In a nutshell, this repo contains Exploratory Analysis of the churn phenomenon, Logistic Regression and Resampling Methods to assess the estimates goodness of the built model.
These were the original instruction of the project: what we are looking for The idea of the assignment is that you report your findings in a transparent way that can easily be verified/reproduced by others. The intended audience is your fellow students. They should be able to understand the code you write together with the explanations that you give for this code.
The following ingredients will be important when we evaluate your assignment:
- Start with a clear and transparent question.
- There are a lot of interesting economic questions for which you do not need programming to find the answer. However, as an important part of this course is programming in python, we want to see some programming. So choose a question where you can show off your programming skills!
- Briefly motivate why this question is interesting.
- Explain the method or data that you use to answer the question.
- Give the answer that you find (as a preview).
- Mention the main assumptions that you need to get this answer.
- When you use information, create a link to this information. The reader then only needs to click to find the relevant information.
- If you use data, present graphs of the data.
- Include the data in your github respository so that we can replicate your analysis.
- If you use equations, use latex to make them easy to read.
- Explain your code, the reader –think of your fellow students– must be able to easily follow what you are doing.
- Present a clear conclusion/answer to your question.
- Programming is great to do sensitivity analysis, just do the same you did before, but now with different parameter values.
- Include some discussion of what you find and elements on which you need additional information.