Option 1 Classification using Logistic Regression 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 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

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Option #1 Classification using Logistic Regression In this assignment, imagine that you work for a company as a data mining expert. You are given a

Option #1Classification using Logistic Regression

In this assignment, imagine that you work for a company as a data mining expert. You are given a dataset calledDefault.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:

Using conditional statements on the variables default and student, provide the summary statistics (as well as histograms) for the variablesbalanceandincomefor 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 variabledefaultas the response variable, fit a logistic regression model with the predictor variablesstudent,balance, andincome. 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.