Please note:

To view the Fall 2022 Academic Calendar, go to www.sfu.ca/students/calendar/2022/fall.html.

Social Data Analytics Minor

The Faculty of Arts and Social Sciences, with the Departments of Economics, Linguistics, Philosophy, and Political Science, along with the Departments of English, Gender, Sexuality and Women's Studies, and Statistics and Actuarial Science, and the School of Communication, offers a minor in Social Data Analytics (SDA). This program offers an interdisciplinary study of statistical and computational methods with an emphasis on the privacy, ethical, and societal issues surrounding technology and big data. It is intended to complement and build on the knowledge and deeper understanding of issues that students acquire from their major program of study in the Arts and Social Sciences and related disciplines. 

The program is managed by the Faculty of Arts and Social Sciences. An advisory committee consisting of representatives from the above departments serve as a liaison between participating departments and the program director.

Admission Requirements

Program admission is limited. Entry is via a formal minor program application and applications will be considered for both students entering Simon Fraser University and those already enrolled. Students may apply for admission to the minor program at any time. It is strongly recommended that students contact the Social Data Analytics advisor or program director early about admission and scheduling.

Program Requirements

Students must complete at least 27 units as follows:

Complete all of:

SDA 250 - Computational Text Analysis (4)

Introduces basics of text analysis through Python programming. Core concepts include: data capture and manipulation; data cleaning and preprocessing; database management; big data; natural language processing; introductory machine learning; text classification. Students with credit for LING 250 may not take this course for further credit.

Section Instructor Day/Time Location
D100 Maite Taboada
Tu 10:30 AM – 12:20 PM
Th 10:30 AM – 12:20 PM
AQ 5030, Burnaby
SWH 10061, Burnaby
SDA 270 - Data, Ethics and Society (3)

This course would introduce students to the ethical, legal, and privacy issues surrounding the collection and use of big data and the implications of these for vulnerable populations. Students with credit for PHIL 270 may not take this course for further credit.

Section Instructor Day/Time Location
D100 Chelsea Rosenthal
Th 2:30 PM – 5:20 PM
REMOTE LEARNING, Burnaby
SDA 490 - Capstone Project Seminar (5)

Final capstone group project that applies the skills students have learned in their studies to gain experience tackling real-world policy and social problems and develop a portfolio that they can showcase to prospective employers or graduate programs. Topics vary. Prerequisite: Admission into the Social Data Analytics Minor and 18 units completed in the minor.

Section Instructor Day/Time Location
D100 Edana Beauvais
Steven Weldon
Th 2:30 PM – 5:20 PM
HCC 2540, Vancouver

Complete one of:

ECON 233 - Introduction to Economic Data and Statistics (3)

Introduces statistical methods, concepts and their application to economic data using both spreadsheets (e.g., Excel) and a specialized statistical programming language such as R. Prerequisite: MATH 150, MATH 151, MATH 154, or MATH 157, with a minimum grade of C-; 15 units. MATH 150, MATH 151, MATH 154, or MATH 157 may be taken concurrently with ECON 233. Students who have taken ECON 333 first may not then take this course for further credit. STAT 270 or BUS 232 will be accepted in lieu of this course.

Section Instructor Day/Time Location
D100 Brian Krauth
Tu 12:30 PM – 2:20 PM
SWH 10041, Burnaby
D101 Tu 2:30 PM – 3:20 PM
WMC 2506, Burnaby
D102 Tu 4:30 PM – 5:20 PM
WMC 2506, Burnaby
D103 Tu 3:30 PM – 4:20 PM
WMC 2506, Burnaby
D104 Th 3:30 PM – 4:20 PM
WMC 2506, Burnaby
D105 Th 4:30 PM – 5:20 PM
WMC 2506, Burnaby
D106 We 3:30 PM – 4:20 PM
WMC 2506, Burnaby
D107 Th 1:30 PM – 2:20 PM
WMC 2506, Burnaby
D108 Th 2:30 PM – 3:20 PM
WMC 2506, Burnaby
POL 201 - Introductory Quantitative Methods in Political Science (4)

Introduces quantitative research techniques in political science. Introduces important analytical and conceptual skills necessary to understand and evaluate quantitative political science research. Corequisite: POL 200W or permission of department. Quantitative.

