Statistical Sciences ColloquiumDr. Mostafa Shams Teacher-Scholar Postdoctoral FellowWake Forest University Bayesian nonparametric regression models for insurance claims data 8 Oct. 11AM, ZSR Auditorium (Room 404) We often want to model insurance claims as a function of covariates, which leads to a regression problem. Parametric regression […]
Statistical Sciences ColloquiumDr. Mitchell Paukner, Assistant Professor of Biostatistics Wake Forest University Information Under the Curve: A Modern Approach to Leveraging Area Under Curves in Survival Analysis 24 Sept. — ZSR Auditorium (Room 404) In this talk, I will discuss several different methods I have […]
Our students have been busy this summer! A few of them were kind enough to share some highlights from their summer experiences. Bukola Emi-Johnson (MS Student in Statistics) 💼 This summer, Bukola worked for Syngenta, one of the world’s leading agricultural companies, as an IT […]
Applied Statistics: Abby Draeger In addition to completing her major in applied statistics, Draeger also completed a minor in computer science and mathematics. When about how she managed to complete such an ambitious workload, she smiled. Full article. Statistics: Hanna Vaidya Determined to pursue statistics, […]
Education, Collaboration, Leadership: It’s What We Do Leslie McClure, PhDDean, College for Public Health and Social Justice, St Louis UniversityBiotech Auditorium Room 151; Tuesday, April 16th 4:00pm The Merriam-Webster Dictionary defines a statistician as: “one versed in or engaged in compiling statistics.” However, the role […]
Flexible Regression Models for Dispersed CountData Kimberly Sellers, NC State University ZSR Auditorium, Tuesday, March 26th 11:00am Poisson regression is a popular tool for modeling count data and is applied in a vast array of disciplines. Real data, however, are often over- or under-dispersed relative […]
Travis Gerke, The Prostate Cancer Clinical Trials ConsortiumMalcolm Barrett, Stanford University ZSR Auditorium, Thursday, March 7th 12:30pm This talk will provide a high-level overview of causal diagrams and discuss current challenges with causal AI. An emerging software platform that enables collaborative human-in-the-loop causal identification and […]
Merging uncertainty sets via majority voteAaditya Ramdas, PhD, Carnegie Mellon UniversityTuesday, February 276h 11:00am Given K uncertainty sets that are arbitrarily dependent – for example, confidence intervals for an unknown parameter obtained with K different estimators, or prediction sets obtained via conformal prediction based on […]
Ashley Mullan has been selected by the Department of Statistical Sciences as the recipient of the Graduate Student Award for Outstanding Scholarship in the Statistical Sciences for 2024. Melita Wiles has been selected by the Department of Statistical Sciences as the recipient of the 2024 […]