Survey and Data Science, Master of Science (M.S.)
Non-thesis option only: 46 credits required
SURV offers a non-thesis program, however students in all three tracks the statistical science, social and psychological science and data science concentrations must fulfill a research experience requirement, yielding a scholarly paper. This paper must be the result of either original research conducted by the student, critical analysis, or evaluation of existing surveys.
Students choose from one of the following concentrations:
Statistical Science
| Course | Title | Credits |
|---|---|---|
| Required courses: | ||
| SURV615 | Statistical Modeling and Machine Learning I | 3 |
| SURV616 | Statistical Modeling and Machine Learning II | 3 |
| SURV720 | Total Survey Error and Data Quality I | 2 |
| SURV721 | Total Survey Error and Data Quality II | 2 |
| SURV772 | Survey Design Seminar | 3 |
| SURV617 | Applications of Statistical Modeling | 3 |
| Fundamentals of Data Collection I | 3 | |
| Fundamentals of Data Collection II | 3 | |
| Fundamentals of Computing and Data Display | 3 | |
| Specialization requirements: | ||
| SURV410 | Introduction to Probability Theory | 3 |
| SURV420 | Theory and Methods of Statistics | 3 |
| SURV440 | Sampling Theory | 3 |
| SURV742 | Inference from Complex Surveys | 3 |
| Electives | 9 | |
| Total Credits | 46 | |
Social and Psychological Science
| Course | Title | Credits |
|---|---|---|
| Required courses: | ||
| SURV615 | Statistical Modeling and Machine Learning I | 3 |
| SURV616 | Statistical Modeling and Machine Learning II | 3 |
| SURV720 | Total Survey Error and Data Quality I | 2 |
| SURV721 | Total Survey Error and Data Quality II | 2 |
| SURV772 | Survey Design Seminar | 3 |
| SURV617 | Applications of Statistical Modeling | 3 |
| Fundamentals of Data Collection I | 3 | |
| Fundamentals of Data Collection II | 3 | |
| Fundamentals of Computing and Data Display | 3 | |
| Specialization requirements: | ||
| SURV625 | Applied Sampling | 3 |
| SURV630 | Questionnaire Design and Evaluation | 3 |
| SURV632 | Cognition, Communication and Survey Measurement | 3 |
| SURV701 | Analysis of Complex Sample Data | 3 |
| Fundamentals of Inference | 3 | |
| Electives | 6 | |
| Total Credits | 46 | |
Data Science
| Course | Title | Credits |
|---|---|---|
| Required courses: | ||
| SURV615 | Statistical Modeling and Machine Learning I | 3 |
| SURV616 | Statistical Modeling and Machine Learning II | 3 |
| SURV720 | Total Survey Error and Data Quality I | 2 |
| SURV721 | Total Survey Error and Data Quality II | 2 |
| SURV772 | Survey Design Seminar | 3 |
| SURV617 | Applications of Statistical Modeling | 3 |
| Fundamentals of Data Collection I | 3 | |
| Fundamentals of Data Collection II | 3 | |
| Fundamentals of Computing and Data Display | 3 | |
| Specialization requirements: | ||
| SURV625 | Applied Sampling | 3 |
| SURV701 | Analysis of Complex Sample Data | 3 |
| Fundamentals of Inference | 3 | |
| Electives | 12 | |
| Total Credits | 46 | |