In this assignment, imagine that you work for a company as a data mining expert. You are given a dataset called Default.csv (Links to an external site.) and the company requests that you analyze the data using classification. To this end, you will be using logistic regression analysis. Logistic regression has been one of the most popular binary classifiers that has been used in practice. Complete the following tasks using SAS Studio:
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- Provide the summary statistic as well as histograms for the variables balance and income for the whole dataset. Explain some of the key characteristics of the dataset.
- Using conditional statements on the variables default and student, provide the summary statistics (as well as histograms) for the variables balance and income for the different combinations of groups. That is, (1) default = Yes and student = Yes; (2) default = Yes, student = No; (3) default = No, student = Yes; and (4) default = No, student =No. Explain some of the key characteristics of the dataset.
- Using the variable default as the response variable, fit a logistic regression model with the predictor variables student, balance, and income. Comment on the output. What can you say about the significance of the predictor variables? How good is the model fit?
- Let’s assume a credit card applicant is a student with a balance of $621 and an income of $1850. How likely will he/she default according to the fitted logistic regression model? Explain and show calculations.
Include all relevant calculations and your answers to all items (1, 2, 3, and 4) in a Word document and submit the document to Canvas for grading. Clearly label all elements in your submission. In addition, provide a short description of any challenge(s) you faced during this assignment.