ISYS 5353 – Predictive Analytics
Exercise 3 – Logistic Regression
AssignmentTutorOnline
Financial Condition of Banks. The file “Banks.xls” 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 dependent 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 new banks.
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.
Write the estimated equation that associates the financial condition of a bank with its two predictors in three formats:
The logit as a function of the predictors.
The odds as a function of the predictors
The probability as a function of the predictors
Consider the following two banks:
Bank A: total loans and leases/assets ratio = 0.6, total expenses/assets ratio = 0.11
Bank B: total loans and leases/assets ratio = 0.56, total expenses/assets ratio = 0.10
From your logistic regression model, estimate the following three quantities for these banks: the logit, the odds, and the probability of being financially weak.
What is the classification of each bank ((Strong, Weak)? Which bank is stronger? Explain your logic.
Your assignment:
Download the file “Banks.csv” from Blackboard. Make sure to take note where the file is saved because this is the folder or path you will use to replace the red code below.
Run the following R code using R-Studio:
setwd(“C:YourPathYourFolder“)
bank.df <- read.csv(“banks.csv”)
reg<-glm(Financial.Condition ~ TotExp.Assets + TotLns.Lses.Assets,
data = bank.df, family = “binomial”)
summary(reg)
# these are the values for Bank A
logit <- c(1, 0.11, 0.6) %*% reg$coefficients
odds <- exp(logit)
prob <- 1/(1+odds)
# to do on your own on R …
# display (screen) the values of logit, odds and prob
# these are the values for Bank B
logit <- c(1, 0.10, 0.56) %*% reg$coefficients
odds <- exp(logit)
prob <- 1/(1+odds)
# to do on your own on R …
# display (screen) the values of logit, odds and prob
** Make sure to change the red code above to where you downloaded the “Banks.csv” file before running the code. This time you will have to little R coding on your own, see the blue code on top.
Take screenshots of the R-Studio Console after you run the code.
Answer questions a, b, and c on the scenario above. Make sure to use the results of the previous code you ran in R to answer the questions and please explain your answers (i.e., which part of the R code and results you used to respond).
Create a MS Word document to include ALL your answers (including screenshots) and submit utilizing the provided drop-box in Blackboard.
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