Welcome to the
Department of Statistical Sciences
at Wake Forest University
Mission Statement: The mission of the Department of Statistical Sciences is to educate students to become leaders and advocates for sound statistical reasoning, and to improve our society through innovative statistical and interdisciplinary research. To succeed in this mission, the Department will:
- Offer a premier undergraduate educational experience to Statistics, Applied Statistics and Mathematical Business majors, preparing each for successful careers as well as further graduate study.
- Offer a personalized Master’s program in Statistics, creating pathways into the field and opportunities for mentored research.
- Contribute to the advancement of the statistical sciences through peer-reviewed research and scientific collaborations across disciplines.
- Support the wider Wake Forest community with high quality general statistics education offerings.
- Colloquium: Flexible Regression Models for Dispersed Count DataFlexible 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 underdispersed relative to a Poisson model and, thus, are not conducive to […]
- Colloquium: Catalyzing the Causal Validation FlywheelTravis 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 verification will be featured. Causal Diagrams in R with ggdag: […]
- Colloquium: Merging uncertainty sets via majority voteMerging 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 K different algorithms on shared data — we address the […]
- Congratulations to Grad Students Mullan and WilesAshley 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 Department of Statistical Sciences Distinguished Teaching Assistant Award.
- Colloquium: What is a second-generation p-value, and why should you care?Jeffrey Blume, PhD, University of VirginiaZSR Auditorium. Tuesday, February 6th 11:00am Despite decades of controversy, p-values remain a popular tool for assessing when the data are incompatible with the null hypothesis. While it is widely recognized that p-values are imperfect, the consequences of ignoring their flaws remain elusive and p-values continue to flourish in the […]