Program Requirement:
The program provides training in statistics with a mathematical core. Taken together with the B.A.; Supplementary Minor Concentration in Statistics, these two programs constitute an equivalent of the B.Sc.; Major in Statistics program offered by the Faculty of Science. With satisfactory performance in an appropriate selection of courses, these two programs can lead to the accreditation "A.Stat" from the Statistical Society of Canada, which is regarded as the entry level requirement for a statistician practicing in Canada. Students interested in this accreditation should consult an academic adviser.
Program Prerequisites
Students entering the B.A.; Major Concentration Statistics program are normally expected to have completed the courses below or their equivalent. Otherwise, they will be required to make up any deficiencies in these courses over and above the 36 credits of courses.
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MATH 133
Linear Algebra and Geometry
3 Credits
Offered in the:
- Fall
- Winter
- Summer
Mathematics & Statistics (Sci): Systems of linear equations, matrices, inverses, determinants; geometric vectors in three dimensions, dot product, cross product, lines and planes; introduction to vector spaces, linear dependence and independence, bases. Linear transformations. Eigenvalues and diagonalization.
Offered by: Mathematics and Statistics
- 3 hours lecture, 1 hour tutorial
- Prerequisite: a course in functions
- Restriction(s): 1) Not open to students who have taken CEGEP objective 00UQ or equivalent. 2) Not open to students who have taken or are taking MATH 123, except by permission of the Department of Mathematics and Statistics.
- Terms
- Instructors
- Jeremy Macdonald
- Charles Roth
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MATH 140
Calculus 1
3 Credits
Offered in the:
- Fall
- Winter
- Summer
Mathematics & Statistics (Sci): Review of functions and graphs. Limits, continuity, derivative. Differentiation of elementary functions. Antidifferentiation. Applications.
Offered by: Mathematics and Statistics
- 3 hours lecture, 1 hour tutorial
- Prerequisite: High School Calculus
- Restriction(s): 1) Not open to students who have taken MATH139 or MATH 150 or CEGEP objective 00UN or equivalent. 2) Not open to students who have taken or are taking MATH 122, except by permission of the Department of Mathematics and Statistics.
- Each Tutorial section is enrolment limited
- Terms
- Instructors
- Sidney Trudeau, Marcin Sabok
-
MATH 141
Calculus 2
4 Credits
Offered in the:
- Fall
- Winter
- Summer
Mathematics & Statistics (Sci): The definite integral. Techniques of integration. Applications. Introduction to sequences and series.
Offered by: Mathematics and Statistics
- Prerequisites: MATH 139 or MATH 140 or MATH 150.
- Restriction(s): Not open to students who have taken CEGEP objective 00UP or equivalent.
- Restriction(s): Not open to students who have taken or are taking MATH 122,except by permission of the Department of Mathematics and Statistics.
- Each Tutorial section is enrolment limited
According to the Faculty of Arts Multi-Track System degree requirements, option C, students registered in this program may also register in the B.A.; Supplementary Minor Concentration in Statistics; they must also then complete another minor concentration in a discipline other than Mathematics and Statistics.
For more information about the Multi-Track System options, please refer to Faculty of Arts regulations under "Faculty Degree Requirements," "About Program Requirements," and "Departmental Programs."
Guidelines for Course Selection
Students are strongly advised to complete all required courses by the end of U2.
Where appropriate, Honours courses may be substituted for equivalent courses. Students planning to pursue graduate studies are encouraged to make such substitutions.
Required Courses (24 credits)
* Students who have taken an equivalent of MATH 203 at CEGEP or elsewhere must replace it by another course from the Complementary course list.
** Students must take MATH 204 before taking MATH 324.
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MATH 203
Principles of Statistics 1
3 Credits*
Offered in the:
- Fall
- Winter
- Summer
Mathematics & Statistics (Sci): Examples of statistical data and the use of graphical means to summarize the data. Basic distributions arising in the natural and behavioural sciences. The logical meaning of a test of significance and a confidence interval. Tests of significance and confidence intervals in the one and two sample setting (means, variances and proportions).
Offered by: Mathematics and Statistics
- No calculus prerequisites
- Restriction: This course is intended for students in all disciplines. For extensive course restrictions covering statistics courses see Section 3.6.1 of the Arts and of the Science sections of the calendar regarding course overlaps.
