Whereas linear regression only has one independent variable, multiple regression encompasses both linear and nonlinear regressions and incorporates multiple independent variables.

Discover how linear regression works, from simple to multiple linear regression, with step-by-step examples, graphs and real-world applications.

Nonlinear regression is a form of regression analysis in which data fit to a model is expressed as a mathematical function.

If the outcome variable is a continuous variable, linear regression is more suitable. The key difference between the two is that logistic regression uses a statistical function (the logistic or ...

Dr. James McCaffrey presents a complete end-to-end demonstration of linear regression using JavaScript. Linear regression is ...

Multiple and Non-Linear Regression The variable you are trying to estimate is referred to as dependent, while the variable you use in the model to predict the dependent variable is called independent.

Learn the difference between linear regression and multiple regression and how investors can use these types of statistical analysis.