Linear regression assumes a linear relationship, is sensitive to outliers, and may not perform well if the assumptions (like homoscedasticity or normality) are violated.

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

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

Journal of Applied Econometrics, Vol. 24, No. 4 (Jun. - Jul., 2009), pp. 651-674 (24 pages) We consider the problem of variable selection in linear regression models. Bayesian model averaging has ...

Learn how to graph linear regression in Excel. Use these steps to analyze the linear relationship between an independent and a dependent variable.