Required Tasks:
Identify the major issues (two) of the case.
Briefly summarize the data (include an explanation of the results of descriptive statistics of the data, variables included, how the data was collected, and any pertinent information about the data available in the case study)
Develop a scatter plot of the variables store size vs. weekly sales. Identify the dependent variable. Briefly describe the relationship between the two variables. Students must include the scatter plot in their report.
Fit a linear regression equation to the data.
Please note, consistent with the emphasis on understanding, interpretation, and application of statistical results in this course, the results of fitting a regression based on the data has been provided below. Students are encouraged to try to reproduce these results for their own benefit and to gain additional insight.
In your report explain the method by which such a regression table is obtained.
In your report, explain whether the variable store size is statistically significant in explaining the amount of the variation in weekly sales?
Include in your report, and based on the estimated regression equation, an explanation of whether it appears that the $5.00 per square foot weekly sales expectation the company currently uses is a valid one.
Comment on any other statistically and practically significant values in the results table (for example R-square, F-statistic and P-value, etc.)
Summarize your analyses and findings in a report which may also include any practical recommendation(s) for the attention of the company’s vice president of finance.
Excel output.