Master of Science in Social Data Analytics and Research The University of Texas at Dallas
The Master of Science in Social Data Analytics and Research builds on faculty expertise in criminology, economics, geospatial information sciences, political science, public and nonprofit management, public policy, political economy, and sociology to equip individuals with multi-disciplinary skills in social data production, collection and analysis for which there is increasing career demand by government, nonprofit and private sector organizations, and by doctoral programs and other advanced research institutions.
Graduates in the program acquire proficiency in:
- Social science research design and evaluation, including quantitative and qualitative approaches.
- Quantitative and qualitative data discovery and analysis methods, including understanding and analyzing large data sets.
- Harnessing capabilities to help government, nonprofit and private sector organizations as they address pressing societal issues on both local and global scales.
- Interpreting core theories and philosophical dimensions of social science practice, and promoting the ethical use of social science methodologies.
- Justifying the importance of applied social science in helping to shape public policy and action.
- Building successful career paths in diverse fields that rely upon social data analytics and research.
The mission of the Master of Science (MS) in Social Data Analytics and Research is to equip individuals with rigorous multi-disciplinary proficiency in methods of social data production, collection, and investigation for which there is a strong and increasing demand in the public, nonprofit, and private sectors, as well as in doctoral programs and other advanced research organizations.
The MS in Social Data Analytics and Research endows students with a clear understanding of the processes involved in the creation, assembly, analysis, and interpretation of social science data. It encourages reflection on core methods, theories, and philosophical dimensions of social science practice. It fosters an appreciation of the role of applied social science in helping to shape public policy and action through participation in the evaluation of policies and programs in place as well as through the formulation of new ones based on the outcomes of data analysis.
The MS in Social Data Analytics and Research orients itself to students wanting to apply social science concepts, principles, and methods to a broad range of questions in research-related and other professional engagements in government, nonprofit, and private sector settings that rely on social data for answers.
There are no specific prerequisites for admission to the MS in Social Data Analytics and Research. Several required courses, however, demand satisfactory prior completion of undergraduate college algebra and/or calculus.
In order to qualify for graduation, students must maintain a minimum 3.0 grade point average in their degree program's core courses plus an aggregate grade point average of 3.0 for all graduate courses taken in the student's degree program at UT Dallas.
Students seeking the MS in Social Data Analytics and Research must complete at least 36 semester credit hours of graduate coursework in the program and maintain at least a 3.0 (B) grade point average in order to graduate.
The program has three components: Required Core Courses (15 semester credit hours), Prescribed Analytical Electives (12 semester credit hours), and Prescribed Disciplinary Electives (9 semester credit hours), as follows:
I. Required Core Courses: 15 semester credit hours
- EPPS 6302 Methods of Data Collection and Production
- PPPE 6310 Research Design I
- EPPS 6313 Introduction to Quantitative Methods*
- or EPPS 7313 Descriptive and Inferential Statistics**
- EPPS 6316 Applied Regression*
- or EPPS 7316 Regression and Multivariate Analysis**
- EPPS 6356 Data Visualization
- or GISC 6363 Internet Mapping and Information Processing
In special circumstances, students may substitute alternative equivalent courses in the core with prior approval of the Program Director or the Associate Dean for Graduate Programs.
II. Prescribed Analytical Electives: 12 semester credit hours
Students complete twelve semester credit hours
- EPPS 6311 Research Practice in the Social Sciences
- EPPS 6323 Knowledge Mining
- EPPS 6324 Data Management for Social Science Research
- EPPS 6346 Qualitative Research Orientation
- EPPS 6352 Evaluation Research Methods in the Economic, Political and Policy Sciences
- EPPS 6354 Information Management
- EPPS 6355 Content Analysis
- EPPS 6356 Data Visualization
- EPPS 7304 Cost-Benefit Analysis
- EPPS 7318 Structural Equation and Multilevel (Hierarchical) Modeling
- EPPS 7344 Categorical and Limited Dependent Variables
- EPPS 7370 Time Series Analysis I
- EPPS 7371 Time Series Analysis II
- EPPS 7386 Survey Research
- EPPS 7390 Bayesian Analysis for Social and Behavioral Sciences
- GISC 5322 GPS (Global Positioning System) Satellite Surveying Techniques
- GISC 5324 3D Data Capture and Ground LiDAR
- GISC 6301 GIS Data Analysis Fundamentals
- GISC 6317 GIS Programming Fundamentals
- GISC 6321 Spatial Data Science
- GISC 6323 Machine Learning for Socio-Economic and Geo-Referenced Data
- GISC 6325 Remote Sensing Fundamentals
- GISC 6381 Geographic Information Systems Fundamentals
- GISC 6384 Advanced Geographic Information Systems
- GISC 7310 Advanced GIS Data Analysis
- GISC 7360 GIS Pattern Analysis
- GISC 7361 Spatial Statistics
- GISC 7365 Advanced Remote Sensing
III. Disciplinary Electives: 9 semester credit hours
Students complete nine semester credit hours in ONE of the following disciplinary domains (Criminology, Geospatial Information Sciences, Economics, Political Science, Public/Nonprofit Management, Public Policy/Political Economy, or Sociology) with courses prescribed by the respective EPPS Programs. The Program Director or the Associate Dean for Graduate Programs must approve course selection.
* Prerequisite is College Algebra.
** Prerequisite is Calculus.
Graduates of the program will:
- Apply methods of social science research design and evaluation, including quantitative (e.g., experimental, quasi-experimental, and naturalistic) and qualitative approaches in varied public, non-profit, and private sector settings;
- Employ quantitative and qualitative analysis methods for social science data used in research by different types of public, non-profit, and private sector organizations;
- Harness acquired skills and capabilities in practice to sustain public, nonprofit, and private sector organizations as they address pressing societal issues on both local and global scales;
- Interpret core theories and philosophical dimensions of social science practice, and promote ethical use of social science methodology;
- Justify the importance of applied social science in helping to shape public policy and action;
- Successfully build career paths in fields applying social data analytics and research.
Graduates seek varied positions, including data analyst/scientist, data mining specialist, database manager, statistician, program evaluation analyst, decision support analyst, research analyst, opinion polling statistician, a community intelligence expert, and information resource analyst.
English Language Requirements
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