Statistics

The central limit theorem started as a bar trick for 18th-century gamblers. Now scientists rely on it every day.

With lots of data, a strong model and statistical thinking, scientists can make predictions about all sorts of complex phenomena. Today, this practice is evolving to harness the power of machine learning and massive datasets. In this episode, co-host Steven Strogatz speaks with statistician Emmanuel Candès about black boxes, uncertainty and the power of inductive reasoning.

Across the social and biological sciences, statisticians use a technique that leverages randomness to deal with the unknown.

The French mathematician spent decades developing a set of tools now widely used for taming random processes.

Mathematicians are working to fully explain unusual behaviors uncovered using artificial intelligence.

Why does natural selection appear to happen slowly on long timescales and quickly on short ones? A multigenerational study of four lizard species addresses biology’s “paradox of stasis.”

Anesthesia is very different from sleep — which is why it offers unique opportunities for studying the human brain, says the physician-researcher and statistician Emery Brown.

Most modeling efforts during the COVID-19 pandemic have sought to address urgent practical concerns. But some groups aim to bolster the theoretical underpinnings of that work instead.

To the surprise of experts in the field, a postdoctoral statistician has solved one of the most important problems in high-dimensional convex geometry.