Linear regression is a type of data analysis that considers the linear relationship between a dependent variable and one or more independent variables. It is typically used to visually show the ...

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

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

When multiple variables are associated with a response, the interpretation of a prediction equation is seldom simple.

The statistical literature and folklore contain many methods for handling missing explanatory variable data in multiple linear regression. One such approach is to incorporate into the regression model ...

2. Multiple Linear Regression Multiple Linear Regression is a method for predicting one outcome variable by considering the combined influence of two or more predictor variables.

As in Excel, we can manually remove explanatory variables one-by-one until we have a model in which all the explanatory variables are significant. This is the essence of data-driven (versus theory ...

Multiple Linear Regression In linear regression, when there's just a single independent variable, the analysis is sometimes called simple linear regression to distinguish the analysis from situations ...