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 ...

Multiple Regression You can create multiple regression models quickly using the fit variables dialog. You can use diagnostic plots to assess the validity of the models and identify potential outliers ...

This is a preview. Log in through your library . Abstract By utilizing the multiple regression technique, this paper examines whether various measures of public policies have significant effect in ...

Multiple regression models with survey data Regression becomes a more useful tool when researchers want to look at multiple factors simultaneously. If we want to know whether the racial divide ...