Academic Calendar - 2021

Western University Academic Calendar. - 2021

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 Honours Specialization module or Double Major modules in an Honours Bachelor degree, at least 3.0 courses will be considered principal courses.



Campus





Course Level






Course Type




Analytics and Decision Sciences


Decision analysis, linear programming, integer programming, dynamic programming, introduction to computer programming, statistical distributions, Markov chains, Monte Carlo simulation, queuing, discrete event simulation. Students will use a variety of tools to investigate applications including transportation networks, revenue management, and sports analytics.


Prerequisite(s): 1.0 course from: Applied Mathematics 1412A/B, the former Applied Mathematics 1413, Applied Mathematics 1414A/B, Calculus 1000A/B, Calculus 1301A/B, Calculus 1501A/B, Mathematics 1120A/B, Mathematics 1225A/B, Mathematics 1228A/B, Mathematics 1229A/B, Mathematics 1230A/B, Mathematics 1600A/B, and Statistical Sciences 1024A/B, and 0.5 from: Economics 2122A/B, Economics 2222A/B, Statistical Sciences 2035, Statistical Sciences 2141A/B, Statistical Sciences 2857A/B, or by permission of the School 1.0 credits in statistics or a quantitative research methods (e.g., Psychology 2840F/G, Psychology 3891F/G, Psychology 3892F/G, Sociology 2205A/B, Sociology 2206A/B) at the 2000 level or above.

Extra Information: 3 lecture hours, 2 lab hours.

Course Weight: 0.50
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Stochastic optimization modelling, decision making under uncertainty, simulation modelling, regression and forecasting models and data mining.


Extra Information: 3 lecture hours, 1 lab hour.

Course Weight: 0.50
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Statistical programming in a high-level language, data visualization design principles, extracting insights from data visualization, data mining and machine learning, data classification; visualization of multivariate, time-series, and hierarchical data. Currently using R including ggplot2 and other relevant packages.

Antirequisite(s): Statistical Sciences 2864A/B.


Extra Information: 3 lecture hours, 2 lab hours.

Course Weight: 0.50
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Practical analytics and software tools explored through case analyses. Linear programming, statistical analysis, decision analysis, game theory, inventory analysis, queuing theory, simulation, Markovian decision model, and forecasting will be applied in a variety of scenarios.


Extra Information: 3 hours, 1 lab hour.

Course Weight: 0.50
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Heuristics, satisficing, disruptive logic, and entrepreneurial thinking are explored and applied to concrete problems that do not fit into well-established frameworks. An intensive experiential learning component involves a 10-day group problem-solving project done in consultation with a not-for-profit, educational, private, or government partner.

Prerequisite(s): Registration in any Honours Specialization or Honours Double-Major at King’s University College, and completion of Philosophy 2293A/B.

Extra Information: 3 hours.

Course Weight: 0.50
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