University of Toronto at Scarborough 2003/2004 Calendar
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Statistics
(B.Sc.)
M. Evans, B.Sc. (Western Ontario), M.Sc., Ph.D., Professor
S.A. Hashim, B.Sc. (Columbia), Ph.D. (Missouri) Lecturer
Discipline Representative: M. Evans (416-287-7274)
Probability and statistics have developed over a period of several hundred years as attempts to quantify uncertainty. With its origins in modeling games of chance, probability theory has become a sophisticated mathematical discipline with applications in such fields as demography, genetics and physics.
Statistics is concerned with the proper collection and analysis of data, both to reduce uncertainty and to provide for its assessment via probability. Applications range from pre-election polling to the design and analysis of experiments to determine the relative efficacies of different vaccines.
STAB22H serves as a non-technical introduction to statistics. It is designed for students from disciplines where statistical methods are applied. STAB52H is a mathematical treatment of probability. STAB57H is an introduction to the methods and theory of statistical inference. The C-level courses build on the introductory material to provide a deeper understanding of statistical methodology and of its practical implementation.
Students interested in programs which involve Statistics are referred to Computer Science (page 60) and Mathematics (page163).
The Statistics streams of the Specialist Program in Mathematics and Its Applications and the Major Program in Mathematical Sciences are eligible for inclusion in the Co-operative Program in Physical Sciences and the Early Teacher Project in Physical Sciences. Please refer to the Physical Sciences Scarborough (page 185) of this Calendar for further information.
STAB22H3 Statistics
An introduction to statistics.
The emphasis of the course is on motivation and applications and the treatment is essentially non-mathematical. A statistical computer package is used for most computations, however, no previous experience with a computer is required. The course covers: descriptive statistics, probability, regression, sampling, experimental design and methods of statistical inference.
Exclusions: ANTC35, (BIOB28), ECOB09, ECOB10, (ECOB11), GGRB31, PSYB07, SOCB06, STAB57, STA220, STA250
STAB52H3 An Introduction to Probability
A mathematical treatment of probability. The topics covered include: the probability model, density and distribution functions, computer generation of random variables, conditional probability, expectation, sampling distributions, weak law of large numbers, central limit theorem, Monte Carlo methods, Markov chains, Poisson processes, simulation, applications. A computer package will be used.
Exclusions: STA107H, STA257H
Prerequisite: MATA36H or MATA37H
STAB57H3 An Introduction to Statistics
A mathematical treatment of the theory of statistics. The covered include: the statistical model, data collection, descriptive statistics, estimation, confidence intervals and P-values, likelihood inference methods, distribution-free methods, book-strapping, Bayesian methods, relationship among variables, contingency tables, regression, ANOVA, logistic regression, applications. A computer package will be used.
Exclusions: STA261H
Prerequisite: STAB52H
STAC42H3 Multivariate Analysis
Linear algebra for statistics. Multivariate distributions, the multivariate normal and some associated distribution theory. Multivariate regression analysis. Canonical correlation analysis. Principal components analysis. Factor analysis. Cluster and discriminant analysis. Multidimensional scaling. Instruction in the use of SAS.
Exclusion: STA437
Prerequisite: STAC67
STAC52H3 Experimental Design
The statistical aspects of collecting and analyzing experimental data. Complete randomization and restricted randomization schemes.
Exclusion: STA332H
Prerequisites: STAC67H
STAC57H3 Time Series Analysis
An overview of methods and problems in the analysis of time series data. Topics covered include descriptive methods, filtering and smoothing time series, identification and estimation of times series models, forecasting, seasonal adjustment, spectral estimation. Instruction in the use of SAS.
Exclusion: STA457
Prerequisite: STAC62H
STAC62H3 Stochastic Processes
This course continues the development of probability theory begun in STAB47H. Topics covered include Poisson processes, Gaussian processes, Markov processes, renewal theory, queuing theory, martingales and stochastic differential equations.
Exclusion: STA347
Prerequisite: (STAB47H) or STAB57H
STAC67H3 Regression Analysis
Orthogonal projections. Univariate normal distribution theory. The linear model and its statistical analysis, residual analysis, influence analysis, collinearity analysis, model selection procedures. Analysis of designs. Random effects. Models for categorical data. Nonlinear models. Instruction in the use of SAS.
Exclusion: STA302
Prerequisite: (STAB47H) or STAB57H
STAB57H3 An Introduction to Statistics
A mathematical treatment of the theory of statistics. The covered include: the statistical model, data collection, descriptive statistics, estimation, confidence intervals and P-values, likelihood inference methods, distribution-free methods, book-strapping, Bayesian methods, relationship among variables, contingency tables, regression, ANOVA, logistic regression, applications. A computer package will be used.
Exclusions: STA261H
Prerequisite: STAB52H
STAC42H3 Multivariate Analysis
Linear algebra for statistics. Multivariate distributions, the multivariate normal and some associated distribution theory. Multivariate regression analysis. Canonical correlation analysis. Principal components analysis. Factor analysis. Cluster and discriminant analysis. Multidimensional scaling. Instruction in the use of SAS.
Exclusion: STA437
Prerequisite: STAC67
STAC52H3 Experimental Design
The statistical aspects of collecting and analyzing experimental data. Complete randomization and restricted randomization schemes.
Exclusion: STA332H
Prerequisites: STAC67H
STAC57H3 Time Series Analysis
An overview of methods and problems in the analysis of time series data. Topics covered include descriptive methods, filtering and smoothing time series, identification and estimation of times series models, forecasting, seasonal adjustment, spectral estimation. Instruction in the use of SAS.
Exclusion: STA457
Prerequisite: STAC62H
STAC62H3 Stochastic Processes
This course continues the development of probability theory begun in STAB47H. Topics covered include Poisson processes, Gaussian processes, Markov processes, renewal theory, queuing theory, martingales and stochastic differential equations.
Exclusion: STA347
Prerequisite: (STAB47H) or STAB57H
STAC67H3 Regression Analysis
Orthogonal projections. Univariate normal distribution theory. The linear model and its statistical analysis, residual analysis, influence analysis, collinearity analysis, model selection procedures. Analysis of designs. Random effects. Models for categorical data. Nonlinear models. Instruction in the use of SAS.
Exclusion: STA302
Prerequisite: (STAB47H) or STAB57H
University of Toronto at Scarborough 2003/2004 Calendar
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