Analytics Ninja and the Curse of Multicollinearity

Analytics Ninja and the Curse of Multicollinearity
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  • Analytics Ninja and The Curse of Multicollinearity
  • Starring Data Monger
  • Starring Analytics Ninja
  • Far far away in a distant office cubical, Data Monger's rants can be heard yet again!
  • Well, I have these predictor variables with large P valuesgenerating highly questionable results. I just don’t know how to pick the bestpredictor for this model and it’s driving me crazy.
  • Holy Pie! These two predictors have large P values and they seem to be highly correlated. This cannot happen to me…I need to get the first iteration of this model out ASAP, or I am gonna lose this project.
  • Somewhere in the core, Analytics Ninja can hear the call for help!
  • I wish Analytics Ninja could come help!
  • Meanwhile Analytics Ninja: Help is on its way my friend!
  • NOPE !
  • OK DM, this is phenomenon is called Multicollinearity. Fortunately,it can be taken care of by looking at VIF statistics of call the predictorvariables. Have you heard of any of this?
  • What seems to be the problem, DM?
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