Social Science Analytics Specialization

Specialization Educational Objectives

In addition to the core objectives, a student graduating with a Bachelor of Science degree with a major in Data Analytics with a specialization in Social Science Analytics:

  • will demonstrate an understanding of methodologies used by social scientists in the conduct of research, including ethical issues.
  • will demonstrate proficiency in critically evaluating social science research.
  • will demonstrate proficiency in the design and implementation of original social science research.

General Education Courses

Students completing the Social Science Analytics specialization are required to complete an independent research project under the guidance of a faculty member. In order to prepare for this research project, students are encouraged to strategically choose General Education courses that allow them to explore their research interests. 

Degree Planning Resources

These documents outline the prerequisite structure within the core curriculum and demonstrate how students flow through the required courses for the Data Analytics major with a specialization in Social Science Analytics. They should be used as guides only. Semester course offerings are subject to change.

Since AU 2022 with NEW GE (GEN)

Before AU 2022 with LEGACY GE (GEL)

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Social Science Analytics Curriculum Sheet (opens in a new window)175.01 KB
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Social Science Analytics Sample 4-year Degree Plan (opens in a new window)207.65 KB

 

Specialization Requirements

All students specializing in Social Science Analytics must complete the following specialization requirements:

Overview of Research Methods: Select One (1) Course

  • COMM 3160: Communications Research Methods (4 cr hrs)
  • POLITSC 4781: Data Analysis in Political Science I (3 cr hrs)
  • PSYCH 2300: Research Methods in Psychology (3 cr hrs)
  • SOCIOL 3487: Research Methods in Sociology (3 cr hrs)

Electives: Choose Any Three (3) Courses

Students can select any three courses they wish from the following list, and are not restricted to courses from only one discipline. It is important to note that some of the courses have prerequisite courses that will need to be completed in advance, so careful planning is necessary.

  • ANTHRO 5650: Research Design and Ethnographic Methods (3 cr hrs)
  • ANTHRO 5651: Spatial Analysis for Anthropologists (3 cr hrs)
  • COMM 3163: Communication Industry Research Meahods (4 cr hrs)
  • ECON 4050: Experimental Economics (3 cr hrs)
  • ECON 5420: Econometrics II (3 cr hrs)
  • GEOG 5200: Cartography and Map Design (3 cr hrs)
  • GEOG 5201: GeoVisualization (3 cr hrs)
  • GEOG 5210: Fundamentals of GIS (3 cr hrs)
  • GEOG 5222: GIS Algorithms and Programming (3 cr hrs)
  • GEOG 5223: Design and Implementation of GIS (3 cr hrs)
  • GEOG 5225: Geographic Applications of Remote Sensing (3 cr hrs)
  • GEOG 5226: Spatial Simulation and Modeling in GIS (3 cr hrs)
  • POLITSC 3780: Data Literacy and Data Visualization (3 cr hrs)
  • PSYCH 4511: Psychological Testing (3 cr hrs)
  • SOCIOL 4650: Seminar in Social Networks (3 cr hrs)

Independent Research in the Social Sciences and Capstone Experience: Take Both (2) Courses

Students completing the Social Science Analytics specialization are required to complete a capstone course and an independent research project under the guidance of a faculty member (see syllabus above in Degree Planning Resources). Students should meet with their academic advisor early and often to discuss possible topics and strategies for pursuing the research component of this specialization. 

  • DEPT 4998/4999: Undergraduate Research or Thesis Research (3+ cr hrs)
  • STAT 4911: Capstone in Data Analytics (4 cr hrs)

[pdf] - Some links on this page are to .pdf files. If you need these files in a more accessible format, please contact data-analytics@osu.edu.