Academic Calendar - 2018

Western University Academic Calendar. - 2018

Courses


Course Numbering

0001-0999* Pre-University level introductory courses
1000-1999 Year 1 courses
2000-4999 Senior-level undergraduate courses
5000-5999 Professional Degree courses in Dentistry, Education, Law, Medicine and Theology (MTS, MDiv)
6000-6999 Courses offered by Continuing Studies
9000-9999 Graduate Studies courses

* These courses are equivalent to pre-university introductory courses and may be counted for credit in the student's record, unless these courses were taken in a preliminary year. They may not be counted toward essay or breadth requirements, or used to meet modular admission requirements unless it is explicitly stated in the Senate-approved outline of the module.


Suffixes

no suffix 1.0 course not designated as an essay course
A 0.5 course offered in first term
B 0.5 course offered in second term
A/B 0.5 course offered in first and/or second term
E 1.0 essay course
F 0.5 essay course offered in first term
G 0.5 essay course offered in second term
F/G 0.5 essay course offered in first and/or second term
H 1.0 accelerated course (8 weeks)
J 1.0 accelerated course (6 weeks)
K 0.75 course
L 0.5 graduate course offered in summer term (May - August)
Q/R/S/T 0.25 course offered within a regular session
U 0.25 course offered in other than a regular session
W/X 1.0 accelerated course (full course offered in one term)
Y 0.5 course offered in other than a regular session
Z 0.5 essay course offered in other than a regular session

Glossary


Prerequisite

A course that must be successfully completed prior to registration for credit in the desired course.


Corequisite

A course that must be taken concurrently with (or prior to registration in) the desired course.


Antirequisite

Courses that overlap sufficiently in course content that both cannot be taken for credit.


Essay Courses

Many courses at Western have a significant writing component. To recognize student achievement, a number of such courses have been designated as essay courses and will be identified on the student's record (E essay full course; F/G/Z essay half-course).


Principal Courses

A first year course that is listed by a department offering a module as a requirement for admission to the module. For admission to an Honors Specialization module or Double Major modules in an Honors Bachelor degree, at least 3.0 courses will be considered principal courses.



Campus





Course Level






Course Type




Statistical Sciences


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.

Antirequisite(s): Statistical Sciences 2037A/B.

Extra Information: Offered in two formats: 3 lecture hours, or weekly online lectures and 2 in-class lab hours.

Course Weight: 0.50
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Statistical inference, experimental design, sampling design, confidence intervals and hypothesis tests for means and proportions, regression and correlation.

Antirequisite(s): All other courses or half courses in Introductory Statistics, except Statistical Sciences 1023A/B and Statistical Sciences 2037A/B.

Prerequisite(s): Grade 12U Mathematics or Mathematics 0110A/B or Mathematics 1229A/B.

Extra Information: Offered in two formats: 3 lecture hours, or weekly online lectures and 2 in-class lab hours (Main); 3 lecture hours (Huron, King's).

Course Weight: 0.50
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This course is also offered at:

Huron King's

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Statistical inference, experimental design, sampling design, confidence intervals and hypothesis tests for means and proportions, regression and correlation.

Antirequisite(s): All other courses or half courses in Introductory Statistics, except Statistical Sciences 1023A/B and Statistical Sciences 2037A/B.

Extra Information: Offered in two formats: 3 lecture hours, or weekly online lectures and 2 in-class lab hours (Main); 3 lecture hours (Huron, King's).

Course Weight: 0.50
More details

This course is also offered at:

Western Main Campus King's

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Statistical inference, experimental design, sampling design, confidence intervals and hypothesis tests for means and proportions, regression and correlation.

Antirequisite(s): All other courses or half courses in Introductory Statistics, except Statistical Sciences 1023A/B and Statistical Sciences 2037A/B.

Prerequisite(s): Grade 12U Mathematics or Mathematics 0110A/B or Mathematics 1229A/B.

Extra Information: Offered in two formats: 3 lecture hours, or weekly online lectures and 2 in-class lab hours (Main); 3 lecture hours (Huron, King's).

Course Weight: 0.50
More details

This course is also offered at:

Western Main Campus Huron

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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.



Extra Information: 3 lecture hours.

Course Weight: 1.00
More details

This course is also offered at:

King's

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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.



Extra Information: 3 lecture hours.

Course Weight: 1.00
More details

This course is also offered at:

Western Main Campus

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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 health-related applications.

