Table 9.1. Specifications For A Particular Toyota Corolla Variable Value Age_-08_-D4 77 KM 117,000 Fuel_Type Petrol HP 110 Automatic No Doors Quarterly_Tax 100 Mig_Guarantee No Guarantee_Period 3 Airco Yes Automatic_Airco No CD_Player No Powered_Windows No Sport_Model No Tow_Bar Yes Chapter 10: Logistic Regression Problem 10.1 Financial Condition of Banks. The file Banks.cav includes data on a sample of 20 banks. The 'Financial Condition" column records the judgment of an expert on the financial condition of each bank. This outcome variable takes one of two possible values- weak or strong-according to the financial condition of the bank. The predictors are two ratios used in the financial analysis of banks: TotLns&Lses/Assets is the ratio of total loans and leases to total assets and TotExp/Assets is the ratio of total expenses to total assets. The target is to use the two ratios for classifying the financial condition of a new bank. Run a logistic regression model (on the entire dataset) that models the status of a bank as a function of the two financial measures provided. Specify the success class as weak (this is similar to creating a dummy that is 1 for financially weak banks and 0 otherwise), and use the default cutoff value of 0.5. a. Write the estimated equation that associates the financial condition of a bank with its two predictors in three formats: i. The logit as a function of the predictors ii. The odds as a function of the predictors iii. The probability as a function of the predictors b. Consider a new bank whose total loans and leases/assets ratio = 0.6 and total expenses/assets ratio = 0.11. From your logistic regression model, estimate the following