Regression Discontinuity Design and Instrumental Variables | Causal Inference in Data Science Part 4

[@jinsoochung6964]

wow honestly, one of the easiest & most practical way to learn casual inference. Thank you Emma and Yuan.

[@eitoruchan]

Emma, I have to say the work you do is simply amazing. I’m working on my master degree’s thesis, which is on causality, and these videos with Yuan have been beyond helpful - not to mention that I owe you the last job I got, as I watched your channel day and night when I was preparing for the interviews :) congrats and keep up with the good work!

[@evasun531]

This is great content! I know it's pretty hard for us non-native speakers, but I notice there're a lot of filling words which impact the flow of learning. If this can be improved this video will be awesome!

[@emma_ding]

Thanks a lot for the feedback, Eva!

[@xinyaohui1919]

thanks a lot!!

[@omersarigul92]

thanks a lot

[@Stanmay1]

Hi! All of your videos are super helpful. Could you please make a video on the incremental effects of marketing interventions?

[@emma_ding]

Great suggestion!

[@karad.2473]

I didn't quite get making the birth season as the IV for school year, why don't we use a binary variable as finished high school or not instead? A bit confused on why we need a IV here and what does "reduced form", "1st stage" mean in the formula?