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Question 2: Logistic Regression Model (Use trainData for thi…

Question 2: Logistic Regression Model (Use trainData for this question)  (13 points) a. i) (2 points) Create a logistic regression model using “Fraudulent” as response variable and “Account_Age_Days” and “International_Transaction” as predicting variables. Call it model1. Display the summary of the model.   ii) (2 points) Interpret the coefficient of “Account_Age_Days” for model1 with respect to the log-odds and odds of the response.   iii) ( 2 points) What does the value of intercept represent in terms of baseline fraud probability? b i. (2 points) Using the “trainData” dataset, create a logistic regression model using “Fraudulent” as response variable and all variables in “trainData” as predictors (call it model2) and display the summary of model2.  ii. ( 2points) What does the summary of model2 suggests about the likelihood of fraud for international transactions compared to domestic transactions? iii. ( 3 points) What do the null and residual deviance indicate in the summary of the model.  Based on the null and residual deviance values, how well does this model fit the data? What does the change in deviance indicate? Use alpha level of 0.01.  

We apply a classification model and obtain the estimated cla…

We apply a classification model and obtain the estimated classification provided in the table, which also provides the observed classification. Use the following table contrasting the estimated versus the observed classification for questions 15-20:     Estimated Classification YES NO Observed Classification YES 105 228 NO 40 9627