A mobile gaming company wants to study a group of its existing customers about their in-game purchases. A data set, a portion of which is shown in the accompanying table, is extracted and includes how old the customer is (Age), Sex (1 if female, 0 otherwise), the amount of weekly play time in hours (Hours), whether or not the customer’s mobile phone is linked to a Facebook account (Facebook = 1 if yes, 0 otherwise), and whether or not the customer has made an in-game purchase (Buy = 1 if yes, 0 otherwise).

 

a. Bin the Age and Hours variables as follows. For Analytic Solver, choose the Equal interval option and two bins for each of the two variables. For R, bin Age into [15, 40) and [40, 65) and Hours into [0, 20) and [20, 40). What are the bin numbers for Age and Hours for the first two observations? 

b. Partition the transformed data to develop a naïve Bayes classification model. Report the accuracy, sensitivity, specificity, and precision rates for the validation data set. 

c. Generate the ROC curve. What is the area under the ROC curve (or AUC value)? 

d. Interpret the performance measures and evaluate the effectiveness of the naïve Bayes model.

Transcribed Image Text:

Age 35 34 ⠀ 49 Sex 1 0 ⠀ 1 Hours 21 2 ⠀ 26 Facebook 0 1 : 1 Buy 1 1 : 1