Section Instructor Day/Time Location
B100 Mark Pickup
We 1:30 PM – 2:20 PM
AQ 3005, Burnaby
B101 We 4:30 PM – 6:20 PM
AQ 5047, Burnaby
B102 We 6:30 PM – 8:20 PM
AQ 5047, Burnaby
B103 Th 9:30 AM – 11:20 AM
AQ 5038, Burnaby
STAT 203 - Introduction to Statistics for the Social Sciences (3)

Descriptive and inferential statistics aimed at students in the social sciences. Scales of measurement. Descriptive statistics. Measures of association. Hypothesis tests and confidence intervals. Students in Sociology and Anthropology are expected to take SA 255 before this course. Intended to be particularly accessible to students who are not specializing in Statistics. Prerequisite: Recommended: 30 units including a research methods course such as SA 255, CRIM 220, POL 200W, or equivalent. Students cannot obtain credit for STAT 203 if they already have credit for - or are taking concurrently - STAT 101, 201, 205, 285, or any upper division STAT course. Quantitative.

Section Instructor Day/Time Location
D100 Marie Loughin
Mo 10:30 AM – 12:20 PM
We 10:30 AM – 11:20 AM
SSCB 9201, Burnaby
AQ 3181, Burnaby
OL01 Distance Education
OP01 TBD

Elective Requirements

Students complete a total of at least 12 elective units, as follows:

No more than four units of which may come from:

CMNS 333 - Digital Policies in a Global Context: Current Issues, Concepts and Analysis (4)

We will investigate current policy issues and case studies from Canada and around the world to examine communication policy as a field shaped by change and continuity. Students will get an introduction to communication policy analysis with the aim to sneak and write analytically about current challenges such as network neutrality, copyright, content regulation and data protection. Students will discuss the tensions that arise between the national-regional and global jurisdictions, and how these are relevant to their everyday life. Prerequisite: One of CMNS 230 or 240, with a minimum grade of C-; and one of CMNS 202 (or 262) or 261, with a minimum grade of C-.

CMNS 353 - Topics in Technology and Society (4)

Examination of the emergence and shaping of information and communication technologies in the digital age. Explores new media and social change between everyday life, social institutions, and various enterprises. Emphasis is placed on social context and relations of power. This course can be repeated once for credit if second topic is different (up to a maximum of two times). Prerequisite: CMNS 253W with a minimum grade of C- and one of CMNS 201W (201 or 260) or CMNS 202 (or 262), with a minimum grade of C-. Recommended: CMNS 362.

Section Instructor Day/Time Location
D100 Peter Chow-White
Mo 10:30 AM – 12:20 PM
HCC 1900, Vancouver
D101 Fr 9:30 AM – 10:20 AM
HCC 1525, Vancouver
D102 Fr 10:30 AM – 11:20 AM
HCC 1525, Vancouver
D103 Fr 12:30 PM – 1:20 PM
HCC 1525, Vancouver
D104 Fr 1:30 PM – 2:20 PM
HCC 1525, Vancouver
D200 Sun Ha Hong
Tu 11:30 AM – 2:20 PM
HCC 1800, Vancouver
D201 We 9:30 AM – 10:20 AM
HCC 3122, Vancouver
D202 We 10:30 AM – 11:20 AM
HCC 3122, Vancouver
D203 We 1:30 PM – 2:20 PM
HCC 2540, Vancouver
D204 We 2:30 PM – 3:20 PM
HCC 2540, Vancouver
ENGL 363 - Studies in Media Cultures (4)

Study of the relation of literature and media (manuscript, print, visual, aural, digital, and/or oral) within their cultural and/or performative contexts. May be further organized by methodology (e.g. book history, textual scholarship, media studies, adaptation studies, digital humanities), historical period, or genre. This course may be repeated for credit if a different topic is taught. Prerequisite: 30 units or two 200-division English courses.

