Statistics Courses

Key to Course Descriptions

For Distribution Requirement purposes STA 220H1, 221H1, 250H1, 255H1, and 257H1 have NO distribution requirement status; STA 429H1 is a SCIENCE or SOCIAL SCIENCE course; all other STA courses are classified as SCIENCE courses.

| Course Winter Timetable |


SCI199H1/Y1
First Year Seminar        52S

Undergraduate seminar that focuses on specific ideas, questions, phenomena or controversies, taught by a regular Faculty member deeply engaged in the discipline. Open only to newly admitted first year students. It may serve as a distribution requirement course; see page 47.


STA107H1
An Introduction to Probability and Modelling        39L, 13T

Introduction to the theory of probability, with emphasis on the construction of discrete probability models for applications. After this course, students are expected to understand the concept of randomness and aspects of its mathematical representation. Topics include random variables, Venn diagrams, discrete probability distributions, expectation and variance, independence, conditional probability, the central limit theorem, applications to the analysis of algorithms and simulating systems such as queues.

Exclusion: ECO220Y1, ECO227Y1/STA247H1STA255H1/STA257H1/
Co-requisite: MAT135Y1/MAT137Y1/MAT157Y1(MAT137Y1/MAT157Y1 is strongly recommended; MAT133Y1 is not acceptable)


STA220H1
The Practice of Statistics I        39L, 13T

An introductory course in statistical concepts and methods, emphasizing exploratory data analysis for univariate and bivariate data, sampling and experimental designs, basic probability models, estimation and tests of hypothesis in one-sample and comparative two-sample studies. A statistical computing package is used but no prior computing experience is assumed.

Exclusion: ECO220Y1/ECO227Y1/GGR270H1/PSY201H1/ SOC300Y1/STA250H1/STA261H1/STA248H1
Prerequisite: Grade 12 Mathematics and one University course in the physical, social, or life sciences
STA220H1 does not count as a distribution requirement course.



STA221H1
The Practice of Statistics II 39L, 13T

Continuation of STA220H1, emphasizing major methods of data analysis such as analysis of variance for one factor and multiple factor designs, regression models, categorical and non-parametric methods.
Exclusion:ECO220Y1/ECO227Y1/GGR270H1 /PSY202H1/SOC300Y1/STA261H1/250H1/STA248H1
Prerequisite: STA220H1
STA221H1 does not count as a distribution requirement course..


STA247H1
Probability with Computer Applications        39L, 13T

Introduction to the theory of probability, with emphasis on applications in computer science. The topics covered include random variables, discrete and continuous probability distributions, expectation and variance, independence, conditional probability, normal, exponential, binomial, and Poisson distributions, the central limit theorem, sampling distributions, estimation and testing, applications to the analysis of algorithms, and simulating systems such as queues.
Prerequisite: MAT135Y1/MAT137Y1/MAT157Y1; CSC108H1/CSC148H1

Exclusion: ECO227Y1/STA255H1/STA257H1


STA248H1
Statistics for Computer Scientists        39L, 13T

A survey of statistical methodology with emphasis on data analysis and applications. The topics covered include descriptive statistics , data collection and the design of experiments, univariate and multivariate design, tests of significance and confidence intervals, power, multiple regressions and the analysis of variance, and count data. Students learn to use a statistical computer package as part of the course.
Prerequisite: STA247H1/STA255H1/STA257H1; CSC108H1/CSC148H1
Exclusion: ECO220Y1/ECO227Y1/GGR 270Y11/PSY201H1/SOC 300Y1/STA220H1//STA250H1/STA261H1


STA250H1
Statistical Concepts        39L, 13T

A survey of statistical methodology with emphasis on data analysis and applications. The topics covered include descriptive statistics, basic probability, simulation, data collection and the design of experiments, tests of significance and confidence intervals, power, multiple regression and the analysis of variance, and count data. Students learn to use a statistical computer package as part of the course.