- 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. Students should consult http://www.mcgill.ca/students/transfercredit for information regarding transfer credits for this course.
- Terms
- Instructors
- Jose Andres Correa, David A Stephens
- Alia Sajjad
-
MATH 204
Principles of Statistics 2
3 Credits**
Offered in the:
- Fall
- Winter
- Summer
Mathematics & Statistics (Sci): The concept of degrees of freedom and the analysis of variability. Planning of experiments. Experimental designs. Polynomial and multiple regressions. Statistical computer packages (no previous computing experience is needed). General statistical procedures requiring few assumptions about the probability model.
Offered by: Mathematics and Statistics
- Winter
- Prerequisite: MATH 203 or equivalent. No calculus prerequisites
- Restriction: This course is intended for students in all disciplines. For extensive course restrictions covering statistics courses see Section 3.6.1 of the Arts and of the Science sections of the calendar regarding course overlaps.
- 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.
-
MATH 208
Intro to Statistical Computing
3 Credits
Offered in the:
- Fall
- Winter
- Summer
Mathematics & Statistics (Sci): Basic data management. Data visualization. Exploratory data analysis and descriptive statistics. Writing functions. Simulation and parallel computing. Communication data and documenting code for reproducible research.
Offered by: Mathematics and Statistics
-
MATH 222
Calculus 3
3 Credits
Offered in the:
- Fall
- Winter
- Summer
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.
Offered by: Mathematics and Statistics
-
MATH 223
Linear Algebra
3 Credits
Offered in the:
- Fall
- Winter
- Summer
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.
Offered by: Mathematics and Statistics
- Fall and Winter
- Prerequisite: MATH 133 or equivalent
- Restriction: Not open to students in Mathematics programs nor to students who have taken or are taking MATH 236, MATH 247 or MATH 251. It is open to students in Faculty Programs
-
MATH 242
Analysis 1
3 Credits
Offered in the:
- Fall
- Winter
- Summer
Mathematics & Statistics (Sci): A rigorous presentation of sequences and of real numbers and basic properties of continuous and differentiable functions on the real line.
Offered by: Mathematics and Statistics
- Fall
- Prerequisite: MATH 141
- Restriction(s): Not open to students who are taking or who have taken MATH 254.
-
MATH 323
Probability
3 Credits
Offered in the:
- Fall
- Winter
- Summer
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.
Offered by: Mathematics and Statistics
- Prerequisites: MATH 141 or equivalent.
- Restriction: Intended for students in Science, Engineering and related disciplines, who have had differential and integral calculus
- Restriction: Not open to students who have taken or are taking MATH 356
- Terms
- Instructors
- Alia Sajjad
- Tharshanna Nadarajah
-
MATH 324
Statistics
3 Credits**
Offered in the:
- Fall
- Winter
- Summer
Mathematics & Statistics (Sci): Sampling distributions, point and interval estimation, hypothesis testing, analysis of variance, contingency tables, nonparametric inference, regression, Bayesian inference.
Offered by: Mathematics and Statistics
- 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.
- Terms
- Instructors
- Tharshanna Nadarajah
- Masoud Asgharian
Complementary Courses (12 credits)
12 credits from the following:
* Students can take at most one of MATH 410, MATH 420, MATH 527D1/D2 and WCOM 314.
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COMP 551
Applied Machine Learning
4 Credits
Offered in the:
- Fall
- Winter
- Summer
Computer Science (Sci): Selected topics in machine learning and data mining, including clustering, neural networks, support vector machines, decision trees. Methods include feature selection and dimensionality reduction, error estimation and empirical validation, algorithm design and parallelization, and handling of large data sets. Emphasis on good methods and practices for deployment of real systems.
Offered by: Computer Science
- Terms
- Instructors
- Isabeau Prémont-Schwarz, Reihaneh Rabbany
- Yue Li
-
MATH 308
Fundls of Statistical Learning
3 Credits
Offered in the:
- Fall
- Winter
- Summer
Mathematics & Statistics (Sci): Theory and application of various techniques for the exploration and analysis of multivariate data: principal component analysis, correspondence analysis, and other visualization and dimensionality reduction techniques; supervised and unsupervised learning; linear discriminant analysis, and clustering techniques. Data applications using appropriate software.