Section Instructor Day/Time Location
D100 Torsten Kehler
Mo 12:30 PM – 2:20 PM
RCB 8100, Burnaby
D101 Torsten Kehler
Tu 9:30 AM – 11:20 AM
RCB 7100, Burnaby
D102 Torsten Kehler
Tu 12:30 PM – 2:20 PM
RCB 5118, Burnaby
D103 Torsten Kehler
Tu 3:30 PM – 5:20 PM
AQ 5050, Burnaby
GSWS 399 - Gender, Sex and Numbers (4)

Through an examination of the social construction of numbers and other forms of quantitative data will provide an introduction to measurement and its use within social justice movements and policy circles. In analyzing such topics as the relationship between professional, state and community conceptualizations of quantitative evidence, students will make use of introductory statistical concepts, methods and argument. Prerequisite: 30 units. Quantitative.

POL 318 - Fake News and Alt-Facts: Navigating Post-Truths Politics (4)

Explores the emergence of post-truth politics; the rejection of expert and scientific opinion; and the emergence of "alternative facts" and "fake news" in political discourse on current issues such as climate change, immigration and the economy. Also explores corresponding increase in the ideological polarization in the US, Canada, and the UK and other European nations. Prerequisite: Six lower division units in Political Science or permission of the department. Students with credit for POL 339 Selected Topics in Comparative Government and Politics under the title Navigating the Post-Truth World may not take this course for further credit.

POL 426W - Political Behavior (4)

The study of political attitudes and behavior in Canada, the United States and other democratic states. Topics will include political culture, public opinion, elections and voting behavior. Prerequisite: POL 222, and eight upper division units in Political Science or the permission of the department. Writing/Quantitative.

Section Instructor Day/Time Location
D100 Sessional
Th 2:30 PM – 5:20 PM
AQ 5036, Burnaby

No more than four units of which may come from:

ECON 334 - Data Visualization and Economic Analysis (3)

Explores how to recognize and learn from patterns in data using modern statistical software for the purpose of economic analysis. Introduces students to techniques for managing, visualizing, and analyzing data to answer real-world economic questions. Prerequisite: ECON 233 or BUS 232 or STAT 270 or POL 201, with a minimum grade of C-; ECON 103 with a minimum grade of C-, or ECON 113 with a minimum grade of A-, or ECON 105 with a minimum grade of C-, or ECON 115 with a minimum grade of A-. Students with credit for POL 390, STAT 341, or STAT 452 may not take this course for further credit. Students with credit for ECON 387 under the title "Applied Data Analysis" may not take this course for further credit.

POL 390 - Data Visualization and Political Analysis (3)

Social data and digital technologies are rapidly transforming politics and society, including election campaigns, how governments make policy, the targeting of consumers, and our interactions and connections with one another. This course offers a hands-on introduction to data science with an emphasis on data visualization for political and social analysis. Prerequisite: One of POL 201, ECON 233, STAT 203 or equivalent. Students with credit for ECON 334, ECON 387 under the title "Applied Data Analysis", or POL 339 under the title "Politics and Data Science" may not take this course for further credit. Quantitative.

Section Instructor Day/Time Location
D100 Steven Weldon
Mo 10:30 AM – 12:20 PM
We 10:30 AM – 11:20 AM
HCC 1425, Vancouver
HCC 1315, Vancouver
STAT 240 - Introduction to Data Science (3)

Introduction to modern tools and methods for data acquisition, management, and visualization capable of scaling to Big Data. Prerequisite: One of STAT 201, STAT 203, STAT 205, STAT 270, BUS 232, or ECON 233, and one of CMPT 102, CMPT 120, CMPT 125, CMPT 128, CMPT 129, CMPT 130, all with a minimum grade of C- or permission of the instructor. STAT 260 is also recommended. Quantitative.

