All Greens is a franchise store that sells house plants and lawn and garden supplies. Although All

Question:

All Greens is a franchise store that sells house plants and lawn and garden supplies. Although All Greens is a franchise, each store is owned and managed by private individuals. Some friends have asked you to go into business with them to open a new All Greens store in the suburbs of San Diego. The national franchise headquarters sent you the following information at your request. These data are about 27 All Greens stores in California. Each of the 27 stores has been doing very well, and you would like to use the information to help set up your own new store. The variables for which we have data are

x₁ = annual net sales, in thousands of dollars

x₂ = number of square feet of floor display in store, in thousands of square feet

x₃ = value of store inventory, in thousands of dollars

x₄ = amount spent on local advertising, in thousands of dollars

x₅ = size of sales district, in thousands of families

x₆ = number of competing or similar stores in sales district

A sales district was defined to be the region within a 5-mile radius of an All Greens store.

(a) Generate summary statistics, including the mean and standard deviation of each variable. Compute the coefficient of variation (see Section 3.2) for each variable. Relative to its mean, which variable has the largest spread of data values? Which variable has the least spread of data values relative to its mean?

(b) For each pair of variables, generate the sample correlation coefficient r. For all pairs involving x,, compute the corresponding coefficient of determination r₂. Which variable has the greatest influence on annual net sales? Which variable has the least influence on annual net sales?

(c) Perform a regression analysis with x₁ as the response variable. Use x₂ x₃, x₄, x₅, and x₆ as explanatory variables. Look at the coefficient of multiple determination. What percentage of the variation in x₁ can be explained by the corresponding variations in x₂, x₃, x₄, x₅, and x₆ taken together?

(d) Write out the regression equation. If two new competing stores moved into the sales district but the other explanatory variables did not change, what would you expect for the corresponding change in annual net sales? Explain your answer. If you increased the local advertising by a thousand dollars but the other explanatory variables did not change. what would you expect for the corresponding change in annual net sales? Explain.

(e) Test each coefficient to determine if it is or is not zero. Use level of significance 5%.

(f) Suppose you and your business associates rent a store, get a bank loan to start up your business, and do a little research on the size of your sales district and the number of competing stores in the district. If x₂= 2.8. x₃= 250, x₄ = 3.l, x₅ = 7.3, and x₆ = 2, use a computer to forecast It = annual net sales and find an 80% confidence interval for your forecast (if your software produces prediction intervals).

(g) Construct a new regression model with x₄ as the response variable and x₁. x₂, x₃, x,, and r₆ as explanatory variables. Suppose an All Greens store in Sonoma. California. wants to estimate a range of advertising costs appropriate to its store. If ii spends too little on advertising, it will not reach enough customers. However, it does not want to overspend on advertising for this type and size of store. At this store, x₁ = 163. 12 = 2.4. x = 188, x = 6.6, and 16 = 10. Use these data to predictx₄ (advertising costs) and find an 80% confidence interval for your predict ion. At the 80% confidence level, what range of advertising costs do you think is appropriate for this store?