- Faculty List
**Professors Emeriti**

D.F. Andrews, MSc, PhD

S. Broverman, BSc, MSc, PhD, ASA

A. Feuerverger, BSc, PhD

D.A.S. Fraser, BA, PhD, FRSC

I. Guttman, MA, PhD

P. McDunnough, MSc, PhD

R. Neal, BSc, PhD

M.S. Srivastava, MSc, PhD

A.M. Vukov, MA, ASA**Professor and Chair of the Department**

M.J. Evans, MA, PhD**Associate Professor and Associate Chair, Graduate Studies**

S. Volgushev, PhD**Associate Professor, Teaching Stream and Associate Chair, Undergraduate Studies - Actuarial Science**

V. Zhang, BSc, MSc, FSA, ACIA, Actuarial Science**Professor, Teaching Stream and Associate Chair, Undergraduate Studies - Statistics**

N. Taback, BSc, MSc, PhD**University Professor**

N.M. Reid, MSc, PhD, FRSC, OC**Professors**

A. Badescu, BSc, MSc, PhD

R. Craiu, BSc, PhD

S. Jaimungal, BSc, MSc, PhD

K. Knight, MSc, PhD

X.S. Lin, MSc, PhD, ASA

J.S. Rosenthal, MA, PhD

J. Stafford, MSc, PhD

L. Strug, BA, BSc, Sc M, PhD

L. Sun, BSc, PhD

B. Virag, PhD (UTSC)

Z. Zhou, BSc, PhD**Associate Professors**

D. Brenner, MSc, PhD

L.J. Brunner, MA, PhD (UTM)

D. Duvenaud, BSc, MSc, PhD

M. Franklin, BSc, MSc, PhD

D. Kong, PhD (UTM)

D. Roy, BSc, MSc, PhD (UTSC)

Q. Sun, PhD

P. Zwiernik, MSc, PhD**Assistant Professors**

M. Alexander, BSc, MA, MSR, PhD

R. Alexander, BE, PhD

B. Babic, BA, JD, MS, PhD

M. Bing, BS, MFE, MSc, PhD

F. Chevalier, BSc, PhD

G. Eadie, BSc, MSc, PhD

M. Erdogdu, BSc, MSc, PhD

J. Gronsbell, BA, PhD

V. Leos Barajas, BSc, PhD

C. Maddison, MSc, PhD

W. Mou, BSc, B. Econ., PhD

J. Y. Park, BA, PhD

S. Pesenti, BSc, MSc, PhD

X. Shi, BSc, MSc, PhD

J. Speagle, BA, MA, PhD

E. Tuzhilina, MSc, PhD

L. Wang, BSc, PhD

L. Wong, BSc, MSc, PhD

Y. Zhang, BSc, PhD**Professor, Teaching Stream**

A. Gibbs, B Math, BEd, MSc, PhD**Associate Professor, Teaching Stream**

B. White, BSc, M Math, PhD, Statistics - Biostatistics**Assistant Professors, Teaching Stream**

S. Caetano, BSc, MSc, PhD

K. Daignault, BSc, MSc

K. Huynh Wong, BSc, MSc

M. Moon, BSc, MSc

N. Moon, BSc, MA, PhD

S. Schwartz, BA, BS, MSc, PhD

## 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 and a specialist and a major program in Actuarial Science (please refer to the Actuarial Science section of the academic calendar for more information on Actuarial Science programs). All Statistics 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 the 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 some exposure and skills in statistical methods which is intended to complement programs in other disciplines that involve quantitative research.

Enquiries: 700 University Avenue, 9th Floor, Ontario Power Building (416-978-3452)

Associate Chair, Undergraduate Studies: Statistics - Associate Professor, Teaching Stream N. Taback; email: ugchair.statistics@utoronto.ca

Associate Chair, Undergraduate Studies: Actuarial Science - Associate Professor, Teaching Stream V. Zhang; email: ugchair.actsci@utoronto.ca

## Arts & Science Internship Program

Starting Fall 2021, the new Arts & Science Internship Program (ASIP) stream is available to students who are entering Year 2 or Year 3 of study and enrolled in the Data Science Specialist, the Specialist in Statistical Science: Methods and Practice, and the Specialist in Statistical Science: Theory and Methods programs.

- Enrolment is limited and requires a supplemental application. Students enrolled in the ASIP stream will be required to complete mandatory Professional Development programming plus a minimum of 12 and maximum of 20 months (Year 2 entry) or a minimum of 12 and maximum of 16 months (Year 3 entry) of paid, full-time work experience. The time to degree completion for students enrolled in ASIP will normally be 5 years. There is an additional cost to participate in the ASIP stream.
- Students will typically be admitted to the ASIP stream for the Fall term of Year 2 of study, however, in exceptional circumstances students, including transfer students, who enrolled in an eligible program in the Summer after Year 2 can be admitted to the ASIP stream for the Fall of Year 3. Acceptance into an ASIP stream in Year 3 is dependent on space and requires approval of the student’s academic unit and the Faculty of Arts & Science Experiential Learning & Outreach Support (ELOS) Office. Please refer to the ASIP eligibility page for further details.
- Further details about ASIP, including eligibility requirements and application procedures, can be found here. Students may also visit the ASIP webpage or contact the ELOS office at asip@utoronto.ca.