• This module includes all of the experiments from the Causal Inference Bootcamp and discusses how treatments and controls can exhibit causal effects.

  • This module covers different examples of social science experiments to show you how they're set up and what they can reveal.

  • Get started with the basics of social science experiments in this module.

  • This module goes through a few examples of how natural experiments have been used to discover causal effects.

  • When experiment subjects don't do as requested, it can cause problems with your experiment and your data collection. This module covers some of the basic ways to deal with noncompliance.

  • When survey subjects don't respond as instructed, it can create issues for your survey data. This module covers what options researchers have for proceeding when subjects don't answer questions.

  • This module describes the basics of setting up and analyzing a randomized experiment, and why they can be hard to find in social science.

  • The deadly London Cholera Outbreak of 1886 is a fascinating and pivotal moment in the history of public policy, epidemiology, and social science. Learn about what happened, and how one early scientific trailblazer turned it into a critical teaching moment.

  • The Oregon Healthcare Experiment was one of the most comprehensive studies ever done on the effect of healthcare coverage. In this module, we cover it from initial assumptions and setup to its results.

  • This landmark study examined the long-term effects of providing preschool to underprivileged children. This module describes how the scientists were able to find causal effects in the study.

  • When the Argentinian government gave property rights to squatters living on largely unclaimed land, the opportunities for natural experiments arose to see what health, economic, and other effects might come from this policy change. This module walks through a couple of examples.

  • Experiments don't always go smoothly. This module covers some of the main challenges you might face when planning and conducting an experiment.

  • If you run an experiment, what are the best ways to deal with the data you get out of it? What are the pitfalls you should avoid? This module will get you started.