- Please Solve This In Rstudio Thank You 1 (46.78 KiB) Viewed 46 times
please solve this in rstudio, thank you
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answerhappygod
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please solve this in rstudio, thank you
please solve this in rstudio, thank you
Question 1 (100 pts) Telecommunications companies providing cell phone service are interested in customer retention. In particular, identifying customers who are about to churn (cancel their service) is potentially worth millions of dollars if the company can proactively address the reason that customer is considering cancellation and retain the customer. The datafile is called Cellphone.csv and it contains n=3,333 customer data to be used to classify a customer as a churner or not. (a) Using GGPlot, provide a bar chart for how Monthly charge is distributed by Churn Status. Comment on what you see. (b) Create a model in where you are predicting whether a customer will Churn vs not Churn when you consider: Accountweeks, Contract Renewal, Data Plan, Data Usage, Customer Service Calls, Day Minutes, Day calls, Monthly Charge, Overage Fee, and Roaming Minutes as the independent variables in the model. (i) Discuss the model's Pseudo R^2, (ii) Interpret the significant predictors by outputting Odds Ratios, Confidence Intervals, and your interpretation of each. (iii) Run the analysis in Excel and include the main results from excel n the knitted documented,
Question 1 (100 pts) Telecommunications companies providing cell phone service are interested in customer retention. In particular, identifying customers who are about to churn (cancel their service) is potentially worth millions of dollars if the company can proactively address the reason that customer is considering cancellation and retain the customer. The datafile is called Cellphone.csv and it contains n=3,333 customer data to be used to classify a customer as a churner or not. (a) Using GGPlot, provide a bar chart for how Monthly charge is distributed by Churn Status. Comment on what you see. (b) Create a model in where you are predicting whether a customer will Churn vs not Churn when you consider: Accountweeks, Contract Renewal, Data Plan, Data Usage, Customer Service Calls, Day Minutes, Day calls, Monthly Charge, Overage Fee, and Roaming Minutes as the independent variables in the model. (i) Discuss the model's Pseudo R^2, (ii) Interpret the significant predictors by outputting Odds Ratios, Confidence Intervals, and your interpretation of each. (iii) Run the analysis in Excel and include the main results from excel n the knitted documented,
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