Recent Posts

Have you got a ruler handy? Fantastic! Then hold out your right hand, extend your thumb and little finger as far as they’ll go, and measure the distance in centimeters, rounding to the nearest half centimeter.

This is the second in a series of posts about how to construct a confidence interval for a proportion. (Simple problems sometimes turn out to be surprisingly complicated in practice!

Back in November a colleague pointed me to a website describing the recent COVID-19 Student Vaccination Survey carried out by my employer, the University of Oxford. At the time I briefly tweeted my concerns at the University: Sorry @UniofOxford, but this is wildly misleading.

Computing is a crucial part of modern applied and theoretical econometrics but most economists, myself included, have little if any formal training numerical analysis and computer science. This means that we often learn things the hard way: by making boneheaded mistakes and spending hours browsing stackoverflow to try to figure out what went wrong.

In a previous post I showed an example in which the “textbook” confidence interval for a proportion performs poorly despite a fairly large sample size. My aim in that post was to convince you that the oft-repeated advice concerning \(n > 30\) and the central limit theorem is worthless.