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Minor Concentration Statistics (18 credits)

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Offered by: Mathematics and Statistics     Degree: Bachelor of Arts and Science

Program Requirements

The Minor Concentration Statistics is offered only in a non-expandable version, that is, one that cannot be expanded into the Major Concentration Mathematics.

The Minor Concentration Statistics may be taken in conjunction with a major concentration in some other discipline under option A of the Multi-track System, or together with the Major Concentration Mathematics and a minor concentration (which must be in some other discipline than Mathematics) under option C.

Under option C, it is not possible to combine the Minor Concentration Statistics and the Minor Concentration Mathematics. Students wishing to do this should instead take the Major Concentration Mathematics under option B (two major concentrations) and select a large number of statistics complementaries.

For more information about the Multi-track System options please refer to the Faculty of Arts regulations under "Faculty Degree Requirements", "About Program Requirements", and "Departmental Programs".

No overlap is permitted with other programs.

Program Prerequisites

Students who have not completed the program prerequisite courses listed below or their equivalents will be required to make up any deficiencies in these courses over and above the 18 credits required for the program.

  • MATH 133 Linear Algebra and Geometry (3 credits)

    Offered by: Mathematics and Statistics (Faculty of Science)

    Overview

    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; quadratic loci in two and three dimensions.

    Terms: Fall 2014, Winter 2015, Summer 2015

    Instructors: Cornwell, Christopher; Kelome, Djivede; Trudeau, Sidney; Brandenbursky, Michael (Fall) Kelome, Djivede; Trudeau, Sidney (Winter) Elias, Yara (Summer)

    • 3 hours lecture, 1 hour tutorial

    • Prerequisite: a course in functions

    • Restriction A: Not open to students who have taken MATH 221 or CEGEP objective 00UQ or equivalent.

    • Restriction B: Not open to students who have taken or are taking MATH 123, MATH 130 or MATH 131, except by permission of the Department of Mathematics and Statistics.

    • Restriction C: Not open to students who are taking or have taken MATH 134.

  • MATH 140 Calculus 1 (3 credits)

    Offered by: Mathematics and Statistics (Faculty of Science)

    Overview

    Mathematics & Statistics (Sci) : Review of functions and graphs. Limits, continuity, derivative. Differentiation of elementary functions. Antidifferentiation. Applications.

    Terms: Fall 2014, Winter 2015, Summer 2015

    Instructors: Hundemer, Axel W; Drury, Stephen W; Conlon, Ronan (Fall) Aleyasin, Seyed Ali (Winter) McGregor, Geoffrey (Summer)

    • 3 hours lecture, 1 hour tutorial

    • Prerequisite: High School Calculus

    • Restriction: Not open to students who have taken MATH 120, MATH 139 or CEGEP objective 00UN or equivalent

    • Restriction: Not open to students who have taken or are taking MATH 122 or MATH 130 or MATH 131, except by permission of the Department of Mathematics and Statistics

    • Each Tutorial section is enrolment limited

  • MATH 141 Calculus 2 (4 credits)

    Offered by: Mathematics and Statistics (Faculty of Science)

    Overview

    Mathematics & Statistics (Sci) : The definite integral. Techniques of integration. Applications. Introduction to sequences and series.

    Terms: Fall 2014, Winter 2015, Summer 2015

    Instructors: Fox, Thomas F (Fall) Haug, Luis; Hundemer, Axel W; Conlon, Ronan (Winter) Zwicker, Justine; Ehlen, Stephan (Summer)

    • Prerequisites: MATH 139 or MATH 140 or MATH 150.

    • Restriction: Not open to students who have taken MATH 121 or CEGEP objective 00UP or equivalent

    • Restriction Note B: Not open to students who have taken or are taking MATH 122 or MATH 130 or MATH 131, except by permission of the Department of Mathematics and Statistics.

    • Each Tutorial section is enrolment limited

Required Courses (15 credits)

* Note: If the Minor Concentration Statistics is combined with the Major Concentration Mathematics, the required courses MATH 222, MATH 223 and MATH 323 must be replaced by courses selected from the Complementary Courses. Credit cannot be received for both MATH 223 and MATH 236 (listed as a required course in the Major Concentration Mathematics).

