I need help with following questions. Models has been run for question 1 and 3.

East-West Airlines has entered into a partnership with the wireless phone company Telcon to sell the latter's service via direct mail. The file East-West-Airlines-sub.xls contains a subset of a data sample who has already received a test offer. About 13% accepted. You are asked to develop a model to classify East-West customers as to whether they purchase a wireless phone service contract (target variable Phone_sale), a model that can be used to predict classifications for additional customers.

1. Using XLMiner, run a neural net model on these data, using the option to normalize the data, setting the number of epochs at 3000, and requesting lift charts for both the training and validation data. Interpret the meaning (in business terms) of the left most bar of the validation lift chart (the bar chart).

2. Comment on the difference between the training and validation lift charts.

3. Run a second neural net model on the data, this time setting the number of epochs at 100. Comment now on the difference between this model and the model you ran earlier, and how overfitting might have affected results.

4. What sort of information, if any, is provided about the effects of the various variables?