Antirequisite(s) at Main campus: Statistical Sciences 1023A/B. Antirequisite(s) at Huron: All other courses or half courses in Introductory Statistics.

Extra Information: Offered in two formats: 3 lecture hours, or weekly online lectures and 2 in-class lab hours (Main); 3 lecture hours (Huron). Note at Main campus: Cannot be taken for credit by students registered in the Faculty of Science and Schulich School of Medicine and Dentistry with the exception of students in Food and Nutrition.

Course Weight: 0.50
More details

This course is also offered at:

Huron

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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 health-related applications.

Antirequisite(s) at Main campus: Statistical Sciences 1023A/B. Antirequisite(s) at Huron: All other courses or half courses in Introductory Statistics.

Extra Information: Offered in two formats: 3 lecture hours, or weekly online lectures and 2 in-class lab hours (Main); 3 lecture hours (Huron). Note at Main campus: Cannot be taken for credit by students registered in the Faculty of Science and Schulich School of Medicine and Dentistry with the exception of students in Food and Nutrition.

Course Weight: 0.50
More details

This course is also offered at:

Western Main Campus

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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 3-year or honors program or in any module in Statistics, Actuarial Science, or Financial Modelling.


Prerequisite(s): Applied Mathematics 1413, or 0.5 course from Calculus 1000A/B, the former Calculus 1100A/B or Calculus 1500A/B plus 0.5 course from either Calculus 1301A/B or Calculus 1501A/B.

Extra Information: 3 lecture hours, 1 tutorial hour.

Course Weight: 0.50
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A data-driven introduction to statistics intended primarily for students in Chemical and Mechanical Engineering. Exploratory data analysis, probability, the Binomial, Poisson, Normal, Chi-Square 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.


Prerequisite(s): Applied Mathematics 1413, or 0.5 course from Calculus 1000A/B, the former Calculus 1100A/B or Calculus 1500A/B plus 0.5 course from either Calculus 1301A/B or Calculus 1501A/B.

Extra Information: 3 lecture hours, 1 tutorial hour.

Course Weight: 0.50
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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.

Extra Information: 2 lecture hours, 3 lab hours.

Course Weight: 0.50
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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, Chapman-Kolmogorov equations, ergodic theorems.

Antirequisite(s): The former Applied Mathematics 2503A/B.

Prerequisite(s): Calculus 2402A/B or (Calculus 2502A/B and Calculus 2503A/B) or (Calculus 2502A/B and Mathematics 2123A/B), Mathematics 1600A/B (or the former Linear Algebra 1600A/B) or Applied Mathematics 1411A/B, Statistical Sciences 2857A/B (or the former Statistical Sciences 2657A), or Economics 2122A/B. In each course a minimum mark of 60% is required.

Extra Information: 3 lecture hours.

Course Weight: 0.50
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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.

Prerequisite(s): A minimum mark of 60% in 0.5 course from (Calculus 1000A/B or Calculus 1500A/B) plus 0.5 course from Calculus 1301A/B (minimum mark 85%) or Calculus 1501A/B (minimum mark 60%). A minimum mark of 60% in Applied Mathematics 1413 may also be used to meet this 1.0 course prerequisite.

Extra Information: 3 lecture hours, 1 tutorial hour.

Course Weight: 0.50
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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.


Prerequisite(s): A minimum mark of 60% in Statistical Sciences 2857A/B (or the former Statistical Sciences 2657A/B).

Extra Information: 3 lecture hours, 1 tutorial hour.

Course Weight: 0.50
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An introduction to programming using a high level language (currently R).

Prerequisite(s): A minimum mark of 60% in Statistical Sciences 2857A/B (or the former Statistical Sciences 2657A/B). Pre-or Corequisite(s): Statistical Sciences 2858A/B.

Extra Information: 3 lecture hours, 1 tutorial hour.

Course Weight: 0.50
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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.

Prerequisite(s): A minimum mark of 60% in Statistical Sciences 2858A/B and in Statistical Sciences 2503A/B (or the former Applied Mathematics 2503A/B) or Calculus 2503A/B.

Extra Information: 3 lecture hours, 1 tutorial hour.

Course Weight: 0.50
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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.

Prerequisite(s): A minimum mark of 60% in Statistical Sciences 2858A/B.

Extra Information: 3 lecture hours.

Course Weight: 0.50
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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.

Prerequisite(s): A minimum mark of 60% in Statistical Sciences 2858A/B.