  • MATH 222 Calculus 3 (3 credits) *

    Offered by: Mathematics and Statistics (Faculty of Science)

    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 2014, Winter 2015, Summer 2015

    Instructors: Brandenbursky, Michael; Xu, Jian-Jun (Fall) Tsogtgerel, Gantumur (Winter) Eswarathasan, Suresh (Summer)

  • MATH 223 Linear Algebra (3 credits) *

    Offered by: Mathematics and Statistics (Faculty of Science)

    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 2014, Winter 2015

    Instructors: Ehlen, Stephan (Fall) Saldanha Salvador, Tiago Miguel (Winter)

    • 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 323 Probability (3 credits) *

    Offered by: Mathematics and Statistics (Faculty of Science)

    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 2014, Winter 2015, Summer 2015

    Instructors: Anderson, William J (Fall) Kelome, Djivede (Winter) Kelome, Djivede (Summer)

    • 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

  • MATH 324 Statistics (3 credits)

    Offered by: Mathematics and Statistics (Faculty of Science)

    Overview

    Mathematics & Statistics (Sci) : Sampling distributions, point and interval estimation, hypothesis testing, analysis of variance, contingency tables, nonparametric inference, regression, Bayesian inference.

    Terms: Fall 2014, Winter 2015

    Instructors: Genest, Christian (Fall) Steele, Russell (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.

  • MATH 423 Regression and Analysis of Variance (3 credits)

    Offered by: Mathematics and Statistics (Faculty of Science)

    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 2014

    Instructors: Stephens, David (Fall)

Complementary Courses (3 credits)

3 credits from:

  • COMP 202 Foundations of Programming (3 credits)

    Offered by: Computer Science (Faculty of Science)

    Overview

    Computer Science (Sci) : Introduction to programming in a modern high-level language, modular software design and debugging. Programming concepts are illustrated using a variety of application areas.

    Terms: Fall 2014, Winter 2015, Summer 2015

    Instructors: Lyman-Abramovitch, Melanie; Gamboa Higuera, Juan Camilo; Tremblay, Jonathan (Fall) Tremblay, Jonathan; Cheung, Jackie; Oakes, Bentley (Winter) Manjanna, Sandeep (Summer)

    • 3 hours

    • Prerequisite: a CEGEP level mathematics course

    • Restrictions: COMP 202 and COMP 208 cannot both be taken for credit. COMP 202 is intended as a general introductory course, while COMP 208 is intended for students interested in scientific computation. COMP 202 cannot be taken for credit with or after COMP 250

  • MATH 204 Principles of Statistics 2 (3 credits)

    Offered by: Mathematics and Statistics (Faculty of Science)

    Overview

    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.

    Terms: Winter 2015

    Instructors: Wallace, Michael (Winter)

    • 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 317 Numerical Analysis (3 credits)

    Offered by: Mathematics and Statistics (Faculty of Science)

    Overview

    Mathematics & Statistics (Sci) : Error analysis. Numerical solutions of equations by iteration. Interpolation. Numerical differentiation and integration. Introduction to numerical solutions of differential equations.

    Terms: Fall 2014

    Instructors: Wan, Andy (Fall)

  • MATH 427 Statistical Quality Control (3 credits)

    Offered by: Mathematics and Statistics (Faculty of Science)

    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 2014-2015 academic year.

    Instructors: There are no professors associated with this course for the 2014-2015 academic year.

  • MATH 447 Introduction to Stochastic Processes (3 credits)

    Offered by: Mathematics and Statistics (Faculty of Science)

    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 2015

    Instructors: Wolfson, David B (Winter)

    • 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 by: Mathematics and Statistics (Faculty of Science)

    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 2015

    Instructors: Steele, Russell (Winter)

    • Winter

    • Prerequisite: MATH 423

    • Restriction: Not open to students who have taken MATH 426

  • MATH 524 Nonparametric Statistics (4 credits)

    Offered by: Mathematics and Statistics (Faculty of Science)

    Overview

    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.

    Terms: Fall 2014

    Instructors: Genest, Christian (Fall)

    • Fall

    • Prerequisite: MATH 324 or equivalent

    • Restriction: Not open to students who have taken MATH 424

  • MATH 525 Sampling Theory and Applications (4 credits)

    Offered by: Mathematics and Statistics (Faculty of Science)

    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: This course is not scheduled for the 2014-2015 academic year.

    Instructors: There are no professors associated with this course for the 2014-2015 academic year.

    • Prerequisite: MATH 324 or equivalent

    • Restriction: Not open to students who have taken MATH 425

Bachelor of Arts & Science—2014-2015 (last updated Feb. 18, 2014) (disclaimer)
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