Why I think that the thirder position is fallacious.

A look into the relation between sample size and certainty, for binary outcomes.

Imagine that a correlation is found between a biomarker and the presence or absence of a disease. It is proposed that this be used for diagnosis. Can it always?

(Betteridge’s law of headlines applies.)

A few articles by Jaynes are now available on this website.

After our recent exploration of the pitfalls of confidence intervals, how about a little foray into the world of P-values?

Confidence intervals (CIs) are possibly one of the most misunderstood concepts in statistics, and that’s saying something.

CIs are one of many approaches to interval estimation: that is, having decided on a model that is thought to explain how the data that we are seeing are generated, how to compute an interval that represents our estimate for one of the model’s parameters, along with the uncertainty that we have about it?