Section Instructor Day/Time Location
D100 Lloyd Elliott
Mo 12:30 PM – 2:20 PM
WMC 3260, Burnaby
D101 Lloyd Elliott
Mo 2:30 PM – 3:20 PM
AQ 3148.2, Burnaby
D102 Lloyd Elliott
Mo 3:30 PM – 4:20 PM
AQ 3148.2, Burnaby
D103 Lloyd Elliott
Mo 4:30 PM – 5:20 PM
AQ 3148.2, Burnaby
D104 Lloyd Elliott
Mo 5:30 PM – 6:20 PM
AQ 3148.2, Burnaby
D105 Lloyd Elliott
Tu 5:30 PM – 6:20 PM
AQ 3148.1, Burnaby
D106 Lloyd Elliott
Tu 6:30 PM – 7:20 PM
AQ 3148.1, Burnaby
D107 Lloyd Elliott
Tu 7:30 PM – 8:20 PM
AQ 3148.2, Burnaby
STAT 310 - Introduction to Data Science for the Social Sciences (2)

An introduction to modern tools and methods for data acquisition, management, visualization, and machine learning, capable of scaling to Big Data. No prior computer programming experience required. Examples will draw from the social sciences. This course may not be used to satisfy the upper division requirements of the statistics honours, major, or minor programs. Prerequisite: 60 units in subjects outside of the Faculties of Science and Applied Sciences and one of STAT 201, STAT 203, STAT 205, STAT 270, BUS 232, ECON 233, or POL 201, with a minimum grade of C-. Corequisite: STAT 311. Students who have taken STAT 240, STAT 440, or any 200-level or higher CMPT course first may not then take this course for further credit. Quantitative.

and STAT 311 - Data Science Laboratory for the Social Sciences (2)

A hands-on application of modern tools and methods for data acquisition, management, visualization, and machine learning, capable of scaling to Big Data. No prior computer programming experience required. Projects will draw from the social sciences and integrate application area insight into the analytic toolkit from STAT 310. This course may not be used to satisfy the upper division requirements of the statistics honours, major, or minor programs. Prerequisite: 60 units in subjects outside of the Faculties of Science and Applied Sciences and one of STAT 201, STAT 203, STAT 205, STAT 270, BUS 232, ECON 233, or POL 201, with a minimum grade of C-. Corequisite: STAT 310. Students who have taken STAT 240, STAT 440, or any 200-level or higher CMPT course first may not then take this course for further credit. Quantitative.

Any of:

ECON 329 - Experimental Economics (3)

Covers experimental methods that are used to test existing theories of rational and behavioural economic decision making in a number of environments related to markets, different institutions, as well as strategic situations. Introduces and discusses methodological tools needed to design, run and analyze experiments. Prerequisite: ECON 103 with a minimum grade of C- or ECON 113 with a minimum grade of A-; ECON 105 with a minimum grade of C- or ECON 115 with a minimum grade of A-. Students who have taken ECON 383 Selected Topics - Experimental Economics in Fall 2011, Fall 2012, Summer 2013, Spring 2014, Summer 2014, Fall 2018, or Spring 2019 may not take this course for further credit.

ECON 335 - Cause and Effect in Economic Data (3)

Provides an introduction to statistical methods used to analyze causal questions and evaluate policies. Discusses various approaches to drawing causal inferences from observational data. Corequisite: ECON 333. Students who have taken ECON 480 first may not then take this course for further credit.

Section Instructor Day/Time Location
D100 Simon Woodcock
Mo 10:30 AM – 12:20 PM
AQ 3149, Burnaby
D101 Mo 12:30 PM – 1:20 PM
WMC 2506, Burnaby
D102 Mo 1:30 PM – 2:20 PM
WMC 2506, Burnaby
D103 Mo 2:30 PM – 3:20 PM
WMC 2506, Burnaby
D105 We 2:30 PM – 3:20 PM
WMC 2506, Burnaby
D106 Th 12:30 PM – 1:20 PM
WMC 2506, Burnaby
ECON 435 - Econometric Methods (5)

The application of econometric techniques to the empirical investigation of economic issues. Prerequisite: ECON 201 and ECON (or BUEC) 333, all with a minimum grade of C-. Entry into this course requires a minimum CGPA of 3.0 or permission of the department. Quantitative.

