This is the final project for the class IDS 702 - Modeling and Data Representation

In Vehicle Coupon Recommendation

For this project I have used logistic regression to model the odds of a driver accepting a coupon based on a wide range of characteristics. The goal of the project is to identify important characteristics that are associated with, and affect a driver's decision to accept a coupon and quantify these relationships.

Based on the final regression model we observe that most variables in the dataset have an impact on the odds. Specifically, variables such as gender, coupon, weather, expiration have noticeably large effects. However, we must ponder on the validity of the inferences given a few limitations of the data.

Please refer to the report and presentation for more detailed approach and findings