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Statistical Sciences

Faculty List

Professors Emeriti 
D.F. Andrews, M Sc, Ph D 
A. Feuerverger, B Sc, Ph D 
D.A.S. Fraser, BA, Ph D, FRSC 
I. Guttman, MA, Ph D 
P. McDunnough, M Sc, Ph D 
R. Neal, B Sc, Ph D 
M.S. Srivastava, M Sc, Ph D 
A.M. Vukov, MA, ASA 

Professor and Chair of the Department 
R. Craiu, B Sc, Ph D 

Professor and Associate Chair, Graduate Studies 
Z. Zhou, B Sc, Ph D 

Assistant Professor, Teaching Stream and Associate Chair, Undergraduate Studies 
V. Zhang, B Sc, M Sc, FSA, ACIA, Actuarial Science

Associate Professor, Teaching Stream and Associate Chair, Undergraduate Studies 
B. White, Ph D, Statistics 

University Professor 
N.M. Reid, M Sc, Ph D, FRSC, OC 

Professors 
S. Broverman, B Sc, M Sc, Ph D, ASA
R. Craiu, B Sc, Ph D 
M.J. Evans, MA, Ph D (UTSC) 
S. Jaimungal, B Sc, M Sc, Ph D 
K. Knight, M Sc, Ph D 
X.S. Lin, M Sc, Ph D, ASA 
J. Quastel, MS, Ph D 
J.S. Rosenthal, MA, Ph D 
J. Stafford, M Sc, Ph D 
L. Sun, B Sc. Ph D 
B. Virag, Ph D (UTSC) 

Associate Professors 
A. Badescu, B Sc, M Sc, Ph D 
D. Brenner M Sc, Ph D 
P. Brown, BA, M Sc, Ph D 
L.J. Brunner, MA, Ph D (UTM) 
Z. Zhou, B Sc, Ph D 

Assistant Professors 
M. Alexander, B Sc, MA, MSR, Ph D 
F. Chevalier, B Sc, Ph D 
D. Duvenaud, B Sc, M Sc, Ph D
G. Eadie, B Sc, M Sc, Ph D 
M. Erdogdu, B Sc, M Sc, Ph D 
D. Kong, Ph D (UTM) 
D. Roy, B Sc, M Sc, Ph D (UTSC) 
S. Pesenti, B Sc, M Sc, Ph D 
D. Simpson, Ph D 
Q. Sun, Ph D 
S. Volgushev, Ph D 
L. Wang, B Sc, Ph D 
L. Wong, B Sc, M Sc, Ph D
Y. Zhang, B Sc, Ph D 

Professor, Teaching Stream
A. Gibbs, B Math, B Ed, M Sc, Ph D

Associate Professor, Teaching Stream 
N. Taback, B Sc, M Sc, Ph D 

Assistant Professors, Teaching Stream
E. Bolton, Ph D
K. Huynh Wong, B Sc, M Sc 
N. Moon, BSc, MA, Ph D 
S. Sue-Chee, B Sc, M Sc, Ph D 
V. Zhang, B Sc, M Sc, FSA, ACIA 

Introduction

Statistical Science is the science of learning from data.   Statistical science plays a large role in data science, which broadly encompasses computational and statistical aspects of managing and learning from large and complex datasets.  Statistical theory and methodology have applications in almost all areas of science, social science, public health, medicine, engineering, finance, technology, business, government and industry.   Statisticians and data scientists are involved in solving problems as diverse as understanding the health risk of climate change, predicting the path of forest fires, understanding the role of genetics in human health, and creating a better search engine.  New ways of collecting, organizing, visualizing, and analyzing data are increasingly driving progress in all fields and have created demand for people with data expertise.

The Department of Statistical Sciences offers specialist, major, and minor programs in Statistics and a specialist program in Data Science.  All programs offer training in statistical methods, theory, computation, and communication, as well as an understanding of the role of statistical science to solve problems in a variety of contexts. The specialist program in Statistical Science: Theory and Methods emphasizes probability and statistical theory as underlying mathematical frameworks for data analysis.  The specialist program in Statistical Science: Methods and Practice has greater emphasis on collaborative statistical practice. Students in this program combine their study in statistics with a focus in a discipline that relies on statistical methods.  The specialist program in Data Science is offered jointly with the Department of Computer Science.  Students in this program acquire expertise in statistical reasoning and methods, in the design and analysis of algorithms and data structures for handling big data, in best practices for software design, and in machine learning.   The major program in Statistics offers the most flexibility in choice of courses.  This program gives students a broad understanding of the methods and computational and communication skills appropriate for effective statistical problem solving.  The minor program in Statistics is designed to provide students with exposure and skills in advanced statistical methods. 

Enquiries: 100 St. George Street, Sidney Smith Hall, Room 6018 (416-978-3452) 

Associate Chair, Undergraduate Studies: Statistics - Associate Professor B. White; e-mail: ugchair.stats@utstat.utoronto.ca

Associate Chair, Undergraduate Studies: Actuarial Science - Professor V. Jiang; e-mail: ugchair.actsci@utstat.utoronto.ca