In qualitative research, a "code" is the most basic building block. But what can a code look like, and how do you do coding? We give you the background you need.
The more we understand the ways the system of privilege operates and is reflected in many institutions and organizations, the more we'll be able to address it and combat these inequities on a larger scale. This module provides some starting points for approaching these issues.
This module of the Causal Inference Bootcamp explains the basic concepts of IV analysis and how social scientists use it to indirectly find causality in their data.
We've covered a lot of ways to look at your data to find causal connections, but in the real world, you usually don't get a perfect dataset or a simple situation where assumptions can be foolproof. How do we balance the strength of our data with the strength of our assumptions?
This module uses regression discontinuity to analyze how a school's quality affects the price of houses in its assignment area.
The Local Average Treatment Effect (LATE) can be helpful when noncompliance is an issue. This module will walk you through how to compute the LATE and how to interpret it.