• We wrap up the Causal Inference Bootcamp by looking at how the different techniques we've talked about can work together, and what choices you might have to make as you start your analysis of 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?