Use the dataset “Tayko-known.xls” for the following problems.

(a) Perform a multiple linear regression. Specify appropriate independent and response variables. Report the resulting equation. (Hint: this duplicates an illustration in the chapter.)

(b) Calculate, or locate in your regression output, the following statistics, and use them in a sentence or two describing the Tayko-known data and your regression. The goal is to convey to your reader an understanding of average spending, how variable it is, and how much a typical prediction might be in error.

– standard deviation of the spending

– mean spending

– RMSE

(c) Use the regression equation to predict spending levels for the customer records in “Tayko-Unknown.xls.”

(d) Sort the results in #3 by predicted spending, and report the top 10 customers for predicted spending.

(e) Your goal is to generate at least $250 in spending per catalog mailed. How many customers should you mail to, from Tayko-unknown.xls? (Hint: would you mail a catalog to the customer represented by the top row in part (d)? The second row? The last row?

Note: (b) and (c) do not require statistical software and can be done in both StatCrunch and Excel. StatCrunch will calculate the RMSE (Root MSE) automatically with a regression equation.