Note: 大发彩票平台鈥檚 new Course Catalogue will replace the eCalendar. The Course Catalogue is expected to go live the week of April 22nd. When the new site is published, "mcgill.ca/study" will be redirected to the new Course Catalogue website.
Course information on this site is not reflective of offerings for the 2025鈥�2026 academic year. Some irregularities may occur as we move operations to the incoming Course Catalogue.
The M.A. in Sociology; Gener and Women鈥檚 Studies provides advanced methodological training in sociology with an emphasis on issues in gender and women鈥檚 studies. The thesis must be on a topic relating to gender and women鈥檚 studies and approved by the supervisor and by participating faculty members in the Gender and Women鈥檚 Studies program
Preparation and completion of a thesis on a topic approved by the supervisor and by participating faculty members in the Gender and Women's Studies program.
Sociology (Arts) : Preparation, submission and approval of the thesis proposal by the student to his/her committee.
Terms: Fall 2024, Winter 2025
Instructors: There are no professors associated with this course for the 2024-2025 academic year.
Restriction: Open only to graduate students registered in the M.A. thesis program of the Sociology Department.
Sociology (Arts) : Fieldwork and data analysis on the thesis. Progress report to the supervisor.
Terms: Fall 2024, Winter 2025
Instructors: There are no professors associated with this course for the 2024-2025 academic year.
Restriction: Open only to graduate students registered in the M.A. thesis program of the Sociology Department.
Sociology (Arts) : Completion, submission, and approval of the M.A. Thesis by the committee and the Graduate and Postdoctoral Studies Office.
Terms: Fall 2024, Winter 2025
Instructors: There are no professors associated with this course for the 2024-2025 academic year.
Restriction: Open only to graduate students registered in the M.A. thesis program of the Sociology Department.
Sociology (Arts) : An introduction to basic regression techniques commonly used in the social sciences. Covers the least squares linear regression model in depth and may introduce models for discrete dependent variables as well as the maximum-likelihood approach to statistical inference. Emphasis on the assumptions behind regression models and correct interpretation of results. Assignments will emphasize practical aspects of quantitative analysis.
Terms: Fall 2024
Instructors: Clark, Shelley (Fall)
Prerequisites: