In this week’s episode Greg and Patrick are honored to visit with Yi Feng, a quantitative methodologist at UCLA, as she helps them understand classification and regression tree analysis. She describes the various ways in which these models can be used, and how these can serve to inform both prediction and explanation. Along the way […]
S5E17 Classification and Regression Trees with Yi Feng Read More »
In this week’s episode Greg and Patrick talk all about Simpson’s Paradox: what it is, examples of where it occurs in real life, and why we might not really need to think about it as a paradox at all. Along the way they also discuss Apple Vision, The Simpsons predicting the future, sitting too close
S5E16 Simpson’s Paradox Read More »
In this week’s episode Greg and Patrick talk about confidence intervals: symmetric and asymmetric, asymptotic and bootstrapped, how to interpret them, and how not to interpret them. Along they way they also discuss tire pressure gauge mysteries, conference travel reimbursement, phases of the moon, gyroscopic effects, baseball walk-of-shame, why people hate us, settling out of
S5E13 The Confidence Interval’s Tale Read More »
In this week’s episode Greg and Patrick have great fun talking about meta-analysis with Paschal Sheeran, a social psychologist from the University of North Carolina at Chapel Hill. He describes what meta-analysis is, what it offers, and how to apply it in your own work. Along the way they also discuss taking off into the
S5E12 Meta-Analysis With Paschal Sheeran Read More »
In this week’s episode, marking the fifth Quantitude Holiday Celebration, Greg and Patrick argue about their favorite holiday movies, including whether Die Hard counts as one or not; they then proceed to discuss several statistical ideas that also seem to Die Hard. Along the way they talk about so much gibberish that we don’t even
S5E11 Statistical Ideas That Die Hard 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 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 »
In honor of April Fool’s Day, this week’s episode is about being fooled, specifically quantitative things that can fool you, accompanied by some classic songs about being fooled. Along the way, Greg and Patrick also discuss ukus, the spaghetti harvest, sucker!, meet the new boss, traditions of doing things wrong, naked garbage bag poker, old
S4E22 April Fools! The Quantitative Things That Fool Us Read More »
In this week’s episode Patrick and Greg discuss the dark art of using regression diagnostics to assess how well assumptions are met in the general linear model, with applications to the wide array of related techniques. Along the way they also mention Big Pharma, Merriam-Webster, free-radical opioids, baguettes, antisocial personality disorder, Elon Musk, yoinked, Trinity
S4E19 The Dark Art of Regression Diagnostics Read More »
In this week’s episode Greg and Patrick discuss variable transformations, both linear and non-linear, and explore the potential pros and cons of using these in applied research settings. Along the way the also discuss prank phone calls, English drama, rapping Dr. Seuss, persnickety estimation, weekly banana intake, it don’t make no never mind, Jeffry Bezos,
S4E17 Variable Transformations: Box-Cox, Fox in Socks Read More »
