Employee Sales_Success Experience Product_Type Region 1 1 1 1 1 20 21 2 3 1 3 1 3 4 0 1 2 4 5 122 1 60322 7 1 1 3 3 8 0 2 3 4 9 1 3 3 1 10 1 1 1 3 11 0 2 2 2 12 1 1 1 4 13 1 3 3 3 14 0 1 2 1 15 1 2 1 3 16 0 3 34 17 1 1 1 2 18 0 2 2 1 19 1 3 32 20 0 1 1 3 A dataset contains information on the number of successful sales calls (Sales_Success: 1 = Successful, 0 = Unsuccessful) made by employees at a marketing firm. The predictor variables are: years of experience (Experience: 1 = 0-2 years, 2 = 3-5 years, 3 = 6+ years), the type of product being sold (Product Type: 1 = Electronics, 2 = Clothing, 3 = Accessories), and the region in which the sales calls are made (Region: 1 = East, 2 = West, 3 = South, 4 = North). a. Create dummy variables for the Experience, Product Type, and Region categorical variables. b. Fit a logistic regression model to the data without interaction terms using the C. appropriate link function. Interpret the coefficients. Fit a logistic regression model to the data with interaction terms between all predictor variables using the appropriate link function. Interpret the coefficients. d. Perform a likelihood ratio test comparing the model with interaction terms to the model e. f. without interaction terms. Provide a conclusion based on the results. Calculate the deviance of the models and explain its significance. Check the significance of the models using appropriate statistical tests. Provide a conclusion based on the results.