Using the Loans.csv file, build a logistic regression model to predict the “Good Risk” dependent variable (use family=binomial() in the glm function in R). In this column, ‘1’ indicates that making the loan is a good risk for the lender; ‘0’ indicates that making the loan is a bad risk. Make sure that you do not use the Applicant ID as an independent variable! You will need to load the MASS package in R by issuing library(MASS), before using the glm function to build your model. Show the creation of the model in your Word document.
In your Word document, document your logistic model’s output, and specifically explain which independent variables have the most predictive power and which have the least. Make sure you identify how you know, and explain why it matters.
Apply your logistic regression model to the data in Applications.csv to generate predictions of “Good Risk” for each loan applicant. If your glm model is stored in an R object called ‘LoanModel’, for example, and your Applications.csv data is in a frame called ‘Appl’, then you would issue a command that looks like this: LoanPredictions <- predict(LoanModel, Appl, type=“response”). Document the application of your model to the Applications data in your Word document.
In your Word document, interpret your predictions for the Applications.csv data. Specifically address the following:
How many loans do you predict to be a good risk for the lender?
How many are predicted to be a bad risk?
What are your highest and lowest post-probability percentages for predictions?
How many loans have at least a 75% post-probability percentage and what does that mean for the lender?
How many loans have less than a 25% post-probability percentage and what does that mean for the lender?
Suppose that the lender is willing to accept a little higher risk and has decided they will make loans to applicants who have post-probability percentages between 40% and 65%. List two things the lender could do to mitigate risk when lending to this group, and explain how these will help.
Make sure that you cite at least five supporting sources beyond the textbook in support of your writing and explanations. Cite correctly in APA format.
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