In our article What is a large enough random sample? we pointed out that if you wanted to measure a proportion to an accuracy “a” with chance of being wrong of “d” then a idea was to guarantee you had a sample size of at least: This is the central […]

Estimated reading time: 7 minutes

We describe ergodic theory in modern notation accessible to interested computer scientists. The ergodic theorem (http://en.wikipedia.org/wiki/Ergodic theory (link)) is an important principle of recurrence and averaging in dynamical systems. However, there are some inconsistent uses of the term, much of the machinery is intended to work with deterministic dynamical systems […]

Estimated reading time: 58 seconds

Introduction To implement many numeric simulations you need a sophisticated source of instances of random variables. The question is: how do you generate them? The literature is full of algorithms requiring random samples as inputs or drivers (conditional random fields, Bayesian network models, particle filters and so on). The literature […]

Estimated reading time: 17 minutes

With the well deserved popularity of A/B testing computer scientists are finally becoming practicing statisticians. One part of experiment design that has always been particularly hard to teach is how to pick the size of your sample. The two points that are hard to communicate are that: The required sample […]

Estimated reading time: 18 minutes