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Regression Analysis: Columbia Drug Stores

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In five-to-seven pages of double-spaced writing in a Word document, answer the following questions:

1. Based on the text above, build a multiple linear regression population model to analyze the impact of the preceding determinants on Columbia's profitability. What is the multiple linear regression population equation? What are the assumptions underlying the model?
2. Using Excel and the accompanying dataset, estimate the population model. Copy and paste your Excel output into your Word document.
3. Based on the Excel output, what is the estimated regression equation?
4. Interpret all coefficient estimates. Identify the significance level for all of these estimates. Are any of the independent variables likely to actually influence Columbia's profitability? Are your estimates consistent or inconsistent with the a priori conjuncturesfound in the article? (E.g., advertising intensity is thought, a priori, to increase profit margin. Does your coefficient on advertising intensity and its associated p-value suggest
that it is directly correlated with profit margin?)
5. What portion of the variability in profit margin is explained by variability in the independent variables? Is the estimated regression equation a good fit for explaining profit margin?
6. Based on the estimate of the coefficient on Superstore Dummy and its associated p-value, do you believe that superstores pose a threat to Columbia's profitability? Expand on the theoretical foundation for this conclusion, i.e., why would the existence of competitor superstores affect Columbia's profitability?

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The solution provides a step by step method for the calculation of regression analysis. Formula for the calculation and interpretations of the results are also included.