Exclusion: ECO220Y1/ECO227Y1/GGR270Y1/PSY201H1/ SOC300Y1/STA220H1/STA261H1/STA221H1/STA248H1
Prerequisite: MAT133Y1/MAT135Y1/MAT137Y1/MAT157Y1
STA250H1 does not count as a distribution requirement course



STA255H1
Statistical Theory 39L, 13T

This courses deals with the mathematical aspects of some of the topics discussed in STA250H1. Topics include discrete and continuous probability distributions, conditional probability, expectation, sampling distributions, estimation and testing, the linear model.
Exclusion: ECO220Y1/ECO227Y1/STA257H1/261H1/247H1/248H1
Prerequisite: STA250H1/STA221H1, MAT135Y1/MAT137Y1/MAT157Y1
STA255H1 does not count as a distribution requirement course.


STA257H1
Probability and Statistics I        39L, 13T

This course covers probability including its role in statistical modelling. Topics include probability distributions, expectation, continuous and discrete random variables and vectors, distribution functions. Basic limiting results and the normal distribution presented with a view to their applications in statistics.

Exclusion: ECO227Y1/STA255H1/STA247H1
Prerequisite: MAT135Y1/MAT137Y1/MAT157Y1 (MAT137Y1/MAT157Y1 is strongly recommended)
Co-requisite: MAT235Y1/MAT237Y1/MAT257Y1 (MAT237Y1/MAT257Y1 is strongly recommended)
STA257H1 does not count as a distribution requirement course



.
STA261H1
Probability and Statistics II 39L, 13T

A sequel to STA257H1 giving an introduction to current statistical theory and methods. Topics include: estimation, testing, and confidence intervals; unbiasedness, sufficiency, likelihood; simple linear and generalized linear models.
Exclusion: ECO227Y1/STA248H1/STA255H1
Prerequisite: STA257H1



STA299Y1
Research Opportunity Program

Credit course for supervised participation in faculty research project. See page 47 for details.



STA302H1
Regression Analysis 39L

Analysis of the multiple regression model by least squares; statistical properties of least squares analysis, estimate of error; residual and regression sums of squares; distribution theory under normality of the observations; confidence regions and intervals; tests for normality; variance stabilizing transformations, multicollinearity, variable search method.
Exclusion: ECO327Y1/357Y1
Prerequisite: STA255H1/STA248H1/261H1/ECO220Y1(70%)/ 227Y1/(STA257H1, MAT224H1)



STA322H1
Design of Sample Surveys 39L

Designing samples for valid inferences about populations at reasonable cost: stratification, cluster/multi-stage sampling, unequal probability selection, ratio estimation, control of non-sampling errors (e.g. non-response, sensitive questions, interviewer bias).
Prerequisite: ECO220Y1/227Y1/GGR270H1 / PSY202H1/SOC300Y1/STA221H1/255H1/261H1/248H1



STA332H1
Experimental Design 39L (formerly STA402H1)

Design and analysis of experiments: randomization; analysis of variance; block designs; orthogonal polynomials; factorial designs; response surface methodology; designs for quality control.
Prerequisite: STA302H1/352Y1/ECO327Y1/357Y1
Exclusion: STA402H1



STA347H1
Probability 39L

An overview of probability from a non-measure theoretic point of view. Random variables/vectors; independence, conditional expectation/probability and consequences. Various types of convergence leading to proofs of the major theorems in basic probability. An introduction to simple stochastic processes such as Poisson and branching processes.
Prerequisite: STA247H1/255H1/257H1/(ECO227, MAT237Y1/MAT257Y1), MAT235Y1/MAT237Y1/MAT257Y1 (MAT237Y1/257Y1 and STA257H1 are strongly recommended)



STA352Y1
Introduction to Mathematical Statistics 78L

Introduction to statistical theory and its application. Basic inference concepts. Likelihood function, Likelihood statistic. Simple large sample theory. Least squares and generalizations, survey of estimation methods. Testing hypotheses, p-values and confidence intervals. Bayesian-fequentist interface. Analysis of Variance from a vector-geometric viewpoint. Conditional inference.
Prerequisite: MAT235Y1/MAT237Y1/MAT257Y1; STA261H1/(STA257H1, MAT224H1)/(ECO227Y1, MAT237Y1/MAT257Y1) (MAT237Y1/MAT257Y1 very strongly recommended).



STA398H0/399Y0
Independent Experiential Study Project

An instructor-supervised group project in an off-campus setting. See page 47 for details.



