Developing a Model that Predicts Churn In this assignment, you will use this data set of approximately 7,000 customers who subscribe to a Telecom service Download data set of approximately 7,000 customers who subscribe to a Telecom service. Your challenge is to develop a model that estimates the probability of churn for each customer. Ultimately, marketing actions could then be taken to connect with customers that the model estimates have a high probability of churning. Here are some steps you will want to follow: Observe the data set in Excel and review the potential independent variables (customer behaviors and characteristics) and the dependent variable (churn). Use pivot tables in Excel to analyze basic, descriptive relationships between independent variables and our dependent variable (churn -- you can use "churn flag" in the data set). Your presentation should display and describe some of the relationships you find by using pivot tables and exploring relationships in the data. Load the data set into SPSS by either importing it or just cutting and pasting into the SPSS Data field. Run a binary logistic regression using your independent variables and your one dependent variable (churn flag) using SPSS. Preparing Your Presentation Analyze the results and prepare a short presentation (fewer than 10 slides or 7 pages) with the following sections: Objectives: Describe the purpose of your work Data & Methodology: Briefly describe your data source and your methods Findings: Show your Key Findings (not all your findings, just what you consider important) and provide commentary and analysis Recommendations: What marketing actions should be taken based on your findings. Because you'll want to both show and describe your results, a presentation format using Google Slides or Microsoft PowerPoint will be the easiest way to present your results