UW Statistics  is an integral part of a thriving ecosystem of scientific and business communities working together to create opportunities for achievement and solutions for a data-driven world.

Coming Seminars

May. 25th, 3:30 PM
Seminar presented by Peng Ding
Randomization is a basis for inferring treatment effects with minimal additional assumptions. Appropriately using covariates in randomized experiments will further yield more precise estimators. In his seminal work Design of Experiments, R. A. Fisher…

Technical Reports

Abstract: Statistical methods are developed for assessing the likelihood of prejudicial bias in agent-assigned permutations, such as the ordering of candidates on an election… more

This report shows how the descent of genome from an ancestor to currently observed descendants results in identity by descent (IBD) in current individuals, and hence similarities in their DNA at… more

A classification tree is a logical tree (in the computer science sense) that encodes an order of instructions used to sort a set of data into n classes. It is a rooted binary (directed-edge) tree… more

Recent News


Please join us as we celebrate and honor our graduate class of 2018 on Friday, June 8, 2018, 11:00 a.m. to 1:00 p.m. in the Haggett Hall Cascade Room.… more

Yen-Chi Chen, assistant professor in the Department of Statistics, helped astronomers identify how the oldest light in the Universe is distorted by the filaments in… more

Elena Erosheva (PI) and Carole Lee (co-PI) have been awarded a $260,000 grant from the National Science Foundation’s Science of Science Policy Program. Their project on “… more

Upcoming Courses

This course will introduce the basis on robust statistics. On top of modeling and theoretical aspects (in uence function, breaking point, depth, sensitivity curves, etc.), the course will cover some numerical optimization for implementing the introduced methods. Time permitting, each registered student will report on a topic of interest to her/him.
The first 3/4 of the course will concentrate on "classical" multivariate analysis, i.e, distribution theory and statistical inference based on the multivariate normal distribution. The last 1/4 will cover special topics of interest to the instructor and/or requested by the class. There will be several homework assignments. Time permitting, each registered student will report on a topic of interest to her/him.