Course Listings: Summer Term 2019

Course Enrolment

Please read through this information carefully if you are planning to enrol in a graduate course at the Department of Statistical Sciences.

Enrolment Dates

Students from the University of Toronto Mississauga (UTM) and University of Toronto Scarborough (UTSC) can enrol in Arts & Science courses starting Wed, April 17 at 6:00 a.m. Students from the Downtown Toronto Campus (St. George) can enrol in Arts & Science courses offered at UTM and UTSC on the same date.

If you have any questions regarding enrolment dates for our graduate courses, please contact our graduate administrator. 


Start and End Dates of Classes & Final Examination Period

Section Code

Classes Start

Classes End

Final Examination

F May 6, 2019 June 14, 2019 June 19-26, 2019
Y May 6, 2019 August 12, 2019 August 15-22, 2019
S July 2, 2019 August 12, 2019 August 15-22, 2019


For dates regarding university closures or course drop deadlines, please have a look at the School of Graduate Studies sessional dates calendar.


Course List Legend

  • F = a half-year course in the first term (September – December)
  • S = a half-year course in the second term (January– April)
  • Y = a full-year course (September – April)
  • (J) indicates a a cross-listed course (a joint graduate/undergraduate course)
  • M = Monday
  • T = Tuesday
  • W = Wednesday
  • R = Thursday
  • F = Friday
  • L0101 or L0201 = 9:00 am to 5:00 pm
  • L5101 = 5:00 pm onwards


2019 Summer Term Course Listings

You can also find a list of graduate courses at the School of Graduate Studies page for our department.


Title (click for description)


Section / Time



STA1001H/STA302H1  F

L0101 / T 2-5

L5101/ MW 6-9


MC 102

MC 102




Guowen Huang



Analysis of variance for one-and two-way layouts, logistic regression, loglinear models, longitudinal data, introduction to time series.

Prerequisite: STA1001H or equivalent

S  L0101 / MW 9-12 ES 1050 Alex Stringer

Design of surveys, sources of bias, randomized response surveys. Techniques of sampling; stratification, clustering, unequal probability selection. Sampling inference, estimates of population mean and variances, ratio estimation., observational data; correlation vs. causation, missing data, sources of bias.

Exclusion: STA322H1

Prerequisite: ECO220Y1/ECO227Y1/GGR270Y1 / PSY202H1/SOC300Y1/STA221H1/STA255H1/261H1/248H1

F  L0101 / TR 2-5 ES 1050 Dragan Banjevic

This cross-listed course covers a number of topics used in the design and analysis of experiments. The course is intended for students of statistics as well as students of other disciplines (eg. engineering, experimental science, etc.) who will use experimental design and analysis in their work.

The course will cover the following topics: randomization, blocking Latin squares, balanced incomplete block designs, factorial experiments, confounding and fractional replication, components of variance, orthogonal polynomials, response surface methods. Additional topics will be covered based on students’ interest as time permits.

Prerequisite: STA302H/352Y/ECO327Y/ECO357Y or permission of instructor

S Please note, this course has been cancelled!

An overview of methods and problems in the analysis of time series data. Topics include: descriptive methods, filtering and adjustment, spectral estimation, bivariate time series models.

The course will cover the following topics:

  • Theory of stationary processes, linear processes
  • Elements of inference in time domain with applications
  • Spectral representation of stationary processes
  • Elements of inference in frequency domain with applications
  • Theory of prediction (forecasting) with applications > ARMA processes, inference and forecasting
  • Non-stationarity and seasonality, ARIMA and SARIMA processes

Further topics, time permitting: multivariate models; GARCH models; state-space models

F L5101 / MW 6-9 ES 1050 Jen-Wen Lin