Acquire an understanding of the concepts surrounding 'collinearity'. Appreciate the indications and symptoms of collinearity in multivariable regression. Become aware of the available diagnostic tools ...

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 ...

Researchers encountering wrong signs on regression coefficients are inclined to blame their variable list rather than measurement error. It is generally assumed that ...

Linear regression is a powerful and long-established statistical tool that is commonly used across applied sciences, economics and many other fields. Linear regression considers the relationship ...

It's easy to run a regression in Excel. The output contains a ton of information but you only need to understand a few key data points to make sense of your regression. You need the Analysis Toolpak ...

Model choice is usually an inevitable source of uncertainty in model-based statistical analyses. While the focus of model choice was traditionally on methods for choosing a single model, methods to ...

Troy Segal is an editor and writer. She has 20+ years of experience covering personal finance, wealth management, and business news. Eric's career includes extensive work in both public and corporate ...

When you perform regression analysis in Microsoft Excel, you are engaging in a statistical process that helps you understand the relationship between variables. This technique is particularly useful ...