Run the regression model you developed and interpret the

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Reference no: EM13582206

Sapphire Coffee:

Jennie Garcia could not believe that her career had moved so far so fast. When she left graduate school with a master's degree in anthropology, she intended to work at a local coffee shop until something else came along that was more related to her academic background. But after a few months, she came to enjoy the business, and in a little over a year she was promoted to store manager. When the company for whom she worked continued to grow, Jennie was given oversight of a few stores.

Now, eight years after she started as a barista, Jennie is in charge of operations and planning for the company's southern region. As a part of her responsibilities, Jennie tracks store revenues and forecasts coffee demand. Historically, Sapphire Coffee would base its demand forecast on the number of stores, believing that each store sold approximately the same amount of coffee. This approach seemed to work well when the company had shops of similar size and layout, but as the company grew, stores became more varied. Now, some stores have drive-thru windows, a feature that top management added to some stores believing that it would increase coffee sales for customers who wanted a cup of coffee on their way to work but who were too rushed to park and enter the store.

Jennie noticed that weekly sales seemed to be more variable across stores in her region and was wondering what, if anything might explain the differences. The company's financial vice president had also noticed the increased differences in sales across the stores and was wondering what might be happening. In an e-mail to Jennie he stated that weekly store sales are expected to average $5.00 per square foot. Thus, a 1,000-square-foot store would have average weekly sales of $5,000. He asked that Jennie analyze the stores in her region to see if this rule of thumb was a reliable measure of a store's performance.

Jennie had been in the business long enough to know that a store's size, although an important factor, was not the only thing that might influence sales. She had never been convinced of the efficacy of the drive-thru window, believing that it detracted from the coffee house experience that so many of Sapphire Coffee customers had come to expect. The VP of finance was expecting the analysis to be completed by the weekend. Jennie decided to randomly select weekly sales records for 53 stores, along with each store's size, whether it was located close to a college, and whether it had a drive-thru window.

1. Identify the primary issue of the case

2. Identify a statistical model you might use to help analyze the case

3. Develop a multiple regression model for Jennie. Be sure to carefully specify the dependent and independent variables.

4. Discuss how the drive-thru and college can be included in the regression model

5. Run the regression model you developed and interpret the results

6. Which variables are significant

7. Provide a short report that describes your analysis and explains in management terms the findings of your model. Be sure to explain which variables, if any, are significant explanatory variables. Provide a recommendation to management.

Reference no: EM13582206

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