Undergraduate Minor

Minor in Social Science Quantitative Data Analytics

Minor in Social Science Quantitative Data Analytics
Plan Code:
Program Level:
Award Type:
Minor Undergraduate
College of Social Science
Social Science Dean

Excerpt from the official Academic Programs Catalog:

Listed below are the approved requirements for the program from the official Academic Programs Catalog.
Students must consult their advisors to learn which specific requirements apply to their degree programs.

College of Social Science

Undergraduate Programs

Minor in Social Science Quantitative Data Analytics

The Minor in Social Science Quantitative Data Analytics, administered by the College of Social Science, enhances the education and empowers students interested in understanding how core social science skills such as critical thinking and theoretically oriented analysis are useful in the systematic collection, integration, analysis, and presentation of large-scale and dense information.
The minor is available as an elective to students who are enrolled in bachelor’s degree programs in the College of Social Science. With the approval of the department and college that administer the student’s degree program, the courses that are used to satisfy the minor may also be used to satisfy the requirements for the bachelor’s degree.

Requirements for the Minor in Social Science Quantitative Data Analytics

Students must complete a minimum of 15 credits from the following:
1. The following course (3 credits):
PLS 202 Introduction to Data Analytics and the Social Sciences 3
2. One of the following quantitative methods courses (3 or 4 credits):
EC 420 Introduction to Econometric Methods 3
GEO 363 Introduction to Quantitative Methods for Geographers 3
MTH 234 Multivariable Calculus 4
PSY 395 Research Design and Measurement in Psychological Research 3
SOC 282 Quantitative Analysis for Social Research 4
STT 200 Statistical Methods 3
STT 201 Statistical Methods 4
STT 315 Introduction to Probability and Statistics for Business 3
STT 421 Statistics I 3
STT 441 Probability and Statistics I: Probability 3
3. Two of the following courses (6 to 8 credits):
CMSE 201 Introduction to Computational Modeling and Data Analysis 4
CMSE 202 Computational Modeling Tools and Techniques 4
CSE 231 Introduction to Programming I 4
CSE 232 Introduction to Programming II 4
EC 421 Advanced Econometric Methods 3
GEO 325 Geographic Information Systems 3
GEO 429 Geoprocessing 3
MTH 235 Differential Equations 3
PLS 397 Analyzing and Visualizing Data in Politics 3
4. The following capstone course (3 credits):
SSC 442 Social Science Data Analytic Applications 3