GEOG 255 - Geographical Information Science I (3)

A basic overview of Geographical Information Systems and Science; GIS software, hardware, data structures and models; spatial data, operations and algorithms; practical applications and limitations. Prerequisite: GEOG 100 or 111 or permission of instructor. Students with credit for GEOG 354 may not take this course for further credit. Quantitative.

Section Instructor Day/Time Location
D100 Shivanand Balram
Tu 12:30 PM – 2:20 PM
SSCC 9000, Burnaby
D101 Tu 2:30 PM – 4:20 PM
AQ 2109, Burnaby
D102 We 8:30 AM – 10:20 AM
AQ 2109, Burnaby
D103 We 10:30 AM – 12:20 PM
AQ 2109, Burnaby
D104 We 2:30 PM – 4:20 PM
AQ 2109, Burnaby
GEOG 355 - Geographical Information Science II (4)

An examination of technical components of GIS. Topics include spatial representations, generalization and data management; computational algebra and set theory; digital surfaces and terrain models. Prerequisite: GEOG 255. Quantitative.

Section Instructor Day/Time Location
D100 Nadine Schuurman
TBD
D101 Tu 10:30 AM – 12:20 PM
AQ 2111, Burnaby
D102 Th 8:30 AM – 10:20 AM
AQ 2111, Burnaby
D103 Th 12:30 PM – 2:20 PM
AQ 2111, Burnaby
LING 450 - Computational Linguistics (3)

Introduction to theoretical and applied issues in the computational processing of natural language. Prerequisite: LING 250 or SDA 250.

PHIL 315 - Formal Methods (3)

A survey of formal methods used in philosophy. Topics will include some of the following: propositional logic, predicate logic, formal syntax, formal semantics, the probability calculus, decision theory, game theory and formal causal modeling. Prerequisite: One of: PHIL 110, 210, 310, 314, MACM 101, BUEC 232, BUS 232, or STAT 270. Students with credit for COGS 315 cannot take this course for further credit.

POL 315 - Intermediate Quantitative Methods (4)

Introduces intermediate quantitative methods and data analysis. Teaches students how to build statistical models and apply them to social and political research. Also covers the fundamentals of probability, sampling, and causal inference; students will learns how to conduct their own data-driven research. Prerequisite: POL 201 or permission of instructor. Quantitative.

Section Instructor Day/Time Location
D100 Edana Beauvais
Tu, Th 10:30 AM – 12:20 PM
HCC 2540, Vancouver
POL 488 - Topics in Empirical Research Design and Analysis (4)

Topics in statistical and computational methodologies that focus on research design, data collection, visualization, and analysis in political and social science. The topics vary and example topics include: time-series and longitudinal analysis, text analysis, network analysis, and computational social science. Students may repeat this course for further credit under a different topic. Prerequisite: POL 201, ECON 233, STAT 203, or equivalent.

STAT 302 - Analysis of Experimental and Observational Data (3)

The standard techniques of multiple regression analysis, analysis of variance, and analysis of covariance, and their role in observational and experimental studies. This course may not be used to satisfy the upper division requirements of the following programs: statistics major, statistics honours, actuarial science major, and actuarial science honours. Prerequisite: One of STAT 201, STAT 203, STAT 205, STAT 270, BUS 232, or ECON 233, with a minimum grade of C-. Students who have taken STAT 350 first may not then take the course for further credit. Quantitative.

