In this week’s episode Greg and Patrick explore the extremely clever yet inexplicably underused method of dominance analysis which offers a set of techniques for determining the relative importance of predictors in a regression model. Along the way they also discuss giving compliments, looking tired, Indy vs. F1, chicken paprikás, Gustav Holst, Fozzie Bear, not […]
S6E20 Dominance Analysis Read More »
In this week’s episode Patrick and Greg talk about outcomes that are count variables: when you need to worry about them and what you can do about them within your analytical models. Along the way they also mention: Bela Lugosi, Vlad the Impaler, Patrick the Poker, Count Chocula, Count von Count, drunken bar brawls, secret
S6E18 Count Variables Read More »
In this weeks episode Greg and Patrick talk about loglinear models as a clever method to deconstruct the potential dependencies among two or more categorical variables. Along the way, they also discuss Children of the Corn, Mr. Magoo glasses, tighty whities, Fogo de Chão, blinded by hand soap, logarithms as drug mules, Euler Euler Euler,
S6E15 Loglinear Models: Someone Should Have Told You Read More »
In this week’s episode Greg and Patrick talk about group coding approaches, like dummy variables and effect code variables, for helping to analyze group differences within the larger general linear model. Along they way they also discuss hacking up a lung, made for audio faces, walking pneumonia, putting Vicks VapoRub on your feet, cards in
S6E13 Group Codes in GLM: Dummy and Dummier Read More »
In this week’s episode Greg and Patrick explore the fascinating world of suppressor variables which have the nearly magical, yet fully understandable, distinction of being unrelated to the dependent variable yet serving to enhance the predictive utility of other variables in the model. Along the way they also discuss getting the giggles, giving away our
S6E12 Suppression Unrepressed Read More »
In this week’s episode, Patrick and Greg play with some of the basics of probability in the context of some classic, fun, and often counterintuitive examples. Along the way they also discuss arguments with relatives, a feel for the roulette wheel, Xeroxing your butt, “The coin has spoken.”, Quantitude Booq Qlub, the Bellagio Fountains, Clooney
S5E18 Probability on Spring Break Read More »
In this week’s episode Greg and Patrick launch a new occasional series called Stuff You Should Know. The topic for today is regression to the mean: what the heck is it, how does it arise in every day life, and what can we do about it. Along the way they also discuss the space-time continuum,
S5E14 Regression to the Mean Read More »
In today’s episode Greg and Patrick talk about regularization, which includes ridge, LASSO, and elastic net procedures for variable selection within the general linear model and beyond. Along the way they also mention Bowdlerizing, The Family Shakespeare, disturbance in the force, McNeish on his bike, Spandex, C’mon guys wait up, the altar of unbiasedness, Curranizing, shooting arrows, stepwise
S5E09 Regularized Variable Selection Methods Read More »
In this week’s episode, Greg and Patrick talk about the terrifying, the feared, the dreaded … Multicollinearity. Blamed for a multitude of general linear model problems, they dare to ask the question: “But should it be?” Along the way they also mention: having your stump ground out, fall guys, Keyser Soze, croissants and breadsticks, baguettes
S5E02 Multicollinearity: The Usual Suspect Read More »
In the last episode of Season 4, Greg and Patrick discuss the very cool exploratory technique of cluster analysis — including concepts of multivariate distance, hierarchical and non-hierarchical methods, and how it differs from mixture models. Along the way they also mention: Scandinavian architects, raccoons on meth, vegetarian hotdogs, sh*t-ton of do-loops, free-range jam, statistical
S4E25 Cluster Analysis Read More »
