PLEASE HELP - DATA MINING PROBLEM! MULTIPLE LINEAR REGRESSION

C. To fit a predictive model for SPENDING:

i. Partition the 1000 records into training and validation sets.

ii. Run a multiple linear regression model for SPENDING versus all six predictors. Give the estimated predictive equation.

iii. Based on this model, what type of purchaser is most likely to spend a large amount of money?

iv. If we used backward elimination to reduce the number of predictors, which predictor would be dropped first from the model?

v. Show how the prediction and the prediction error are computed for the first purchase in the validation set.

vi. Evaluate the predictive accuracy of the model by examining its performance on the validation set.

vii. Create a histogram of the model residuals. Do they appear to follow a normal distribution? How does this affect the predictive performance of the model?

TO ACCESS THE DATA SET, CLICK ON THIS LINK:

https://www.dropbox.com/s/8wlhu8d14c88w4i/6.2_Tayko_DataSet.xls?dl=0

PLEASE USE EXCEL MINER TO SOLVE THIS

6.2 Predicting Software Reselling Profits. Tayko Software is a software catalog firm that sells games and educational software. It started out as a software manufacturer and then added third-party titles to its offerings. It recently revised its collection of items in a new catalog, which it mailed out to its customers. This mailing yielded 1000 purchases. Based on these data, Tayko wants to devise a model for predicting the spending amount that a purchasing customer will yield. The file Tayko.xls contains information on 1000 purchases. Table 242 6.4 describes the variables to be used in the problem (the Excel file contains additional variables) TABLE 6.4 DESCRIPTION OF VARIABLES FOR TAYKO SOFTWARE EXAMPLE FREQ LAST UPDATENumber of days since last update to customer record WEB Number of transactions in the preceding year Whether customer purchased by Web order at least GENDER ADDRESS RES ADDRESS US SPENDING (response) once Male or female Whether it is a residential address Whether it is a U.S. address Amount spent by customer in test mailing (in dollars) 6.2 Predicting Software Reselling Profits. Tayko Software is a software catalog firm that sells games and educational software. It started out as a software manufacturer and then added third-party titles to its offerings. It recently revised its collection of items in a new catalog, which it mailed out to its customers. This mailing yielded 1000 purchases. Based on these data, Tayko wants to devise a model for predicting the spending amount that a purchasing customer will yield. The file Tayko.xls contains information on 1000 purchases. Table 242 6.4 describes the variables to be used in the problem (the Excel file contains additional variables) TABLE 6.4 DESCRIPTION OF VARIABLES FOR TAYKO SOFTWARE EXAMPLE FREQ LAST UPDATENumber of days since last update to customer record WEB Number of transactions in the preceding year Whether customer purchased by Web order at least GENDER ADDRESS RES ADDRESS US SPENDING (response) once Male or female Whether it is a residential address Whether it is a U.S. address Amount spent by customer in test mailing (in dollars)