The program provides an integrated training in social science theory and evidence, statistical methods, the analysis of social data, and the interpretation and presentation of results. To achieve these goals, students take required courses that offer foundational training in quantitative methods and social science paradigms, electives that offer opportunities for advanced methodological training and deeper engagement of topics in social science, and a capstone project in which students will apply the skills they have learned to carry out an analysis on a topic of their choice. The course is designed so that students acquire foundational training in their first two years, develop experience carrying out analysis independently in their second and especially third year by taking laboratory courses in conjunction with their electives, and then demonstrate their ability to design and execute a project of their own in their capstone project, and communicate the results.
Through this training, students will learn how to apply advanced quantitative methods to complex datasets in a way that accounts for the unique challenges associated with the analysis of social data, and reflects an understanding of existing social theory and evidence. They will learn how to identify a research question, collect and manage complex social data, carry out analysis, and then develop, test, and refine hypotheses informed by social science theory.
Overview of Program Requirements
70-73 credits from Program Requirements (depending on MATH placement)
- 19 credits from required Social Science (SOSC) courses
- Research methods
- Applied quantitative methods
- First-year seminar, laboratory, capstone project, proseminar
- 15-18 credits of MATH courses, depending on placement. These include calculus, applied statistics, and probability.
- 24 credits from Quantitative Social Analysis program electives of which at least
- 12 credits are from a menu of topical courses, mainly in SOSC. Subjects include political science, psychology economics, sociology, and other social science disciplines. These introduce theory, evidence, and major issues and debates, and help students understand how to think about questions as a social scientist.
- 12 credits are from a menu of methodological courses in MATH, SOSC, and other units. These allow students to pursue more advanced and specialized training in specific methods according to their interests. Choices include more theoretical courses in MATH ideal for students planning postgraduate studies, and applied courses in SOSC and other units for students who will seek employment in business, government, or the non-profit sector.
- 6 units in programming courses in Computer Science (COMP)
- 6 units in Language (LANG/LABU) courses
36 credits from Common Core courses as required by the University
- Students taking the BSc Program in Quantitative Social Analysis as their first major are exempted from the School Requirements. They are still required to complete the University requirements in addition to the major requirements for graduation.
- Some courses used to fulfill Major Requirements can also fulfill University Common Core Requirements. Students may reuse a maximum of 6 credits of these courses to count towards Common Core Requirements.
- To graduate from the University, students should complete at least 120 credits. Students may have to take courses beyond the ones summarized above to meet this requirement. We will do our best to accommodate students who seek to use these additional courses to complete a minor, or double major.
Detailed Program Requirements
Descriptions of courses that are central to the program
All course descriptions – at University website
|SOSC 1100||Elementary Statistics for Social Research||3|
|SOSC 1200||Quantitative Social Analysis||3|
|SOSC 1210||First-year seminar (P/F Grading)||1|
|SOSC 2140||Research Methods in the Social Sciences||3|
|SOSC 2400||Intermediate Statistics for Social Research||3|
|SOSC 3700||Quantitative Social Analysis Laboratory|
|Note:Attainment of 2 credits from SOSC3700 by taking the course for 2 times||2|
|SOSC 4100||Research Proseminar (P/F Grading)||1|
|SOSC 4110||Capstone project||3|
|[(MATH1012/1013/1023) AND (MATH 1014/1024)] OR [MATH 1020]||4-7|
|MATH1023||Honors Calculus I|
|MATH1024||Honors Calculus II|
|MATH2011||Introduction to Multivariate Calculus||3|
|LANG2070||English Communication for Global China Studies I||3|
|LANG3070 or MABU2060||3|
|LANG3070||English Communication for Global China Studies II|
|LABU2060**||Effective Communication in Business|
|COMP1022P OR COMP 1022Q||3|
|COMP1022P||Introduction to Computing With Java|
|COMP1022Q||Introduction to Computing With Excel VBA|
|COMP1942||Exploring and Visualizing Data||3|
Electives – 24 credits from the following, with at least 12 credits each from the Methodological and Topical menus
|SOSC 1661||Contemporary Hong Kong: Society||3|
|SOSC 1662||Contemporary Hong Kong: Politics and Government||3|
|SOSC 1860||Population and Society||3|
|SOSC 2310||Introductory Environmental and Health Economics||3|
|SOSC 2630||Development in Rural China||3|
|SOSC 3110||Science and Technology in Hong Kong||3|
|SOSC 3120||Economic Development||3|
|SOSC 3130||Hong Kong Culture||3|
|SOSC 3410||East Asian Economic Development||3|
|SOSC 3520||Understanding Comparative Politics||3|
|SOSC 3880||Social Inequality and Social Mobility||3|
|SOSC 3240||Applications of Geographical Information Systems||3|
|SOSC 4310||Categorical data analysis||3|
|SOSC 4320||Structural Equation Modelling||3|
|MATH 3423||Statistical Inference||3|
|MATH 3424||Regression Analysis||3|
|MATH 4423||Nonparametric Statistics||3|
|MATH 4424||Multivariate Analysis||3|
|MATH 4425||Introductory Time Series||3|
|COMP 2011||Introduction to Object-Oriented Programming||4|
|ISOM 3360||Business Intelligence and Data Mining||3|
|MARK 3220||Marketing Research||4|
|See notes above regarding Common Core requirements and University graduation requirements.|