 
Statistical Sciences (S)



Statistical Sciences
1023A/B 
Statistical Concepts

An examination of statistical issues aiming towards statistical literacy and appropriate interpretation of statistical information. Common misconceptions will be targeted. Assessment of the validity and treatment of results in popular and scientific media. Conceptual consideration of study design, numerical and graphical data summaries, probability, sampling variability, confidence intervals and hypothesis tests.
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Statistical Sciences
1024A/B 
Introduction to Statistics

Statistical inference, experimental design, sampling design, confidence intervals and hypothesis tests for means and proportions, regression and correlation.
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Statistical Sciences
2035 
Statistics for Business and Social Sciences

Descriptive statistics and graphs, probability and distributions. Sampling, hypothesis testing, and confidence intervals. Experimental design and analysis of variance. Regression and correlation, including multiple regression. Applications emphasized. This course cannot be taken for credit in any module in Statistics, Actuarial Science, or Financial Modelling.
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Statistical Sciences
2037A/B 
Statistics for Health

An examination of statistical issues aiming towards statistical literacy and appropriate interpretation of statistical information. Common misconceptions will be targeted. Assessment of the validity and treatment of results in popular and scientific media. Conceptual consideration of study design, numerical and graphical data summaries, probability, sampling variability, confidence intervals and hypothesis tests. Emphasis will be placed on healthrelated applications.
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Statistical Sciences
2141A/B 
Applied Probability and Statistics for Engineers

An introduction to statistics with emphasis on the applied probability models used in Electrical and Civil Engineering and elsewhere. Topics covered include samples, probability, probability distributions, estimation (including comparison of means), correlation and regression. Cannot be taken for credit in any 3year or honors program or in any module in Statistics, Actuarial Science, or Financial Modelling.
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Statistical Sciences
2143A/B 
Applied Statistics and Data Analysis for Engineers

A datadriven introduction to statistics intended primarily for students in Chemical and Mechanical Engineering. Exploratory data analysis, probability, the Binomial, Poisson, Normal, ChiSquare and F distributions. Estimation, correlation and regression (model building and parameter estimation), analysis of variance, design of experiments. Cannot be taken for credit in any module in Statistics, Actuarial Science, or Financial Modelling.
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Statistical Sciences
2244A/B 
Statistics for Science

An introductory course in the application of statistical methods, intended for honors students in departments other than Statistical and Actuarial Sciences, Applied Mathematics, Mathematics, or students in the Faculty of Engineering. Topics include sampling, confidence intervals, analysis of variance, regression and correlation. Cannot be taken for credit in any module in Statistics, Actuarial Science, or Financial Modelling.
Prerequisite(s):
A full mathematics course, or equivalent, numbered 1000 or above. Statistical Sciences 1024A/B can be used to meet 0.5 of the 1.0 mathematics course requirement.
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Statistical Sciences
2503A/B 
Advanced Mathematics for Statistical Applications

Modeling deterministic systems with differential equations: first and second order ODEs, systems of linear differential equations. Laplace transforms and moment generating functions. Modeling stochastic systems with Markov chains: discrete and continuous time chains, ChapmanKolmogorov equations, ergodic theorems.
Antirequisite(s):
The former Applied Mathematics 2503A/B.
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Statistical Sciences
2857A/B 
Probability and Statistics I

Probability axioms, conditional probability, Bayes' theorem. Random variables motivated by real data and examples. Parametric univariate models as data reduction and description strategies. Multivariate distributions, expectation and variance. Likelihood function will be defined and exploited as a means of estimating parameters in certain simple situations.
Antirequisite(s):
The former Statistical Sciences 2657A.
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Statistical Sciences
2858A/B 
Probability and Statistics II

An introduction to the theory of statistics with strong links to data as well as its probabilistic underpinnings. Topics covered include estimation and hypothesis testing, sampling distributions, linear regression, experimental design, law of large numbers and central limit theorem.
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Statistical Sciences
2864A/B 
Statistical Programming

An introduction to programming using a high level language (currently R).
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Statistical Sciences
3657A/B 
Intermediate Probability

A continuation of the study of multivariate probability and stochastic processes. This course builds on the background developed in the second year courses, and focuses on the more advanced aspects of multivariate probability, namely transformations where the domain of random variables must be carefully considered.
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Statistical Sciences
3843A/B 
Introduction to Study Design

A case study approach to how data are collected in science, social science and medicine, including the methods of designed experiments, sample surveys, observational studies and administrative records.
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Statistical Sciences
3850F/G 
Data Analysis

A course in applied statistical computing using popular statistical software such as R or SAS. The primary objective of this course is to strengthen students' applied statistics skills and statistical problem solving abilities. At the end of the course they should be able to identify suitable statistical methodologies for different situations and critically evaluate the appropriateness of model assumptions.
Antirequisite(s):
The former Statistical Sciences 3814A/B.
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Statistical Sciences
3858A/B 
Mathematical Statistics

Point estimation: sufficiency, completeness, consistency, unbiasedness, CramerRao inequality, RaoBlackwell theorem, Hypotheses tests:uniformly most powerful tests, likelihood ratio tests.
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Statistical Sciences
3859A/B 
Regression

Multiple linear regression, GaussMarkov theorem, Cochran's theorem, Craig's theorem, stepwise regression, polynomial regression, use of indicator variables, and regression diagnostics.
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Statistical Sciences
4654A/B 
Markov Chains with Applications

Continuoustime Markov chains, applications to phasetype distributions, Markov chain Monte Carlo simulation and queuing theory.
Antirequisite(s):
The former Statistical Sciences 3652A/B, former Statistical Sciences 4652A/B, former Statistical Sciences 4657A/B and former Statistical Sciences 4737A/B.
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Statistical Sciences
4846A/B 
Experimental Design

Completely randomized designs, randomized complete and incomplete block designs, factorial and fractional factorial designs, latin square designs, hierarchical designs, random and fixed effect models.
Antirequisite(s):
The former Statistical Sciences 3846A/B.
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Statistical Sciences
4850F/G 
Advanced Data Analysis

Modern methods of data analysis including linear and generalized linear models, modern nonparametric regression, principal component analysis, multilevel modelling and bootstrapping.
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Statistical Sciences
4853A/B 
Sampling Theory and Methods

Simple random sampling with and without replacement, stratification, systematic sampling, cluster and multistage clustering, ratio and regression estimation, models in surveys, survey design, estimation and analysis.
Antirequisite(s):
The former Statistical Sciences 3853F/G.
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Statistical Sciences
4861A/B 
Time Series

ARIMA models, seasonality, dynamic regression, model building using an interactive computer package, forecasting, intervention analysis, control, applications in econometrics, business, and other areas.
Antirequisite(s):
The former Statistical Sciences 3861A/B.
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Statistical Sciences
4930A/B 
Selected Topics in Statistics

A course description will be available from the department at the time of registration.
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A minimum mark of 60% in Statistical Sciences 3657A/B (or the former Statistical Sciences 2657A/B) or permission of the department.
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Statistical Sciences
4940F/G 
Selected Topics in Statistics

A course description will be available from the department at the time of registration.
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Statistical Sciences
4999F/G/Z 
Project in Statistical Sciences

The student will work on a project under faculty supervision. The project may involve an extension, or more detailed coverage, of material presented in other courses. Credit for the course will involve a written report as well as an oral presentation.
Prerequisite(s):
Registration in the fourth year of the Honors Specialization in Actuarial Science, Statistics, or Financial Modelling. Students must have a modular course average of at least 80% and must find a faculty member to supervise the project.
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