Assumptions in the model : There should be a linear relationship between dependent (response) variable and independent (predictor) variable(s). If we fit a linear model to a non-linear, the regression model would not capture the trend mathematically, thus resulting in an inefficient model. Also this will result in erroneous prediction on out of sample data There should be no relationship between the…
Category: Regression Analysis
Logistic Regression
INTRODUCTION : Logistic Regression is a regression analysis appropriate to use when dependent variable is dichotomous in nature i.e. binary (0 or 1). It is used when the variable is qualitative or probabilistic in nature. Example of usage for logistic regression – Predicting whether a claim for insurance will be raised or not based on factors like age of driver,…