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You must meet the course requirements of the program to graduate from the PhD program in Mathematical and Statistical Modelling. The following courses are designed to fulfil application-oriented interdisciplinary goals and program-level learning outcomes of this program. They are divided into the following two groups – required and elective courses. Required courses contain learning outcomes dealing with the core set of skills in mathematical and statistical modelling that students working in any domain area require. Elective courses allow students to specialize their training needs according to norms within their chosen domain.

MA800: Comprehensive Examination (0.0 Credit)

This course is designed to assess the student's broad knowledge in foundational topics of Mathematical and Statistical Modelling at the honours undergraduate level. To demonstrate adequate knowledge of foundational topics, the candidate will be required to take and pass the comprehensive examination normally during the first year of registration in the program. The examination will be held in the spring term each year. Students must pass the comprehensive examination to continue in the program. 
One of the following two decisions will be made concerning the candidate's performance on the comprehensive examination:

  • Pass: If the majority of the Comprehensive Exam Committee (CEC) will be satisfied with the performance of a student on the exam.
  • Fail: In this case, a student may be allowed, at the discretion of the CEC to take the examination only one additional time for a total of two attempts. The examination may be repeated no later than six months from the date of the first examination. If the student does not receive a pass following the second attempt, the graduate coordinator will recommend to the Faculty of Graduate and Postdoctoral Studies that the student be terminated from the PhD program.

The CEC shall consist of five faculty members involved in the program, including at least three from the Department of Mathematics.

MA810: The Research Proposal and Qualifying Examination (0.5 Credit)

This course is required of PhD candidates to demonstrate broad knowledge in their research area in addition to their expertise in a specific research topic within one or more of the application domains of mathematical and statistical modelling. It is normally completed in the fourth term, and not later than in the fifth term, after entering the program. This examination comprises the following:

  • A written dissertation proposal (10 to 15 pages in length excluding a title page, references and appendices).
  • An oral presentation of the PhD research plan (20 to 30 minutes) in the presence of the Qualifying Exam Committee (QEC).
  • Open questioning of the student by the QEC to ascertain the readiness of the student to carry out the proposed research. The period for questions should not exceed 1.5 hours.

A written research proposal outlining the planned dissertation research must be submitted to the QEC at least two weeks before the date of the exam. There will be program guidelines for the format and content of the written proposal developed for all students. The graduate coordinator appoints an impartial chair for the research proposal and qualifying exam. The chair must be a member of the graduate faculty of the university. The QEC is composed of the Dean's Advisory Committee (DAC) and one member external to the program/unit. The DAC should ensure that this person is a member of the graduate faculty of the university, has expertise related to the subject of the dissertation, is willing to serve in this capacity, and is available to attend the research proposal presentation. The external member of the QEC is approved by the graduate coordinator. This person may then function as an “internal/external” examiner in the Dissertation Examination Committee (DEC).

Presentation and defence of the research proposal includes a student’s oral presentation summarizing the research proposal, which is followed by a period of questions from members of the audience, excluding the QEC. The final part of the examination will consist of questions from the QEC to the candidate, and will be performed in camera in the presence of the QEC and the chair. The examiners may ask questions related to the research proposal, which allow them to judge the student's mastery of relevant background knowledge for his/her dissertation topic, including an appropriate breadth of knowledge in the discipline and the student's ability to undertake independent and original research.

Based on the candidate’s defence of the research proposal and responses to questions, the QEC will render a pass/fail/deferred decision on the exam. Students must pass the research proposal and qualifying exam to continue in the program. Students will gain 0.5 credit if they pass the qualifying exam. If the student’s performance is deemed to be unsatisfactory (failed or decision deferred), the examination may be repeated no later than six months from the date of the first examination. If the student does not receive a pass following the second examination, the graduate coordinator will recommend to the Faculty of Graduate and Postdoctoral Studies that the student be terminated from the PhD program. 

MA820: Interdisciplinary Seminar in Modelling and Its Applications (0.0 Credit)

All students in the program must attend the Interdisciplinary Seminar in Modelling and Its Applications, which will typically run in the fall and winter terms, for the duration of their time in the program. The seminar will include presentations from guest speakers, as well as faculty from the program, and may occasionally be combined with the existing MS2Discovery Seminar Series events devoted to mathematical and statistical modelling. Such events frequently feature world-renowned researchers in all application domains of the program. This seminar not only will expose to our students the challenges of real-word problems, but also will teach them from first-hand experience how to communicate the modelling tools in the application domains with their own technical language. Students are also expected to attend other specialized research seminars, as appropriate. To document attendance of the interdisciplinary seminar, students are required to complete a brief statement indicating which presentations they attended (speaker name, institution, title, date) and a two to three sentence summary or critique of each seminar. This seminar attendance form shall be included in the annual report as an appendix. Students are required to attend a minimum of six presentations every year. Graded as complete/incomplete.

MA821: Research Seminar (0.5 Credit)

Students will be required to present his/her research at least once before graduation at the research seminar, normally in the third year of doctoral studies. This research seminar and the work on dissertation (typically under supervision of two experts, one from the home department and the other with specialized expertise in application domain involving modelling) will further consolidate students’ skills on how to communicate the modelling tools in the application domains with their own technical language. The research seminar is a public event and will be announced through the office of the graduate coordinator. It is required that all graduate students in the program attend these seminars.

MA880: Graduate Seminar in Mathematical and Statistical Modelling (0.5 Credit)

This seminar course is designed to develop the capacity to abstract salient features of problems in all three identified application domains of mathematical and statistical modelling, and to develop, analyze and interpret models. This course sets the tone by introducing the students to all aspects of modelling, including formulating a mathematical representation of the real-world problem of interest, solving that problem and interpreting the results in the context of the application domain. The commonality of mathematical and statistical methods and structures across disciplines is emphasized. Students work individually and in groups, and produce both written and oral reports on their projects.

MA899: PhD Dissertation (6.0 Credits)

As a requirement for graduation from the program, the student must prepare a dissertation on his or her original research in mathematical and statistical modelling within one or more of the application domains identified for this program, and present this dissertation to the DEC composed of the members of the DAC and at least one external examiner as described in the regulations and procedures for the doctoral dissertation section of the Laurier Graduate Calendar. The external examiner should be knowledgeable on the subject of the dissertation and at arm’s length from the candidate and the DAC. If the DAC does not include a member who is from outside the academic unit/program of the candidate, such a person must be nominated and approved for membership on the DEC no later than when the external examiner is nominated (this person would then function as an “internal/external” examiner). The external examiner and chair for the dissertation defence exam are suggested by the program coordinator and approved by the Faculty of Graduate and Postdoctoral Studies.