You perform a multiple linear regression analysis when you have more than one explanatory variable for consideration in your model. You can write the multiple linear regression equation for a model ...

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.

Regression analysis is a quantitative tool that is easy to use and can provide valuable information on financial analysis and forecasting.

Because much economic data has cycles, multiple trends and non-linearity, simple linear regression is often inappropriate for time-series work, according to Yale University. On the other hand ...

The purpose of this tutorial is to continue our exploration of regression by constructing linear models with two or more explanatory variables. This is an extension of Lesson 9. I will start with a ...

A new multivariate concept of quantile, based on a directional version of Koenker and Bassett's traditional regression quantiles, is introduced for multivariate location and multiple-output regression ...

First, multiple linear regression models are considered and the design matrices are allowed to be different. Second, the predictor variables are either unconstrained or constrained to finite intervals ...