Note: This is the 2018鈥�2019 eCalendar. Update the year in your browser's URL bar for the most recent version of this page, or .
Program Requirements
The Minor may be taken in conjunction with any primary program in the Faculty of Science. Students should declare their intention to follow the Minor Statistics at the beginning of the penultimate year and must obtain approval for the selection of courses to fulfil the requirements for the Minor from the Departmental Chief Adviser (or delegate).
All courses counted towards the Minor must be passed with a grade of C or better. Generally, no more than 6 credits of overlap are permitted between the Minor and the primary program. However, with an approved choice of substantial courses, the overlap restriction may be relaxed to 9 credits for students whose primary program requires 60 credits or more, and to 12 credits when the primary program requires 72 credits or more.
Required Courses (15 credits)
* MATH 223 may be replaced by MATH 235 and MATH 236. In this case the complementary credit requirement is reduced by 3 credits.
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MATH 222 Calculus 3 (3 credits)
Overview
Mathematics & Statistics (Sci) : Taylor series, Taylor's theorem in one and several variables. Review of vector geometry. Partial differentiation, directional derivative. Extreme of functions of 2 or 3 variables. Parametric curves and arc length. Polar and spherical coordinates. Multiple integrals.
Terms: Fall 2018, Winter 2019, Summer 2019
Instructors: Macdonald, Jeremy; Faifman, Dmitry (Fall) Sektnan, Lars (Winter) Pequignot, Yann Batiste (Summer)
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MATH 223 Linear Algebra (3 credits) *
Overview
Mathematics & Statistics (Sci) : Review of matrix algebra, determinants and systems of linear equations. Vector spaces, linear operators and their matrix representations, orthogonality. Eigenvalues and eigenvectors, diagonalization of Hermitian matrices. Applications.
Terms: Fall 2018, Winter 2019
Instructors: Kelome, Djivede (Fall) Macdonald, Jeremy (Winter)
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MATH 323 Probability (3 credits)
Overview
Mathematics & Statistics (Sci) : Sample space, events, conditional probability, independence of events, Bayes' Theorem. Basic combinatorial probability, random variables, discrete and continuous univariate and multivariate distributions. Independence of random variables. Inequalities, weak law of large numbers, central limit theorem.
Terms: Fall 2018, Winter 2019, Summer 2019
Instructors: Stephens, David (Fall) Wolfson, David B (Winter) Kelome, Djivede (Summer)
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MATH 324 Statistics (3 credits)
Overview
Mathematics & Statistics (Sci) : Sampling distributions, point and interval estimation, hypothesis testing, analysis of variance, contingency tables, nonparametric inference, regression, Bayesian inference.
Terms: Fall 2018, Winter 2019
Instructors: Khalili Mahmoudabadi, Abbas (Fall) Asgharian-Dastenaei, Masoud (Winter)
Fall and Winter
Prerequisite: MATH 323 or equivalent
Restriction: Not open to students who have taken or are taking MATH 357
You may not be able to receive credit for this course and other statistic courses. Be sure to check the Course Overlap section under Faculty Degree Requirements in the Arts or Science section of the Calendar.
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MATH 423 Regression and Analysis of Variance (3 credits)
Overview
Mathematics & Statistics (Sci) : Least-squares estimators and their properties. Analysis of variance. Linear models with general covariance. Multivariate normal and chi-squared distributions; quadratic forms. General linear hypothesis: F-test and t-test. Prediction and confidence intervals. Transformations and residual plot. Balanced designs.
Terms: Fall 2018
Instructors: Yang, Yi (Fall)
Complementary Courses (9 credits)
9 credits selected from:
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CHEM 593 Statistical Mechanics (3 credits)
Overview
Chemistry : Intermediate topics in statistical mechanics, including: modern and classical theories of real gases and liquids, critical phenomena and the renormalization group, time-dependent phenomena, linear response and fluctuations, inelastic scattering, Monte Carlo and molecular dynamics methods.
Terms: Winter 2019
Instructors: Ronis, David M (Winter)
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GEOG 351 Quantitative Methods (3 credits)
Overview
Geography : Multiple regression and correlation, logit models, discrete choice models, gravity models, facility location algorithms, survey design, population projection.
Terms: Winter 2019
Instructors: Breau, Sebastien (Winter)
Winter
3 hours
Prerequisite: GEOG 202 or equivalent or permission of instructor
You may not be able to get credit for this course and other statistic courses. Be sure to check the Course Overlap section under Faculty Degree Requirements in the Arts or Science section of the Calendar.
