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

Multiple linear regression (MLR) is a statistical technique that uses several explanatory variables to predict the outcome of a response variable.

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

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 ...

The problem of assessing influence and detecting influential cases in multiple linear regression with incomplete data is considered. A case is said to be influential if appreciable changes in fitted ...