From the course: Machine Learning & AI Foundations: Linear Regression

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Collinearity diagnostics

Collinearity diagnostics - SPSS Tutorial

From the course: Machine Learning & AI Foundations: Linear Regression

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Collinearity diagnostics

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- [Instructor] Okay, we've seen repeated evidence that there is multicollinearity in the waste data set. It's time for us to formally request multicollinearity diagnostics and take a look, so I'm going to go to analyze, regression, linear, and I'm gonna declare waste tons as my dependent, and all of the variables as my independent. Now, I'm going to go into the statistics sub-menu, and request collinearity diagnostics as well as part and partial correlations. I don't need R squared change because I'm not doing hierarchical. I don't need Durbin-Watson, but I do need confidence intervals. I am not going to request any additional output like partial plots and residuals plots because I've already reviewed that in earlier steps. I'm gonna go ahead and click on OK. Now I'm gonna go to the, now I'm going to open the output window. And what I'm gonna be focused on is this table right here. So I'm gonna go ahead and put this in a separate window. Now if you look up collinearity diagnostics…

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