This is a different kind of post, but one that I think is kind of fun. I currently live in Ottawa, which for those who don’t know, is the capital city of Canada. For a capital city, it’s fairly small, but it’s increasingly urbanizing (we just got lightrail transit). Segregated bicycle lanes and paths are becoming more common too and many of these paths have trackers on them that count how many bicycles cross a particular street or path each day.
This past summer, I watched a brilliant lecture series by Richard McElreath on Bayesian statistics. It honestly changed my whole outlook on statistics, so I couldn’t recommend it more (plus, McElreath is an engaging instructor). One of the most compelling cases for using Bayesian statistics is with a collection of statistical tools called linear mixed models or multilevel/hierarchical models. It’s common that data are grouped or clustered in some way.