Logistic Regression (GLM) using Excel

In statistics, the logistic model is used to model the probability of a certain class or event existing such as pass/fail, win/lose, alive/dead or healthy/sick.
The zip contains 5 workbooks-
1. First sheet illustrates steps of Linear Regression and Logistic Regression. Pseudo-R2, NULL and Residual Deviance are calculated. It also shows parameter estimation and standard errors on the beta coefficients.
2. Second sheet demonstrates the concept of General Linear Modelling in Excel using 4 main link functions Normal, Poisson, Binomial, Gamma.
3. Third sheet shows detailed working of Multinomial Logit model in Excel. In the example used, the response variable (Y) has 3 values which the Model tries to predict.
4. Fourth sheet shows detailed working of Logistic regression where the response variable Y is an ordered category (e.g. Grade A, B, C)
5. Fifth sheet shows Application of Logit & Probit to Probability of Default calculation.