Peter Christie joined the Statistical Training department at SAS in 2008 as a course developer and instructor. Prior to SAS, he worked in the entertainment, retail, banking, and pharmaceutical industries. He earned an MBA from the University of North Carolina at Chapel Hill. His areas of interest include data mining, business analytics and predictive modeling. When not working with customers, Peter is either in training for a marathon or playing in a 10 piece Jazz band.
My oh my… It makes me happy to see that most of our blog readers have been very good this year. You know, the elves have been especially busy keeping track of predicting the probability that you will be naughty or nice. This really cuts down on the last minute
Fasten your seat belts - it's time to put the pedal to the metal. In this segment, we're going to burn rubber and unleash the full fury of the advanced RPM model on the unsuspecting burglary data! We will pop the hood and take a sneak peek at the drive
So… what ‘cha gonna do? Use it or Peruse it? SAS Rapid Predictive Modeler (RPM) cranks out models like nobody’s business, and like the academy awards presentation will just “give you the envelope please." If your data is super clean, this might work beautifully for your non mission-critical models. If
Did you ever wonder why one place is more likely to experience burglaries than another? Maybe you want to move to a new neighborhood and make sure it has as much going for it as possible before you load up the truck. I found some data at the University of
