001 |
1.07 |
CITY POPULATION |
0.0174 |
0.0243 |
0.72 |
0.498 |
1.07 |
Regression Equation
SALES |
= |
38.21 - 3.245 NUMBER OF COMPETITORS + 0.0174 CITY POPULATION |
Study this output then answer the following questions:
R-Square value: 81.98% of the total variation in the explanatory variables in the regression model.
The p-value of number of competitors is 0.001< 0.05 hence the variable is significant
The p-value of city population is 0.498 > 0.05 hence the variable is not significant
Which independent variable is the most significant? number of competitors
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