Math & Stats Events: 2021 - 2022

 

Math/Stat Table  

Every Monday from 12:00 - 1:30 pm 
Science Center Living Room - common area on the first floor of the Science Center 

Math/Stat Table is an informal social time for students and
faculty to get together and chat. There's no need to be majoring in Mathematics or
Statistics; all are welcome. Please join us any time between noon and 1:30
pm on Mondays. 


Information Session for Prospective Statistics Majors

Thinking about majoring in Statistics?  Come chat with the department's faculty, and get your questions answered!

Monday, October 25th, 7:00 -8:00 pm, Science Center, E110 - Lipton Lecture Hall


Information Sessions for Prospective Math Majors

Thinking about majoring in Mathematics?  Come chat with the department's faculty, and get your questions answered!

Monday, October 25th, 4:30 - 5:30 pm, SMUD 207

Wednesday, October 27th 5:30-6:30 via Zoom: https://amherstcollege.zoom.us/j/94084130024?pwd=d3ZkK3BxT2xuQzJEMGlPejVoNDRJZz09
Meeting ID: 940 8413 0024
Passcode: 188161

Thursday, October 28, 4:30-5:30 pm, SMUD 207


Amherst College Statistics and Data Science Colloquium 
Thursday, October 28th, 4:00pm ET - VIRTUAL

Using Electronic Health Records and Phenome-wide Association Studies for COVID-19 Research

Register in advance for this webinar: 
 
Electronic Health Records linked with other auxiliary data sources hold tremendous potential for conducting real time actionable research. However, one has to answer two fundamental questions before conducting inference: "Who is in my study?" and "What is the target population of Inference?".  Without accounting for selection bias one can quickly produce fast but inaccurate conclusions. In this talk, I will discuss large-scale association studies  across multiple phenotypes, namely Phenome-wide association studies (PheWAS) that have gained traction in the genetics and medical informatics world.  I will present several applications of this tool in genetics, cancer and for identifying risk factors for COVID-19 hospitalization and mortality. I will further discuss a statistical framework for jointly considering selection bias and phenotype misclassification in such analyses. This is joint work with Lars Fritsche, Lauren Beesley and Maxwell Salvatore at the University of Michigan School of Public Health.
Bhramar Mukherjee
Bhramar Mukherjee, John D Kalbfleisch Collegiate Professor of Biostatistics and Chair of Biostatistics
Professor of Epidemiology
Professor of Global Public Health
School of Public Health, University of Michigan.

Title: TBD

Professor Nicholas Reich
Department of Biostatistics
University of Massachusetts/Amherst