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Chasing the Elusive Numbers That Define Epidemics
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.
Statistics Postdoc Tames Decades-Old Geometry Problem
To the surprise of experts in the field, a postdoctoral statistician has solved one of the most important problems in high-dimensional convex geometry.
The Grand Unified Theory of Rogue Waves
Rogue waves — enigmatic giants of the sea — were thought to be caused by two different mechanisms. But a new idea that borrows from the hinterlands of probability theory has the potential to predict them all.
New Turmoil Over Predicting the Effects of Genes
Promising efforts at disentangling the effects of genes and the environment on complicated traits may have been confounded by statistical problems.
How Network Math Can Help You Make Friends
Studying the structure of existing friendships in your community can help you forge the best connections when forming a new circle of friends.
A Revealer of Secrets in the Data of Life and the Universe
The statistician Donald Richards lives to uncover subtle patterns hiding in real-world data.
A Statistical Search for Genomic Truths
The computer scientist Barbara Engelhardt develops machine-learning models and methods to scour human genomes for the elusive causes and mechanisms of disease.
Scant Evidence of Power Laws Found in Real-World Networks
A new study challenges one of the most celebrated and controversial ideas in network science.
Why Math Is the Best Way to Make Sense of the World
To tell truth from fiction, start with quantitative thinking, argues the mathematician Rebecca Goldin.