Extra Information: 2 lecture hours, 1 laboratory hours.

Course Weight: 0.50
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Point estimation: sufficiency, completeness, consistency, unbiasedness, Cramer-Rao inequality, Rao-Blackwell theorem, Hypotheses tests: uniformly most powerful tests, likelihood ratio tests.

Prerequisite(s): A minimum mark of 60% in Statistical Sciences 3657A/B.

Extra Information: 3 lecture hours, 1 tutorial hour.

Course Weight: 0.50
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Multiple linear regression, Gauss-Markov theorem, Cochran's theorem, Craig's theorem, stepwise regression, polynomial regression, use of indicator variables, and regression diagnostics.

Prerequisite(s): A minimum mark of 60% in Statistical Sciences 2858A/B.

Extra Information: 3 lecture hours, 1 tutorial hour.

Course Weight: 0.50
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Estimation and tests for generalized linear models, including residual analysis and the use of statistical packages. Logistic regression, log-linear models. Additional topics may include generalized estimating equations, quasi-likelihood and generalized additive models.

Prerequisite(s): Statistical Sciences 3859A/B with at least 60%.

Extra Information: 3 lecture hours.

Course Weight: 0.50
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Continuous-time Markov chains, applications to phase-type 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.

Prerequisite(s): A minimum mark of 60% in Statistical Sciences 3657A/B.

Extra Information: 3 lecture hours.

Course Weight: 0.50
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An introduction to the interpersonal techniques of statistical consulting, including methodologies for data analysis common to many consulting problems and ethics, in the context of the cycle of Problem, Plan, Data, Analysis and Conclusion. A large portion of the course will be conducted in a seminar format with student participation.

Prerequisite(s): Statistical Sciences 3859A/B with at least 60%.

Extra Information: 3 lecture hours. Note: This course is restricted to students enrolled in the Honors Specialization module in Data Science.

Course Weight: 0.50
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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.


Extra Information: 3 lecture hours.

Course Weight: 0.50
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Modern methods of data analysis including linear and generalized linear models, modern nonparametric regression, principal component analysis, multilevel modelling and bootstrapping.

Prerequisite(s): A minimum mark of 60% in both Statistical Sciences 3843A/B and Statistical Sciences 3859A/B.

Extra Information: 3 lecture hours.

Course Weight: 0.50
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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.


Extra Information: 3 lecture hours.

Course Weight: 0.50
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A review of multiple regression including assumptions, estimation and inference, diagnostics, and modelling with factors. Variable selection techniques including cross-validation. Smoothing techniques, generalized additive models, and the incorporation of random effects and/or serial auto-correlated error structures.

Prerequisite(s): Statistical Sciences 3859A/B.

Extra Information: 3 lecture hours.

Course Weight: 0.50
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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.

Prerequisite(s): A minimum mark of 60% in both Statistical Sciences 3858A/B and Statistical Sciences 2864A/B.

Extra Information: 3 lecture hours.

Course Weight: 0.50
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Review of fundamental concepts in statistical computing, including programming, optimization methods and Monte Carlo simulations. A selection of advanced topics such as bootstrapping, robust methods, statistical graphics, Markov chain Monte Carlo, nonlinear regression, relational databases, time series analysis, and spatial statistics.


Extra Information: 3 lecture hours.

Course Weight: 0.50
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A course description will be available from the department at the time of registration.

Prerequisite(s): A minimum mark of 60% in Statistical Sciences 3657A/B (or the former Statistical Sciences 2657A/B) or permission of the department.

Extra Information: 3 lecture hours, 1 tutorial hour.

Course Weight: 0.50
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A course description will be available from the department at the time of registration.

Prerequisite(s): A minimum mark of 60% in Statistical Sciences 3657A/B and permission of the department.

Extra Information: 3 lecture hours.

Course Weight: 0.50
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This course aims to develop important business skills that are often not emphasized in the formal education of quantitative financial professionals. The course focuses on four main topic areas: how businesses work, financial statement analysis, oral and written communications skills, and leadership and people management.

Prerequisite(s): Registration in fourth year of an Actuarial Science, Data Science, Statistics or Financial Modeling module.

Extra Information: 3 lecture hours.

Course Weight: 0.50
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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.

Antirequisite(s): Actuarial Science 4997F/G/Z, Financial Modelling 4998F/G/Z, the former Statistical Sciences 4998F/G/Z.

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.

Course Weight: 0.50
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