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Sporty Inc., a regional chain of sporting goods stores, wants to investigate why some of their stores in university towns have higher sales than other stores. Accordingly, they randomly sampled stores nationwide and collected information on yearly sales (\$1000s), yearly advertising expenditures (\$1000s), number of students at the university, and distance from the university (miles) (see attached data).

Explain in managerial terms how the above variables impact sales.

How much of the variation in sales can you explain?

What recommendations would you make to Three Guys, Inc.?

Three Guys, Inc. is considering opening a store 15 miles from a university that has 12,000 students, and plans to spend \$2,000/month on advertising. What level of annual sales should they expect?

Three Guys, Inc. is also considering opening a store two miles from a university that has 4,500 students, and plans to spend \$250/month on advertising. What level of annual sales should they expect?

Solution Summary

The solution discusses Sporty Inc., a regional chain of sporting goods stores, wants to investigate why some of their stores in university towns have higher sales than other stores. Accordingly, they randomly sampled stores nationwide and collected information on yearly sales (\$1000s), yearly advertising expenditures (\$1000s), number of students at the university, and distance from the university (miles) (see attached data).

Explain in managerial terms how the above variables impact sales.

How much of the variation in sales can you explain?

What recommendations would you make to Three Guys, Inc.?

Three Guys, Inc. is considering opening a store 15 miles from a university that has 12,000 students, and plans to spend \$2,000/month on advertising. What level of annual sales should they expect?

Three Guys, Inc. is also considering opening a store two miles from a university that has 4,500 students, and plans to spend \$250/month on advertising. What level of annual sales should they expect?

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1.Explain in managerial terms how the above variables impact sales.

We regress Sales on the other three variables: advertising expenditures, number of students, and distance. Using OLS, we get the following result.

Coefficients Coefficients Std. Error t Sig.
(Constant) 74.14003 69.165 1.072 0.289
Advertising Expenditures (\$1000s) 0.90349 1.418 0.637 0.527
Number of Students 0.00962 0.003 3.118 0.003
Distance (miles) -5.60373 2.809 -1.995 0.052
l Note: the t-value of "Number of Students" is statistically significant (>2.0), and the t-value of the distance variable is barely significant.
l The manager can expect high correlation between sales and Number of Students and distance from the university, but not the Advertising Expenditures. So it is not ...

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