Automated multiple regression model-building techniques often hide important aspects of data from the data analyst. Such features as nonlinearity, collinearity, outliers, and points with high leverage ...

Linear regression is a type of data analysis that considers the linear relationship between a dependent variable and one or more independent variables.

Comparing regression coefficients between models when one model is nested within another is of great practical interest when two explanations of a given phenomenon are specified as linear models. The ...

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