Statistics

In sport, as in life, luck plays a role. For instance, in cricket, there is a toss at the start of the game. And the team that wins the toss wins the game 3% more often. The estimate of the advantage from winning the toss, however, is likely an underestimate

The mortality rate is puzzling to mortals. A better number is the expected number of years lost. (A yet better number would be quality-adjusted years lost.) To make it easier to calculate the expected years lost, Suriyan and I developed a Python package that uses the SSA actuarial data and

You may have heard that most published research is false (Ionnadis). But what you probably don’t know is that most corporate data science is also false. Gaurav Sood The returns on data science in most companies are likely sharply negative. There are a few reasons for that. First, as

The paper (pdf) makes the case that the primary reason for electoral cycles in dissents is priming. The paper notes three competing explanations: 1) caseload composition, 2) panel composition, and 3) volume of caseloads. And it “rules them out” by regressing case type, panel composition, and caseload on quarters from

Say that you want to predict wait times at restaurants using data with four columns: wait times (wait), the restaurant name (restaurant), time, and date of observation. Using the time and date of the observation, you create two additional columns: time of the day (tod) and day of the week

Forward Stepwise Regression (FSR) is hardly used today. That is mostly because regularization is a better way to think about variable selection. But part of the reason for its disuse is that FSR is a greedy optimization strategy with unstable paths. Jigger the data a little, and the search paths,

Say that you want to persuade a group of people to go out and vote. You can reach people by phone, mail, f2f, or email. And the cost of reaching out f2f > phone > mail > email. Your objective is to convert as many people as possible. How would

This is not a note about George Box’s quote about models. Neither is it about explainability. The first is trite. And the second is a mug’s game. Imagine the following: you get hundreds of emails a day, and someone must manually sort which emails are urgent and which