Those with economics degrees are in high demand in a large number of occupations, whether in business or government; students with advanced econometrics skills who understand how to apply these techniques in real-world settings are in even higher demand. This Certificate in Applied Econometrics and Data Analysis is designed to provide the education needed for employment in analysis positions in business or government. The Certificate is a valuable credential for economics majors with a quantitative focus, (applied) math majors, and selected students from other social sciences.
The Certificate consists of 6 courses met through 3 required courses and 3 electives which must be selected from the list below. At least 4 of these courses must be completed in residency at UMSL.
(Note that all of these courses have prerequisites that the student must complete before taking the selected course.)
| Required Courses | ||
| ECON 4100 | Introduction to Econometrics | 4 |
| ECON 4110 | Applied Econometrics | 4 |
| ECON 4120 | Time Series Econometrics for Economics and Finance | 4 |
| or ECON 4130 | Business and Economic Forecasting | |
| Electives | ||
| The remaining 3 electives must come from the following list: | 9-10 | |
| Booms and Busts in the Economy: Data and Theory | ||
| Time Series Econometrics for Economics and Finance (if course not used above) | ||
| Business and Economic Forecasting (if course not used above) | ||
| Geospatial Analysis in the Social Sciences | ||
| Business Forecasting (may not be used with ECON 4130) | ||
| Mathematical Statistics I | ||
| Mathematical Statistics II | ||
| Survey Research Practicum in Political Science | ||
| Psychological Testing and Assessment | ||
| Survey Research Practicum for Sociology | ||
SOC 4331 | ||
Learning Outcomes
- Use statistical software to estimate, analyze, and interpret economic relationships applying regression analysis techniques to data.
- Develop appropriate econometric models using real-world data to make management or policy recommendations in a variety of professional settings.
- Apply key concepts of estimation and forecasting in a time series context.