DATA 4080: Introduction to Causal Inference
This 3-credit hour course provides an introduction to the fundamental problem of causal inference and data-oriented methods to estimate causality. A variety of experimental and quasi-experimental methodologies will be covered in addition to considerations of logic, design, and ethical issues associated with the collection and use of experimental data. The course is designed for students from any major with real-world examples drawn from the social and behavioral sciences, economics and finance, biology, history, anthropology, conflict studies, health, development, and government.
Course Goals
- Understand the fundamental problem of causal inference.
- Evaluate the approaches to detecting causality and the advantages and disadvantages of each.
- Explain the ethical issues associated with experiments.
- Summarize the limitations of traditional regression-based methodologies.
- Utilize several alternative methodologies to generate causal estimates from data.
- Become proficient using open-source software and other technologies for experimental data analysis.
Prerequisites
DATA 3520: Data Analysis or another course in data or statistical analysis may be used to meet the prerequisite requirement with approval of the instructor.
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