In: Finance
Davis Stores sells clothing in 15 stores located around the southwestern United States. The managers at Davis are considering expanding by opening new stores and are interested in estimating costs in potential new locations. They believe that costs are driven in large part by store volume measured by revenue. During a discussion, one of the managers suggests that number of employees might be better at explaining cost than store revenues. As a result of that suggestion, managers collected the following information from last year’s operations (revenues and costs in thousands of dollars):
Store | Costs | Employees | Revenues |
101 | $2,323 | 40 | $5,881 |
102 | 1,926 | 25 | 4,424 |
103 | 2,941 | 28 | 6,983 |
104 | 2,728 | 37 | 6,937 |
105 | 2,497 | 49 | 5,322 |
106 | 5,206 | 50 | 3,339 |
107 | 2,924 | 44 | 4,807 |
108 | 3,168 | 40 | 2,829 |
109 | 2,775 | 28 | 4,709 |
110 | 5,917 | 57 | 4,640 |
111 | 2,452 | 32 | 3,806 |
112 | 3,128 | 28 | 5,005 |
113 | 3,282 | 37 | 3,298 |
114 | 4,880 | 42 | 4,910 |
115 | 5,157 | 54 | 4,889 |
d-1. Enter the regression coefficients.
d-2. Estimate the cost of a store with 42 employees using the results from a simple regression of store cost on employees.
Enter the regression coefficients. (Round your answers to 2 decimal places. Negative amounts should be indicated by a minus sign.)
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Estimate the cost of a store with 42 employees using the results from a simple regression of store cost on employees. (Round your intermediate calculations and final answer to 2 decimal places.)
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The summary of the regression is shown below. Your questions have been addressed subsequently.
SUMMARY OUTPUT | ||||||||
Regression Statistics | ||||||||
Multiple R | 0.729124426 | |||||||
R Square | 0.531622429 | |||||||
Adjusted R Square | 0.495593385 | |||||||
Standard Error | 876.7669739 | |||||||
Observations | 15 | |||||||
ANOVA | ||||||||
df | SS | MS | F | Significance F | ||||
Regression | 1 | 11342765 | 11342764.69 | 14.75538541 | 0.00204102 | |||
Residual | 13 | 9993364.2 | 768720.3265 | |||||
Total | 14 | 21336129 | ||||||
Coefficients | Standard Error | t Stat | P-value | Lower 95% | Upper 95% | Lower 95.0% | Upper 95.0% | |
Intercept | -101.598197 | 944.38262 | -0.107581603 | 0.915970216 | -2141.812812 | 1938.616419 | -2141.8128 | 1938.6164 |
X Variable 1 | 89.38743308 | 23.270257 | 3.84127393 | 0.00204102 | 39.11509838 | 139.6597678 | 39.1150984 | 139.65977 |
Part d - 1 Enter the regression coefficients. (Round your answers to 2 decimal places. Negative amounts should be indicated by a minus sign.)
Intercept | -101.60 |
Employees | 89.39 |
Part d - 2
Estimate the cost of a store with 42 employees using the results from a simple regression of store cost on employees. (Round your intermediate calculations and final answer to 2 decimal places.)
Cost = Intercept + Coefficient x Employees = - 101.60 + 89.39 x 42 = $ 3,652.67