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 ...

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 ...

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

Methods to determine the validity of regression models include comparison of model predictions and coefficients with theory, collection of new data to check model predictions, comparison of results ...

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