Section Instructor Day/Time Location
D100 Owen Ward
Mo 12:30 PM – 2:20 PM
We 12:30 PM – 1:20 PM
SSCB 9200, Burnaby
SSCB 9200, Burnaby
OL01 Distance Education
OP01 TBD
STAT 360 - Advanced R for Data Science (2)

Advanced R programming methods for data science. Tools for reproducible research. Version control. Data structures, subsetting, functions, environments, and debugging. Functional programming. Code performance: profiling, memory, integrating R and C++. Prerequisite: One of STAT 260 or STAT 341 and one of STAT 302, STAT 305, STAT 350, or ECON 333, all with a minimum grade of C-. CMPT 125 or CMPT 129 is also recommended. Corequisite: STAT 361.

Section Instructor Day/Time Location
D100 Wei Lin
Tu 12:30 PM – 2:20 PM
AQ 3005, Burnaby
and STAT 361 - Laboratory for Advanced R for Data Science (1)

A hands-on application of advanced R programming methods for data science. Using the R concepts covered in STAT 360 and tools for reproducible research, students will work with different data structures, write functions, and debug and optimize the performance of their code. Prerequisite: One of STAT 260 or STAT 341 and one of STAT 302, STAT 305, STAT 350, or ECON 333, all with a minimum grade of C-. CMPT 125 or CMPT 129 is also recommended. Corequisite: STAT 360.

Section Instructor Day/Time Location
D100 Wei Lin
Th 2:30 PM – 3:20 PM
WMC 3511, Burnaby
D200 Wei Lin
Th 3:30 PM – 4:20 PM
WMC 3511, Burnaby
D300 Wei Lin
Fr 11:30 AM – 12:20 PM
WMC 3511, Burnaby
D400 Wei Lin
Fr 12:30 PM – 1:20 PM
WMC 3511, Burnaby
STAT 452 - Statistical Learning and Prediction (3)

An introduction to the essential modern supervised and unsupervised statistical learning methods. Topics include review of linear regression, classification, statistical error measurement, flexible regression and classification methods, clustering and dimension reduction. Prerequisite: STAT 302 or STAT 305 or STAT 350 or ECON 333 or equivalent, with a minimum grade of C-. Quantitative.

With approval of the program director, up to six units of relevant courses from other departments may be counted for the minor.

Faculty of Arts and Social Sciences Degree Requirements

For all bachelor of arts (BA) programs, students complete 120 units, which includes

  • at least 60 units that must be completed at Simon Fraser University
  • at least 45 upper division units, of which at least 30 upper division units must be completed at Simon Fraser University
  • at least 60 units (including 21 upper division units) in Faculty of Arts and Social Sciences courses
  • satisfaction of the writing, quantitative, and breadth requirements
  • an overall cumulative grade point average (CGPA) and upper division overall CGPA of at least 2.0, and program CGPA and upper division program CGPA of at least 2.0 on the course work used to satisfy the minimum program requirements. FASS departments may define additional GPA requirements for their respective programs.

For students in other faculties, please check your faculty's overall degree requirements: https://www.sfu.ca/students/calendar/faculties-research.html

Writing, Quantitative, and Breadth Requirements

Students admitted to Simon Fraser University beginning in the fall 2006 term must meet writing, quantitative and breadth requirements as part of any degree program they may undertake. See Writing, Quantitative, and Breadth Requirements for university-wide information.

WQB Graduation Requirements

A grade of C- or better is required to earn W, Q or B credit

Requirement

Units

Notes
W - Writing

6

Must include at least one upper division course, taken at Simon Fraser University within the student’s major subject
Q - Quantitative

6

Q courses may be lower or upper division
B - Breadth

18

Designated Breadth Must be outside the student’s major subject, and may be lower or upper division
6 units Social Sciences: B-Soc
6 units Humanities: B-Hum
6 units Sciences: B-Sci

6

Additional Breadth 6 units outside the student’s major subject (may or may not be B-designated courses, and will likely help fulfil individual degree program requirements)

Students choosing to complete a joint major, joint honours, double major, two extended minors, an extended minor and a minor, or two minors may satisfy the breadth requirements (designated or not designated) with courses completed in either one or both program areas.