Courses Overview
Graduate Courses
STAT 518 (3) Theoretical Statistics
The foundations of statistical interference, exponential families. Likelihood, sufficiency and ancillarity. Principles of estimation and testing, asymptotic theory. Special topics.
Prerequisite: All of STAT 461, MATH 418 and one of MATH 420, MATH 544.
STAT 520 (1-6) d Topics in Bayesian Analysis and Decision Theory
STAT 521 (1-6) d Topics in Multivariate Analysis
STAT 522 (1-6) d Topics in Asymptotic Theory and Statistical Inference
STAT 526 (1-6) d Topics in Smoothing Methods
STAT 527 (1-6) d Topics in Biostatistics
STAT 530 (1-3) d Bayesian Inference and Decision
Utility functions and subjective probability distributions, uninformative priors, inference for common models such as the multivariate normal and regression models, hierarchical prior models, intersubjective statistical decision theory.
Prerequisite: STAT 461.
STAT 531 (1-3) d Reliability Theory
Probabilistic aspects of reliability theory. Classes of life distributions based on notions of aging, coherent systems, shock models, notions of dependence, multivariate distributions for dependent components, maintenance and replacement models.
Prerequisite: All of MATH 303, MATH 321, STAT 305.
STAT 532 (1-3) d Sequential Statistical Procedures
Sequential probability ratio test, fundamental identity, operating characteristics, optimality. Sequential tests for composite hypotheses. Sequential design of experiments, Bayes sequential decision problems, numerical methods. Applications to statistical problems.
Prerequisite: All of MATH 419, STAT 461.
STAT 533 (1-3) d Survival Analysis
Basic concepts, special distributions, censoring. Parametric and nonparametric methods, product-limit estimator, log-rank test, goodness-of-fit. Models for dependence on explanatory variables, residual analysis, time-dependent covariates.
Prerequisite: All of STAT 306, STAT 461.
STAT 534 (1-3) d Experimental Design and Quality Improvement
Graphical methods including Ishakawa's methods and control charts. Deming and Taguchi philosophy and methods. Acceptance sampling. Robust parameter designs. Fractional factorial designs and orthogonal arrays. Response surface methodology. Special topics.
Prerequisite: STAT 404.
STAT 535 (1-3) d Statistical Computing
Numerical methods useful for statistical research, and numerical analysis useful for writing statistical software (e. g., numerical linear algebra, optimization, generation of pseudo-random numbers, statistical graphics). The statistical language and computing environments for data analysis. Special research topics.
STAT 536 (1-3) d Statistical Theory for the Design and Analysis of Clinical Studies
Theory for statistical problems commonly encountered in medical studies, including clinical trials, studies of agreement and diagnostic accuracy, rate-comparisons, and standardization.
Corequisite: STAT 460.
STAT 537 (1-3) d Linear Models
Inference for normal theory linear models using projections and linear algebra, unifying regression and analysis of variance. Model building and model verification, mixed models and variance components. Special topics.
Prerequisite: All of STAT 404, STAT 460.
STAT 538 (1-3) d Generalized Linear Models
Extensions of the (Gaussian) linear model. Regression methods and models for binary, count data, categorical responses. Exposure to implementations in modern software.
Prerequisite: All of STAT 306, MATH 307.
STAT 540 (3) Statistical Methods for High Dimensional Biology
STAT 541 (1-3) d Applied Multivariate Analysis
Techniques of multivariate analysis motivated by examples from various sciences. Topics from : multivariate normal distribution, assessing multivariate normality, Hotelling's T2, multivariate analysis of variance and covariance, multivariate regression, discrimination and classification, cluster analysis, canonical correlation, principal components and factor analysis.
Prerequisite: All of STAT 306, MATH 307.
STAT 542 (1-3) d Analysis of Categorical Data
A systematic treatment of the theory and use of log-linear and linear logistic models for categorical response variables. Poisson, multinomial and product-multinomial sampling models, maximum likelihood estimation, existence of direct estimates, computational algorithms, adjusted residuals, asymptotic inference, approaches to model selection, special topics.
Prerequisite: STAT 404.
STAT 543 (1-3) d Time Series Analysis
Techniques of forecasting and modelling of time series. Topics from: time dependence and randomness, trend, seasonality, stationarity, Box-Jenkins techniques, exponential smoothing, spectral analysis, the Wiener-Kolmogorov approach, multivariate time series, cross-spectral analysis, and Kalman filtering.
Prerequisite: All of STAT 306, MATH 307.
STAT 544 (1-3) d Theory of Sampling
A comprehensive account of sampling theory for use in sample surveys. Topics include simple random sampling, stratified random sampling, ratio estimates, regression estimates, systematic sampling, cluster sampling, subsampling, double sampling, estimation of sample size, sources of errors in surveys.
STAT 545 (1-3) d Data Analysis
Introduction to modern statistical software for commonly used statistical methods. Motivation from datasets and scientific problems. Topics from: likelihood and Bayesian inference, model comparison, EM algorithm, resampling techniques, cross-validation, fitting curves to data, non-linear models, random effects, generalized additive models, classification trees, clustering and classification methods.
Prerequisite: All of STAT 306, MATH 307.
STAT 546 (1-3) d Nonparametric Statistical Methods
Linear rank tests for one and two samples, sign test, rank sum test, normal scores test, Savage test. Rank tests for k samples and nonparametric regression. Permutation tests. Goodness-of-fit tests, Kolmogorov-Smirnov and Cramer-von Mises tests. Power and efficiency of nonparametric methods. Nonparametric estimation. Theory of U-statistics.
Prerequisite: STAT 461.
STAT 547 (1-6) d Topics in Statistics
Students should consult the Statistics Department for the particular advanced topics offered in a given year.
STAT 548 (1-6) c Directed Studies in Statistics
Advanced study under the direction of a faculty member may be arranged in special situations.
STAT 549 (6/12) c Thesis for Master's Degree
STAT 550 (3) Techniques of Statistical Consulting
The basic skills of statistical consulting. Analysis of data sets, modelling, and statistical computing. Special topics such as graphical methods and data reduction techniques. Readings on consulting and applying statistics.
Corequisite: STAT 404.
STAT 551 (3) Statistical Consulting
Supervised statistical practice directed toward the solution of current problems posed by subject-area researchers.
Prerequisite: STAT 550.
STAT 560 (3) Statistical Theory I
Credit will not be given for both STAT 460 and STAT 560. [3-0-0]
STAT 561 (3) Statistical Theory II
STAT 589 (3) M.Sc. Project
STAT 598 (3) Co-operative Work Placement I
Restricted to students admitted to the Co-operative M.Sc. Education Program in Statistics.
STAT 599 (3) Co-operative Work Placement II
Restricted to students admitted to the Co-operative M.Sc. Education Program in Statistics.
Prerequisite: STAT 598.
STAT 649 (0) Ph.D. Thesis
