DEPARTMENT OF STATISTICS

Working Groups

Statistical Methods in the Social Sciences

Adviser: Larry Hedges

Points of Contact: Sarah Peko-Spicer, Jake Schauer

About: The Statistical Methods in the Social Sciences working group meets biweekly to learn about methodological advances with applications in social and public policy. Areas of active research include replication, adaptive interventions, and single-case designs. 

Upcoming meetings dates and topics:

• January 28 – Graphical Representations of Record Linkage
• February 11 – Robust Variance Estimation
• February 25 – Design Comparable Effect Sizes in Single Case Designs
• March 11 – Causal Inference & Data Integration
• April 8 – Generalizability & Meta-Analysis
• April 22 – TBA
• May 6 – Missing Data Methods in Meta-Analysis
• May 13
• May 20
• June 3
• June 10

All meetings are 11:00am-12:00pm in 2006 Sheridan Rd, room B02

Bayesian Statistics & Machine Learning

Points of Contact: Tsz Kit (Tim) Lau

About: The Bayesian Statistics & Machine Learning working group meets weekly to learn about the essence of Bayesian statistics and machine learning (particularly, Bayesian machine learning). We study both its theory and practice to address the need of modern statistical machine learning. Refer to the webpage (https://github.com/timlautk/bayesian-stat-machine-learning) of the working group for details.