Nature magazine reports “‘One-size-fits-all’ threshold for P values under fire: Scientists hit back at a proposal to make it tougher to call findings statistically significant.” Researchers are at odds over when to […]
Free Data Science Class: Predictive Case Study 1, Part VI
Review! This class is neither frequentist nor Bayesian nor machine learning in theory. It is pure probability, and unlike any other class available. And for the right price! Last time we completed […]
Bayesian Statistics Isn’t What You Think
Back to our Edge series. Sean Carroll says Bayes’s Theorem should be better known. He outlines the theorem in the familiar updating-prior-belief formula. But, as this modified classic article shows, this is […]
Statistical Models CANNOT Show Cause, But EVERYBODY Thinks They Can. Hence the Replication CRISIS
Please pass this on to ANY researcher who uses statistics. Pretty please. With sugar on top. Like I say below, it’s far far far far far past time to cease using statistics […]
The Bayesian Metaphor Can Do More Harm Than Good: Update
Quoting from a post on vampires, “In Bayesian inference, you start with some initial beliefs (called ‘Bayesian priors’ or just ‘priors’), and then you ‘update’ them as you receive new evidence.” This […]
The Gambler’s Fallacy Proves Classical Statistics (Frequentist & Bayes) Fails
Everybody who’s anybody—which makes, as we’ll see, a lot of nobodies—knows the gambler’s fallacy. Gambler watches the roulette wheel come up red six times running and says to himself, “Black is due.” […]
Number 1 Book In Epistemology & In Logic! Get It While It’s Hot!
It’s probably gone by now, but for a little while my new book, Uncertainty: The Soul of Modeling, Probability & Statistics, was “#1 New Release in Epistemology” then “#1 New Release in […]
Uncertainty (#1 New Release in Statistics) Book Page — Here Are The Details. Update!
This isn’t the book page. This is. Or you can buy it here. The page is permanently located at the menu bar at the top of the page, at the far left. […]
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