Offered by: Mathematics and Statistics
-
MATH 410
Majors Project
3 Credits*
Offered in the:
- Fall
- Winter
- Summer
Mathematics & Statistics (Sci): A supervised project.
Offered by: Mathematics and Statistics
- Prerequisite: Students must have 21 completed credits of the required mathematics courses in their program, including all required 200 level mathematics courses.
- Requires departmental approval.
- Terms
- Instructors
- Djivede A Kelome
- Djivede A Kelome
-
MATH 420
Independent Study
3 Credits*
Offered in the:
- Fall
- Winter
- Summer
Mathematics & Statistics (Sci): Reading projects permitting independent study under the guidance of a staff member specializing in a subject where no appropriate course is available. Arrangements must be made with an instructor and the Chair before registration.
Offered by: Mathematics and Statistics
- Fall and Winter and Summer
- Requires approval by the chair before registration
- Please see regulations concerning Project Courses under Faculty Degree Requirements
- Terms
- Instructors
- Djivede A Kelome
- Djivede A Kelome
-
MATH 423
Applied Regression
3 Credits
Offered in the:
- Fall
- Winter
- Summer
Mathematics & Statistics (Sci): Multiple regression estimators and their properties. Hypothesis tests and confidence
intervals. Analysis of variance. Prediction and prediction intervals. Model diagnostics. Model selection. Introduction to weighted least squares. Basic contingency table analysis. Introduction to logistic and Poisson regression. Applications to experimental and observational data.
Offered by: Mathematics and Statistics
-
MATH 427
Statistical Quality Control
3 Credits
Offered in the:
- Fall
- Winter
- Summer
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.
Offered by: Mathematics and Statistics
- Terms
- This course is not scheduled for the 2024-2025 academic year
- Instructors
- There are no professors associated with this course for the 2024-2025 academic year
-
MATH 447
Intro. to Stochastic Processes
3 Credits
Offered in the:
- Fall
- Winter
- Summer
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.
Offered by: Mathematics and Statistics
- Winter
- Prerequisite: MATH 323
- Restriction: Not open to students who have taken or are taking MATH 547.
-
MATH 523
Generalized Linear Models
4 Credits
Offered in the:
- Fall
- Winter
- Summer
Mathematics & Statistics (Sci): Exponential families, link functions. Inference and parameter estimation for generalized linear models; model selection using analysis of deviance. Residuals. Contingency table analysis, logistic regression, multinomial regression, Poisson regression, log-linear models. Multinomial models. Overdispersion and Quasilikelihood.
Applications to experimental and observational data.
Offered by: Mathematics and Statistics
-
MATH 524
Nonparametric Statistics
4 Credits
Offered in the:
- Fall
- Winter
- Summer
Mathematics & Statistics (Sci): Distribution free procedures for 2-sample problem: Wilcoxon rank sum, Siegel-Tukey, Smirnov tests. Shift model: power and estimation. Single sample procedures: Sign, Wilcoxon signed rank tests. Nonparametric ANOVA: Kruskal-Wallis, Friedman tests. Association: Spearman's rank correlation, Kendall's tau. Goodness of fit: Pearson's chi-square, likelihood ratio, Kolmogorov-Smirnov tests. Statistical software packages used.
Offered by: Mathematics and Statistics
- Fall
- Prerequisite: MATH 324 or equivalent
- Restriction: Not open to students who have taken MATH 424
-
MATH 525
Sampling Theory & Applications
4 Credits
Offered in the:
- Fall
- Winter
- Summer
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.
Offered by: Mathematics and Statistics
- Prerequisite: MATH 324 or equivalent
- Restriction: Not open to students who have taken MATH 425
-
MATH 527D1
Stat. Data Science Practicum
3 Credits*
Offered in the:
- Fall
- Winter
- Summer
Mathematics & Statistics (Sci): The holistic skills required for doing statistical data science in practice. Data science life cycle from a statistics-centric perspective and from the perspective of a statistician working in the larger data science environment. Group-based projects with industry, government, or university partners. Statistical collaboration and consulting conducted in coordination with the Data Science Solutions Hub (DaS^2H) of the Computational and Data Systems Initiative (CDSI).
