2001/2002 Calendar
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STA Statistics Courses

| Course Winter Timetable |


SCI199Y1
First Year Seminar 52T

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 breadth requirement course; see page 44.


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: ECO227Y/STA255H/257H
Co-requisite: MAT135Y/137Y/157Y(MAT137Y/157Y is strongly recommended; MAT133Y 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: ECO220Y/227Y/GGR270Y/PSY201H/SOC300Y/STA250H/261H
Prerequisite: Grade 12 Mathematics and one University course in the physical, social, or life sciences


STA220H does not count as a distribution requirement course.
STA221H1

The Practice of Statistics II 39L, 13T
Continuation of STA220H, 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
:ECO220Y/227Y/GGR270Y/JBS229H/PSY202H/SOC300Y/STA261H
Prerequisite: STA220H


STA221H does not count as a distribution requirement course.
JBS229H1

Statistics for Biologists 39L, 13T
Continuation of STA220H, jointly taught by Statistics and Biology faculty, emphasizing methods and case studies relevant to biologists including experimental design and analysis of variance, regression models, categorical and non-parametric methods.
Exclusion: ECO220Y/227Y/GGR270Y/PSY202H/SOC300Y/STA221H/261H
Prerequisite: BIO150Y, STA220H


JBS229H does not count as a distribution requirement course.
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: ECO220Y/227Y/GGR270Y/PSY201H/SOC300Y/STA220H/261H
Prerequisite: MAT133Y/135Y/137Y/157Y


STA250H 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 STA250H. Topics include discrete and continuous probability distributions, conditional probability, expectation, sampling distributions, estimation and testing, the linear model.
Exclusion: ECO220Y/227Y/STA257H
Prerequisite: STA250H/221H/JBS229H, MAT135Y/137Y/157Y


STA255H 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: ECO227Y/STA255H
Prerequisite: MAT135Y/137Y/157Y (MAT137Y/157Y is strongly recommended)
Co-requisite: MAT235Y/237Y/257Y ((MAT237Y/157Y is strongly recommended


STA257H does not count as a distribution requirement course.
STA261H1

Probability and Statistics II 39L, 13T
A sequel to STA257H 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: ECO227Y
Prerequisite: STA257H


STA299Y1
Research Opportunity Program


Credit course for supervised participation in faculty research project. See page 44 for details.


STA302H1
Regression Analysis 39L

Analysis of the multiple regression model by least squares; statistical properties of the least square analysis, including the Gauss Markov theorem; 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: ECO327Y, 357Y
Prerequisite: STA255H/261H/ECO220Y(70%)/227Y/(STA257H, MAT224H)
Recommended preparation: APM233Y/MAT223H/240H


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: ECO220Y/227Y/GGR270Y/JBS229H/PSY202H/SOC300Y/STA221H/255H/261H


STA332H1
Experimental Design

(formerly STA402H) 39L
Design and analysis of experiments: randomization; analysis of variance; block designs; orthogonal polynomials; factorial designs; response surface methodology; designs for quality control.
Prerequisite: STA302H/352Y/ECO327Y/357Y


STA347H1
Probability 39L

An overview of probability form 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: STA257H


STA352Y1
Introduction to Mathematical Statistics 78L

An introduction to the theory of mathematical statistics. The topics include: a review of some relevant concepts from the theory of probability, the theory of optimal estimators, tests and confidence regions, large sample theory, likelihood theory, distribution-free methods, Bayesian inference.
Prerequisite: MAT235Y/237Y/257Y; STA261H/(STA 257H, MAT 224H)


STA398H0/399Y0
Independent Experiential Study Project


An instructor-supervised group project in an off-campus setting. See page 44 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: STA302H, CSC260H/270H


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: STA352Y


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 STA322H
Prerequisite: ECO220Y/227Y/GGR270Y/JBS229H/PSY202H/SOC300Y/STA221H/250H


STA429H 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: ECO327Y/357Y/STA302H/352Y
Recommended preparation: APM233Y/MAT223H/240H


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: MAT223H/240H, STA352Y/437H


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: ECO327Y/357Y/STA302H


STA447H1
Stochastic Processes (formerly STA348H) 39L

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).
Prerequisite: STA347H


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: ECO327Y/357Y/STA302H
Recommended preparation: MAT235Y/237Y/257Y


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.


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