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Courses of Instruction in Statistics in the Faculty of Arts and Science
AVAILABILITY
The Department of Mathematics and Statistics does not offer all of the courses listed in the Calendar every year. For the most up-to-date information on the availability of courses offered in the current year, check QCARD or consult with the departmental office, web site, or an academic adviser.

PREREQUISITES
In all cases, stated course prerequisites are suggested guidelines meant to indicate the type and level of background that will be assumed in the course. A student lacking the stated prerequisite or equivalent should consult the instructor before registration.
 STAT-263*/0.5 Introduction to Statistics 3L
A basic course in statistical methods with the necessary probability included. Topics include probability models, random variables, distributions, estimation, hypothesis testing, elementary nonparametric methods. May not be taken concurrently with or subsequently to STAT 269*.
Also offered as a distance course. Consult Continuing and Distance Studies.
PREREQUISITE    An Ontario 4U mathematics course or equivalent.
EXCLUSIONS    COMM 162*; ECON 250*; PSYC 202*; SOCY 211*; STAT 261*, STAT 267*, STAT 367*.
 STAT-268*/0.5 Statistics and Probability I 3L;1T
Basic ideas of probability theory such as random experiments, probabilities, random variables, expected values, independent events, joint distributions, conditional expectations, moment generating functions. Main results of probability theory including Chebyshev’s inequality, law of large numbers, central limit theorem. Introduction to statistical computing. PREREQUISITE    One of MATH 120, MATH 121, MATH 124*, MATH 126.
EXCLUSIONS    STAT 251*, STAT 351*.
 STAT-269*/0.5 Statistics and Probability II 3L;1T
Basic techniques of statistical estimation such as best unbiased estimates, moment estimates, maximum likelihood. Bayesian methods. Hypotheses testing. Classical distributions such as the t-distribution, F-distribution, beta distribution. These methods will be illustrated by simple linear regression. Statistical computing.
PREREQUISITES    MATH 221* or MATH 280*; STAT 268*; or permission of the Department.
EXCLUSION    STAT 261*.
 STAT-351*/0.5 Probability I 3L;1T
Basic probability theory; conditioning; densities, expectation; jointly distributed random variables, transformations, generating functions, limit laws. Distributions: binomial, Poisson, hypergeometric, uniform, exponential,  gamma, normal, bivariate normal. Elementary random processes.
COREQUISITE    MATH 221* or MATH 280*.
EXCLUSIONS    STAT 251*, STAT 268*, STAT 356*.
 STAT-353*/0.5 Probability II 3L;1T
Intermediate probability theory as a basis for further study in mathematical statistics and stochastic processes; probability measures, expectations; modes of convergence of sequences of random variables; conditional expectations; independent systems of random variables; Gaussian systems; characteristic functions; Law of large numbers, Central limit theory; some notions of dependence. PREREQUISITES    STAT 251* or STAT 269* or STAT 351*; MATH 110 or MATH 111 or MATH 112*, MATH 281*.
 STAT-361*/0.5 Applied Methods in Statistics I 3L;1T
A detailed study of simple and multiple linear regression, residuals and model adequacy. The least squares solution for the general linear regression model. Analysis of variance for regression and simple designed experiments; analysis of categorical data. Sample surveys: basic principles and methodology; random sampling, stratified sampling, ratio and regression estimates. PREREQUISITES    A course in linear algebra; one of STAT 251*, STAT 269*, STAT 351*, STAT 356*; one of STAT 261*, STAT 263*, STAT 267*, STAT 367*, or permission of the Department.
EXCLUSION    ECON 351*.
 STAT-455*/0.5 Stochastic Processes and Applications 3L;1T
Markov chains, birth and death processes, random walk problems, elementary renewal theory, Markov processes, Brownian motion and Poisson processes, queuing theory, branching processes. Given jointly with STAT 855*. PREREQUISITE    STAT 353*, or one of STAT 251*, STAT 269*, STAT 351* with permission of the Department.
 STAT-460*/0.5 Survey Sampling 3L
A course in applied statistics with topics to include: planning a survey, questionnaire design, concepts in sampling from a finite population, simple random sampling, stratified sampling, cluster and systematic sampling, introduction to multi-phase and multi-stage surveys, sampling with unequal probabilities, sampling with replacement, and design based estimation. Given jointly with STAT 867*. PREREQUISITE    STAT 261* or STAT 269*; or any of MATH 120, MATH 121, MATH 124*, MATH 126 or APSC 172 and STAT 263* with a mark of at least 80 per cent; or EPID 813*.
 STAT-462*/0.5 Computational Data Analysis 2L;2P
An introduction to computer software consistent with modern professional practice of statistics. Use of the statistical package SAS and S-PLUS. Given jointly with STAT 862*.
COREQUISITE    STAT 361* or ECON 351* or permission of the Department.
 STAT-463*/0.5 Fundamentals of Statistical Inference 3L;1T
Decision theory and Bayesian inference; principles of optimal statistical procedures; maximum likelihood principle; large sample theory for maximum likelihood estimates; principles of hypotheses testing and the Neyman-Pearson theory; generalized likelihood ratio tests; the chi-square, t, F and other distributions.
PREREQUISITES    STAT 269* (or STAT 251* and STAT 261*). STAT 353* is recommended.
EXCLUSION    STAT 363*.
 STAT-464*/0.5 Discrete Time Series Analysis 3L
Autocorrelation and autocovariance, stationarity; ARIMA models; model identification and forecasting; spectral analysis. Applications to biological, physical and economic data. PREREQUISITE    STAT 361* or ECON 351* or permission of the Department.
 STAT-465*/0.5 Quality Management 3L
An overview of the statistical and lean manufacturing tools and techniques used in the measurement and improvement of quality in business, government and industry today. Topics include management and planning tools, Six Sigma approach, statistical process charting, process capability analysis, measurement system analysis and factorial and fractional factorial design of experiments. PREREQUISITE    One of STAT 261*, STAT 263*, STAT 267*, STAT 269*, STAT 367*. Students with a different statistics background should obtain approval of the Department.
 STAT-471*/0.5 Design and Analysis of Experiments 3L
Analysis of variance for fixed, random and mixed models; analysis of covariance; distribution of mean squares; fractional factorial experiments, Latin squares and split plot designs. Modern topics such as Taguchi methods and designs for nonlinear models. Offered jointly with STAT 871*. PREREQUISITE    STAT 361* or permission of the Department.
 STAT-473*/0.5 Generalized Linear Models 3L
An introduction to advanced regression methods for binary, categorical, and count data. Major topics include maximum-likelihood method, binomial and Poisson regression, contingency tables, log linear models, and random effect models. The generalized linear models will be discussed both in theory and in applications to real data from a variety of sources. Given jointly with STAT 873*. PREREQUISITES    STAT 268* or STAT 351*; STAT 361*; STAT 363*; or permission of the Department.
 STAT-486*/0.5 Survival Analysis 3L
Introduces the theory and application of survival analysis: survival distributions and their applications, parametric and nonparametric methods, proportional hazards models, counting process and proportional hazards regression, planning and designing clinical trials. Given jointly with STAT 886*. PREREQUISITES    STAT 361* or ECON 351*; STAT 462* is recommended.
 STAT-505*/0.5 Topics in Statistics I 3L
An important topic in probability or statistics not covered in any other course. PREREQUISITE    Permission of the Department.