Logistic regression is a powerful statistical method that is used to model the probability that a set of explanatory (independent or predictor) variables predict data in an outcome (dependent or ...

Linear regression is a statistical method used to understand the relationship between an outcome variable and one or more explanatory variables. It works by fitting a regression line through the ...

Estimating Coefficients and Predicting Values The equation y = mx +b represents the most basic linear regression equation: x is the predictor or independent variable y is the dependent variable or ...

Logistic regression is a technique used to make predictions in situations where the item to predict can take one of just two possible values. For example, you might want to predict the credit ...

The Data Science Lab How to Do Multi-Class Logistic Regression Using C# Dr. James McCaffrey of Microsoft Research uses a full code program, examples and graphics to explain multi-class logistic ...

Dimitris Bertsimas, Angela King, Logistic Regression: From Art to Science, Statistical Science, Vol. 32, No. 3 (August 2017), pp. 367-384 ...

Peiming Wang, Martin L. Puterman, Mixed Logistic Regression Models, Journal of Agricultural, Biological, and Environmental Statistics, Vol. 3, No. 2 (Jun., 1998), pp ...

In this module, we will introduce generalized linear models (GLMs) through the study of binomial data. In particular, we will motivate the need for GLMs; introduce the binomial regression model, ...

Amy Gallo is a contributing editor at Harvard Business Review, a cohost of the Women at Work podcast, and the author of Getting Along: How to Work with Anyone (Even Difficult People) (Harvard ...