Data Science 241
Experiments and Causal Inference
This course introduces students to experimentation in the social sciences. This topic has increased considerably in importance since 1995, as researchers have learned to think creatively about how to generate data in more scientific ways, and developments in information technology have facilitated the development of better data gathering. Key to this area of inquiry is the insight that correlation does not necessarily imply causality. In this course, we learn how to use experiments to establish causal effects and how to be appropriately skeptical of findings from observational data.
Experimental design / Statistical analysis / Communicating results / Cleaning data / Mining and exploring data
Current Course Designers
Original Course Designers
Previously listed as DATASCI W241.
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