Graduate academic calendar 2012 - 2013 - Trent University

GRADUATE PROGRAMS Applied Modelling & Quantitative Methods
47
member must have been identified who will supervise the student’s work. Prospective students must
have a university course in differential and integral calculus, and one in probability and statistics
or the equivalent. Students will also have some familiarity with linear algebra, and be capable
of programming at an elementary level in at least one computational language. In addition, a
course in either differential equations or advanced statistics is required, depending on whether the
student’s area of research will be mathematics or statistics based. Students are involved both in
course work and thesis research in their home discipline and in interdisciplinary study. Coursework
in the foundations and methods of quantitative modelling and in their home discipline consists of
about one-third of the work towards the degree. Each student must satisfactorily complete at least
four one-term modelling courses, consisting of two courses in the foundations and mathematical
aspects of modelling, and two courses in the home discipline. The required course work is normally
completed in two terms, allowing the Summer sessions and the entire second year to be devoted to
uninterrupted research. Students also participate in an interdisciplinary seminar on modelling and
make one presentation each year. In this seminar the student discusses, in a way comprehensible to
the audience, the system being modelled, the model developed and the means of validation of the
model; here the emphasis is upon the modelling process itself rather than on the relevance of the
results to the discipline of the research. Through this seminar the students develop the skills required
to communicate with researchers outside their own discipline, and develop a perspective on their
own and other disciplines not obtainable within a single-discipline context. Candidates are required
to submit and be examined on a research thesis supervised by one of the core faculty listed above.
Selection of the research topic is made by the student together with her/his supervisor and graduate
supervisory committee (typically two or three core faculty members including the supervisor.) A
grade of at least B- (70) must be obtained in each of the graduate courses. For further details, see
Failed Course Policy. The expected time for completion of the degree is two years.
FINANCIAL SUPPORT
All students accepted are offered a teaching assistantship and a research fellowship. These stipends
are frequently increased by research stipends provided from faculty’s research funds. The program
also provides funds to cover minor overhead research costs such as laboratory and computing
supplies, equipment and some conference travel. Canadian candidates are encouraged to apply,
before the middle of October, for national and provincial scholarships (NSERC, SSHRC and OGS
awards).
For further information on financial support for graduate students, please refer to the graduate
studies website: www.trentu.ca/graduatestudies/financialsupport.php.
Not all courses will be available every year. Please consult www.trentu.ca/amod for
information on courses that will be offered for the upcoming academic year.
All courses listed are one-term courses. Students are normally required to take AMOD 5010H, 5020H,
5610H and one of 5510H, 5710H or 5810H. Students with advanced preparation in the material
covered in any of 5510H, 5610H or 5710H may appeal to take the corresponding advanced course
instead: 5520H, 5620H, 5720H and 5820H respectively.
AMOD 5010H, AMOD 5020H, AMOD 5030H
Discipline-specific courses in the home department. These may be given by the research supervisor in
a reading/project course format.
AMOD 5510H – Statistical aspects of modelling
Various statistical approaches to modelling are illustrated, with an emphasis on the applications of
statistics within the social and natural sciences. The course discusses both univariate and multivariate
procedures, with particular attention to the latter (e.g., multiple regression, multi-analysis of
variance, exploratory factor analysis, confirmatory factor analysis, and path analysis). Prerequisite: As
for AMOD 5610H, plus a university course in advanced statistics and some knowledge of SAS, SPSS
or an alternative statistical application package.
AMOD 5520H – Special topics in statistics of modelling
Prerequisite: AMOD 5510H or equivalent.