2014 - 2015

2015 Mar 04

BCASA Talk: Matthew Tom

7:00pm to 8:30pm

Location: 

The Alumni Room, Wheelock College, 200 The Fenway
Gambling and Statistics: Beyond the Games Registration required for presentation (free)
2015 Mar 10

ResearchStats: Frederick Phoa

12:00pm to 1:00pm

Location: 

Science Center Rm. 705
A Swarm Intelligence Based (SIB) Optimization Method for Design of Experiments (more information)
2014 Sep 30

ResearchStats: Jun Zhang

12:00pm to 1:00pm

Location: 

Science Center Rm. 705
Jun Zhang Information Geometry: From Divergence Functions to Geometric Structures
2015 Mar 24

AstroStatTalk: Gwendolyn Eadie

1:00pm to 3:00pm

Location: 

Science Center Rm. 706
Bayesian Mass Estimates of the Galaxy: Incorporating Incomplete Data
2014 Oct 06

BrownCSSem: David Meltzer

3:30pm to 5:00pm

Location: 

Room 245, 121 South Main Street, Providence
Redesign of Care for Patients at High Risk of Hospitalization in a Reforming U.S. Healthcare System: Rationale for a CMMI Innovation Challenge Project
2015 Mar 25

CMSA Talk: Peter Qian

4:00pm to 5:00pm

Location: 

Science Center Lecture Hall A
Title: Some Statistical Aspects of Uncertainty Quantification Abstract: Computer simulations, such as computational fluid dynamics, finite element analysis, agent-based models and multi-physics codes, are widely used in science, engineering and business for studying complex phenomena. As simulation models are never perfect and possess various uncertainties, including random initial condition and boundary conditions, input uncertainty and model discrepancy, uncertainty quantification (UQ) plays a big role in simulation-based decision-making. Without a rigorous mathematical framework for UQ in... Read more about CMSA Talk: Peter Qian
2014 Oct 27

Stat Colloq: Sudipto Banerjee

4:15pm to 5:15pm

Location: 

Science Center Rm. 705
On Gaussian Process Models for High-Dimensional Geostatistical Datasets
2014 Oct 23

SEAS CS: Emma Brunskill

4:00pm to 5:15pm

Location: 

Maxwell Dworkin G115
Interactive ML for People: The Small Data Problem
2015 Apr 14

ResearchStats: David Jones

12:00pm to 1:00pm

Location: 

Science Center Rm. 705
Designing Test Information and Test Information in Design
2015 May 05

ResearchStats: Jiannan Lu

12:00pm to 1:00pm

Location: 

Science Center Rm. 705
Bounding causal effects for ordinal outcomes: partial identification and objective inference We consider the problem of causal inference for ordinal outcomes, in which the estimands are often unidentifiable. Instead of invoking strong modeling assumptions, we take the objective approach of partial identification and derive closed form expressions for the sharp bounds of various estimands. Our results are assumption free, scientifically meaningful and extremely easy to compute and interpret. We illustrate our results through simulation studies and a real data example.

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