The concentration in Data Analytics provides students with the knowledge and skills to apply state-of-the-art methodological skills to a wide-variety of topic areas.
Data analytic skills, such as statistics, data management and manipulation, global information studies (GIS), social network analysis, game theory and other techniques are changing the way that organizations and agencies use and increasingly rely on data. During the School of International Affairs annual career trips to prospective employers, one of the top skills that employers (whether companies, NGOs, international organizations, or government agencies) identify is data analytics. All SIA students are required to take a course in advanced statistics, providing them with above-average methodological skills. The concentration in Data Analytics provides students with a skill package that moves them into the top of public policy methods analysts by providing them with substantial training in advanced data analysis skills. By developing cutting-edge data analytic skills, these students and future employees will be ready to not just contribute to, but to thrive in, the information revolution.
Students wishing to receive attestation certifying the depth of their specialization in this particular area will be required to successfully complete at least four of the courses listed below or other additional courses agreed to by the SIA Director of Academic Advising.
Please note that this list will be reviewed from time to time depending on the available course offerings at any given time. Students should check the availability of these courses with the SIA academic advisor and the individual course instructors. Students should also determine if there are pre-requisites for enrolling in a particular course.
- Research Design — INTAF 500 (3 credits)
- Science, Technology and International Policy — INTAF 502 (3 credits)
- Strategy, Conflict, Peace (Game Theory) — INTAF 505 (3 credits)
- Time Series and long-T Panel Analysis — INTAF 597* (3 credits)
- Spatial Demography — ANTH/SOC 579 (3 credits)
- Business Strategies for Data Analytics — BAN 530** (3 credits)
- Predictive Analytics for Business — BAN 840** (3 credits)
- Prescriptive Analytics for Business — BAN 550** (3 credits)
- Community, Environment and Development Research Methods — CED 404 (3 credits)
- Introduction to Data Analysis in Communications — COMM 516 (3 credits)
- Introductory Data Analysis (in Educational Policy Making) — EDTHP 497* (3 credits)
- Problem-Solving with GIS — GEOG 483** (3 credits)
- Strategies for Data Analysis in Developmental Research — HDFS 523 (3 credits)
- Data Analysis in Hospitality Management — HM 586
- Principles of Public Health Administration — HPA 410 (3 credits)
- Policy Making and Evaluation — PLSC 490 (3 credits)
- Methods of Political Analysis — PLSC 501 (3 credits)
- Statistical Methods for Political Research — PLSC 502 (3 credits)
- Multivariate Analysis for Political Research — PLSC 503 (3 credits)
- Time Series Analysis in Political Science — PLSC 505 (3 credits)
- Game Theory for Political Science I — PLSC 506 (3 credits)
- Game Theory for Political Science II — PLSC 507 (3 credits)
- Program Evaluation and Research in Recreation Services — RPTM 433 (3 credits)
- Intermediate Social Statistics — SOC 470 (3 credits)
- Qualitative Research Methods in Sociology — SOC 471 (3 credits)
- Sociological Research Methods — SOC 513 (3 credits)
- Research Methods in Criminology and Deviance — SOC 515 (3 credits)
- Survey Methods I: Survey Design — SOC 518 (3 credits)
- Survey Methods II: Analysis of Survey Data — SOC 519 (3 credits)
- Social Network Analysis — SOC 580 (3 credits)
- Introduction to Probability Theory — STAT 414 (3 credits)
- Introduction to Mathematical Statistics — STAT 415 (3 credits)
- Intermediate Applied Statistics — STAT 460 (3 credits)
- Applied Time Series Analysis — STAT 463 (3 credits)
- Introduction to SAS — STAT 480 (1 credit)
- Intermediate SAS for Data Management — STAT 481 (1 credit)
- Advanced Statistics Procedures in SAS — STAT 482 (1 credit)
- Applied Statistics — STAT 500 (3 credits)
- Regression Methods — STAT 501 (3 credits)
- Analysis of Variance and Design of Experiments — STAT 502 (3 credits)
- Analysis of Discrete Data — STAT 504 (3 credits)
- Applied Multivariate Statistical Analysis — STAT 505 (3 credits)
- Applied Time Series Analysis — STAT 510 (3 credits)
* Frequency and availability of Special Topics 597 courses will vary each semester.
** World Campus courses may require approval from the faculty, department, and/or World Campus Registrar for enrollment.