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MATH 427 Statistical Quality Control (3 credits)
Overview
Mathematics & Statistics (Sci) : Introduction to quality management; variability and productivity. Quality measurement: capability analysis, gauge capability studies. Process control: control charts for variables and attributes. Process improvement: factorial designs, fractional replications, response surface methodology, Taguchi methods. Acceptance sampling: operating characteristic curves; single, multiple and sequential acceptance sampling plans for variables and attributes.
Terms: This course is not scheduled for the 2018-2019 academic year.
Instructors: There are no professors associated with this course for the 2018-2019 academic year.
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MATH 447 Introduction to Stochastic Processes (3 credits)
Overview
Mathematics & Statistics (Sci) : Conditional probability and conditional expectation, generating functions. Branching processes and random walk. Markov chains, transition matrices, classification of states, ergodic theorem, examples. Birth and death processes, queueing theory.
Terms: Winter 2019
Instructors: Steele, Russell (Winter)
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MATH 523 Generalized Linear Models (4 credits)
Overview
Mathematics & Statistics (Sci) : Modern discrete data analysis. Exponential families, orthogonality, link functions. Inference and model selection using analysis of deviance. Shrinkage (Bayesian, frequentist viewpoints). Smoothing. Residuals. Quasi-likelihood. Contingency tables: logistic regression, log-linear models. Censored data. Applications to current problems in medicine, biological and physical sciences. R software.
Terms: Winter 2019
Instructors: Neslehova, Johanna (Winter)
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MATH 525 Sampling Theory and Applications (4 credits)
Overview
Mathematics & Statistics (Sci) : Simple random sampling, domains, ratio and regression estimators, superpopulation models, stratified sampling, optimal stratification, cluster sampling, sampling with unequal probabilities, multistage sampling, complex surveys, nonresponse.
Terms: Winter 2019
Instructors: Steele, Russell (Winter)
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MATH 545 Introduction to Time Series Analysis (4 credits)
Overview
Mathematics & Statistics (Sci) : Stationary processes; estimation and forecasting of ARMA models; non-stationary and seasonal models; state-space models; financial time series models; multivariate time series models; introduction to spectral analysis; long memory models.
Terms: Fall 2018
Instructors: Steele, Russell (Fall)
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MATH 556 Mathematical Statistics 1 (4 credits)
Overview
Mathematics & Statistics (Sci) : Distribution theory, stochastic models and multivariate transformations. Families of distributions including location-scale families, exponential families, convolution families, exponential dispersion models and hierarchical models. Concentration inequalities. Characteristic functions. Convergence in probability, almost surely, in Lp and in distribution. Laws of large numbers and Central Limit Theorem. Stochastic simulation.
Terms: Fall 2018
Instructors: Asgharian-Dastenaei, Masoud (Fall)
Fall
Prerequisite: MATH 357 or equivalent
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MATH 557 Mathematical Statistics 2 (4 credits)
Overview
Mathematics & Statistics (Sci) : Sampling theory (including large-sample theory). Likelihood functions and information matrices. Hypothesis testing, estimation theory. Regression and correlation theory.
Terms: Winter 2019
Instructors: Khalili Mahmoudabadi, Abbas (Winter)
Winter
Prerequisite: MATH 556
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PHYS 362 Statistical Mechanics (3 credits)
Overview
Physics : Quantum states and ensemble averages. Fermi-Dirac, Bose-Einstein and Boltzmann distribution functions and their applications.
Terms: Winter 2019
Instructors: Francois, Paul (Winter)
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PHYS 559 Advanced Statistical Mechanics (3 credits)
Overview
Physics : Scattering and structure factors. Review of thermodynamics and statistical mechanics; correlation functions (static); mean field theory; critical phenomena; broken symmetry; fluctuations, roughening.
Terms: Fall 2018
Instructors: Del Rio Amador, Lenin (Fall)
Fall
3 hours lectures
Restriction: U3 Honours students, graduate students, or permission of the instructor
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SOCI 504 Quantitative Methods 1 (3 credits)
Overview
Sociology (Arts) : Analysis of quantitative information, especially in large, survey-type, data sets. Use of computer programs such as SPSS and SAS. Topics include: cross tabulations with an emphasis on multi-dimensional tables, multiple correlation and regression, and, the relationship between individual and aggregate level statistical analyses. Special reference to demographic techniques.
Terms: Fall 2018
Instructors: Soehl, Thomas (Fall)
No more than 6 credits may be taken outside the Department of Mathematics and Statistics.
Further credits (if needed) may be freely chosen from the required and complementary courses for majors and honours students in Mathematics, with the obvious exception of courses that involve duplication of material.
Faculty of Science—2018-2019 (last updated Aug. 22, 2018) (disclaimer)