STA410H1
Statistical Computation 39L

Programming in an interactive statistical environment. Generating random variates and evaluating statistical methods by simulation. Algorithms for linear models, maximum likelihood estimation, and Bayesian inference. Statistical algorithms such as the Kalman filter and the EM algorithm. Graphical display of data.
Prerequisite: STA302H1, CSC108H1



STA414H1
Statistical Methods for Data Mining and Machine Learning 52L, 26P

Statistical aspects of supervised learning: regression with spline bases, regularization methods, parametric and nonparametric classification methods, nearest neighbours, cross-validation and model selection, generalized additive models, trees, model averaging, clustering and nearest neigtbour methods for unsupervised learning.
Prerequisite: STA302H1/CSC411H1



STA422H1
Theory of Statistical Inference 39L

The course discusses foundational aspects of various theories of statistics. Specific topics covered include: likelihood based inference, decision theory, fiducial and structural inference, Bayesian inference.
Prerequisite: STA352Y1



STA429H1
Advanced Statistics for the Life and Social Sciences 39L

The course discusses many advanced statistical methods used in the life and social sciences. Emphasis is on learning how to become a critical interpreter of these methodologies while keeping mathematical requirements low. Topics covered include multiple regression, logistic regression, discriminant and cluster analysis, principal components and factor analysis.
Exclusion: All 300+ level STA courses except STA322H1
Prerequisite: ECO220Y1/227Y1/GGR270Y1 /PSY202H1/SOC300Y1/STA221H1/250H1
STA429H1 does not count towards any STA programs


STA437H1
Applied Multivariate Statistics        26L, 13P

Practical techniques for the analysis of multivariate data; fundamental methods of data reduction with an introduction to underlying distribution theory; basic estimation and hypothesis testing for multivariate means and variances; regression coefficients; principal components and partial, multiple and canonical correlations; multivariate analysis of variance; profile analysis and curve fitting for repeated measurements; classification and the linear discriminant function.
Prerequisite: ECO327Y1/357Y1/STA302H1/STA352Y1
Recommended preparation: APM233Y1/MAT223H1/MAT240H1


STA438H1
Theoretical Multivariate Statistics        39L

An introductory survey of current multivariate analysis, multivariate normal distributions, distribution of multiple and partial correlations, Wishart distributions, distribution of Hotelling’s T2, testing and estimation of regression parameters, classification and discrimination.
Prerequisite: MAT223H1/MAT240H1, STA352Y1/STA437H1 (STA352Y1 strongly recommended)


STA442H1
Methods of Applied Statistics        39L

Advanced topics in statistics and data analysis with emphasis on applications. Diagnostics and residuals in linear models, introductions to generalized linear models, graphical methods, additional topics such as random effects models, split plot designs, smoothing and density estimation, analysis of censored data, introduced as needed in the context of case studies.
Prerequisite: ECO327Y1/357Y1/STA302H1


STA447H1
Stochastic Processes        39L (formerly STA348H1)

Discrete and continuous time processes with an emphasis on Markov, Gaussian and renewal processes. Martingales and further limit theorems. A variety of applications taken from some of the following areas are discussed in the context of stochastic modeling: Information Theory, Quantum Mechanics, Statistical Analyses of Stochastic Processes, Population Growth Models, Reliability, Queuing Models, Stochastic Calculus, Simulation (Monte Carlo Methods).

Exclusion: STA348H1
Prerequisite: STA347H1


STA450H1
Topics in Statistics        39L

Topics of current research interest are covered. Topics change from year to year, and students should consult the department for information on material presented in a given year.


STA457H1
Time Series Analysis        39L

An overview of methods and problems in the analysis of time series data. Topics include: descriptive methods, filtering and smoothing time series, theory of stationary processes, identification and estimation of time series models, forecasting, seasonal adjustment, spectral estimation, bivariate time series models.
Prerequisite: ECO327Y1/357Y1/STA302H1
Recommended preparation: MAT235Y1/MAT237Y1/MAT257Y1


STA496H1/497H1
Readings in Statistics        TBA

Independent study under the direction of a faculty member. Persons wishing to take this course must have the permission of the Undergraduate Secretary and of the prospective supervisor.


STA498Y1/499Y1
Readings in Statistics        TBA

Independent study under the direction of a faculty member. Persons wishing to take this course must have the permission of the Undergraduate Secretary and of the prospective supervisor.