Offered by: Mathematics and Statistics
- Terms
- Instructors
- Jose Andres Correa, Eric Kolaczyk
-
MATH 527D2
Stat. Data Science Practicum
3 Credits*
Offered in the:
- Fall
- Winter
- Summer
Mathematics & Statistics (Sci): See MATH 527D1 for course description.
Offered by: Mathematics and Statistics
- Terms
- Instructors
- Jose Andres Correa, Eric Kolaczyk
-
MATH 545
Intro to Time Series Analysis
4 Credits
Offered in the:
- Fall
- Winter
- Summer
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.
Offered by: Mathematics and Statistics
-
MATH 556
Mathematical Statistics 1
4 Credits
Offered in the:
- Fall
- Winter
- Summer
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.
Offered by: Mathematics and Statistics
- Terms
- Instructors
- Abbas Khalili Mahmoudabadi
-
MATH 557
Mathematical Statistics 2
4 Credits
Offered in the:
- Fall
- Winter
- Summer
Mathematics & Statistics (Sci): Sufficiency, minimal and complete sufficiency, ancillarity. Fisher and Kullback-Leibler
information. Elements of decision theory. Theory of estimation and hypothesis testing from the Bayesian and frequentist perspective. Elements of asymptotic statistics including large-sample behaviour of maximum likelihood estimators, likelihood-ratio tests, and chi-squared goodness-of-fit tests.
Offered by: Mathematics and Statistics
-
MATH 558
Design of Experiments
4 Credits
Offered in the:
- Fall
- Winter
- Summer
Mathematics & Statistics (Sci): Introduction to concepts in statistically designed experiments. Randomization and replication. Completely randomized designs. Simple linear model and analysis of
variance. Introduction to blocking. Orthogonal block designs. Models and analysis for block designs. Factorial designs and their analysis. Row-column designs. Latin squares. Model and analysis for fixed row and column effects. Split-plot designs, model and analysis. Relations and operations on factors. Orthogonal factors. Orthogonal decomposition. Orthogonal plot structures. Hasse diagrams. Applications to real data and ethical issues.
Offered by: Mathematics and Statistics
-
MATH 559
Bayesian Theory and Methods
4 Credits
Offered in the:
- Fall
- Winter
- Summer
Mathematics & Statistics (Sci): Subjective probability, Bayesian statistical inference and decision making, de Finetti’s representation. Bayesian parametric methods, optimal decisions, conjugate
models, methods of prior specification and elicitation, approximation methods. Hierarchical models. Computational approaches to inference, Markov chain
Monte Carlo methods, Metropolis—Hastings. Nonparametric Bayesian inference.
Offered by: Mathematics and Statistics
- Terms
- This course is not scheduled for the 2024-2025 academic year
- Instructors
- There are no professors associated with this course for the 2024-2025 academic year
-
MATH 598
Topics in Probability & Stats
4 Credits
Offered in the:
- Fall
- Winter
- Summer
Mathematics & Statistics (Sci): This course covers a topic in probability and/or statistics.
Offered by: Mathematics and Statistics
- Prerequisite(s): At least 30 credits in required or complementary courses from the Honours in Probability and Statistics program including MATH 356. Additional prerequisites may be imposed by the Department of Mathematics and Statistics depending on the nature of the topic.
- Restriction(s): Requires permission of the Department of Mathematics and Statistics.
- Terms
- Instructors
- Louigi Dana Addario-Berry, Johanna Neslehova
- Masoud Asgharian, Abbas Khalili Mahmoudabadi
-
WCOM 314
Communicating Science
3 Credits*
Offered in the:
- Fall
- Winter
- Summer
Written and Oral Communication: Production of written and oral assignments (in English) designed to communicate scientific problems and findings to varied audiences Analysis of the disciplinary conventions of scientific discourse in terms of audience, purpose, organization, and style; comparative rhetorical analysis of academic and popular genres, including abstracts, lab reports, research papers, print and online journalism.
Offered by: McGill Writing Centre
- Restriction: Not open to students who have taken CCOM 314.