Multiple linear regression should be used when multiple independent variables determine the outcome of a single dependent variable. This is often the case when forecasting more complex relationships.

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

The simplest form of regression in Python is, well, simple linear regression. With simple linear regression, you're trying to ...

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.

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

One common problem in the use of multiple linear or logistic regression when analysing clinical data is the occurrence of explanatory variables (covariates) which are not independent, ie ...

Leo A. Goodman, A Modified Multiple Regression Approach to the Analysis of Dichotomous Variables, American Sociological Review, Vol. 37, No. 1 (Feb., 1972), pp. 28-46 ...

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