This video provides an intuitive idea of the potentially complicated topic of quantile regression.
The video starts by discussing the case of OLS (Ordinary Least Squares) regression as the conditional mean, before discussing the cases of the conditional median (i.e. median regression) and conditional quantiles (quantile regression). The video explains why quantile regression cannot be estimated at the 0% and 100% quantiles, and explains why quantile regression is more robust to outliers on the dependent variable than OLS.
The video shows figures and graphs as well as some code in R software, although viewers can follow the video without any knowledge of R software.
The R code and slides that accompany this video are freely available from my github page:
https://github.com/alexcoad/Econometrics