Descriptive and inferential statistics, elementary probability, probability distributions, estimation of parameters, hypotheses testing, correlation, linear regression. Credit will be granted for only one of STAT 121 or STAT 124. [3-0-0] Prerequisite: Either (a) a score of 60% or higher in one of MATH 125, MATH 126 or (b) a score of 67% or higher in one of MATH 12, PREC 12.
Introduction to surveys and simple sampling strategies; descriptive methods for one and two variables; frequency distributions; correlation and regression; descriptive methods for time series and index numbers; and probability and relationship to statistical inference. Good for CA, CMA credit. Credit will be granted for only one of STAT 121, STAT 124. [3-0-0] Prerequisite: One of Principles of Mathematics 11, Pre-Calculus 11, Foundations of Mathematics 12.
Combinatorics. Axioms of probability. Discrete and continuous random variables, expectation, and variance. Transformations. Central limit theorem and applications. Weak law of large numbers. Credit will be granted for only one of STAT 203 or STAT 230. [3-0-0] Prerequisite: One of MATH 101, MATH 103, MATH 142. Corequisite: DATA 101.
Sampling distribution theory. Likelihood. Parameter estimation. Confidence intervals and hypothesis testing; simple regression, analysis of variance and contingency table analysis. Credit will be granted for only one of STAT 205 or STAT 230. [3-0-0] Prerequisite: STAT 203.
Applied statistics for students with a first-year calculus background. Estimation and testing of hypotheses, problem formulation, models and basic methods in analysis of variance, linear regression, and non-parametric methods. Descriptive statistics and probability are presented as a basis for such procedures. [3-0-0] Prerequisite: One of MATH 101, MATH 103, MATH 142 and one of DATA 101, COSC 221.
Multivariate probability distributions, moment and generating functions. [3-0-0] Prerequisite: All of MATH 200, STAT 203.
Simple and compound interest, discount, force of interest, simple and general annuities, amortization of debts, bonds, depreciation, mortality tables, contingent payments, life annuities, insurance, and an introduction to financial derivatives. Credit will be granted for only one of STAT 324 and STAT 224. [3-0-0] Prerequisite: MATH 200 and one of STAT 205, STAT 230.
Development of broad guidelines for a comprehensive approach to data analysis with a focus on communicating statistical ideas from planning experiments to the presentation of results. Topics include criteria for selection of suitable methodologies, data preparation, outlier detection, and exploratory data analysis. Credit will be granted for only one of DATA 500 or STAT 400 when the subject matter is of the same nature. [3-0-0] Prerequisite: DATA 310. DATA 315 is strongly recommended.
Theory of statistical modelling: distributions of data, likelihood-based inference for learning unknown parameters, construction of confidence intervals and development of tests. Bayesian methods will be used to contrast standard statistical procedures. [3-0-0] Prerequisite: STAT 303.
Random walks, Markov chains, Poisson processes, continuous time Markov chains, birth and death processes, exponential models, and applications of Markov chains. [3-0-0] Prerequisite: STAT 303.
Statistical concepts and methods in environmental science and management. Scientific problem-solving using statistical methods. Integration of the formulation of objectives, study design, and quantitative methods appropriate for the design. The role and use of statistical software packages. [3-0-0] Prerequisite: DATA 310.
Investigation of a specific topic as agreed upon by the student and the faculty supervisor. Completion of a project and an oral presentation are required. No more than 6 credits of STAT 448 may be taken for credit. Prerequisite: Successful completion of 15 credits of 300- or 400-level MATH and STAT courses; and permission of the department head and faculty supervisor.
Students should consult with the unit to determine the availability of specific topics to be offered under the direction of a staff member. May be taken more than once with different topics. Prerequisite: Permission of the department head.
Collection of data using either designed experiments or survey samples. Planning and practice of data collection. Observational and experimental data pros and cons. Standard methods in survey samples. Experimental design review. Credit will be granted for only one of DATA 407, or STAT 507.
Least-squares, generalized least-squares and likelihood estimation. Theory and application of parametric and non-parametric regression models such as splines, penalized splines, and generalized additive models. Assessment and treatment of data issues including missingness and measurement error. Credit will be granted for only one of DATA 410, or STAT 538. [3-2-0]
Topics chosen from different areas within the field of statistics, such as time series, longitudinal and multi-level modelling, multivariate analysis, machine learning, resampling and permutation methods, smoothing and filtering, survival analysis, sports analytics and spatial statistics. Content will be determined so as to complement course offerings and meet the needs of the students. With the permission of the department head, this course may be taken more than once on a different topic. [3-0-0]
Theory of probability, including random variables, expectation, conditional expectation, generating functions, modes of convergence of random variables and their distributions. Applications to random models such as Markov, Poisson, birth-death, Gaussian and diffusion processes. [3-0-0]