Refer to Exercise 9.16 for the description of a solar panel company called New Age Solar and

Question:

Refer to Exercise 9.16 for the description of a solar panel company called New Age Solar and the Solar_Data worksheet.

a. Bin the Age and Income variables in the Solar_Data worksheet as follows. For Analytic Solver, choose the Equal count option and two bins for each of the two variables. For R, bin Age into [30, 50) and [50, 90) and Income into [30, 85) and [85, 140). What are the bin numbers for Age and Income of the first two observations?

b. Partition the transformed data and 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 results and evaluate the effectiveness of the naïve Bayes model.

Data from Exercises 9.16

New Age Solar sells and installs solar panels for residential homes. The company’s sales representatives contact and pay a personal visit to potential customers to present the benefits of installing solar panels. This high-touch approach works well as the customers feel that they receive personal services that meet their individual needs, but it is more expensive than other, mass-marketing approaches. The company wants to be very strategic about visiting potential customers who are more likely to install solar panels. The company has compiled a data set of past home visits by sales reps. The data include the age and annual income (in $1,000s) of the potential customer and whether or not the customer purchases the solar panels (Install: Y/N). A portion of the Solar_Data worksheet is shown in the accompanying table.