Bayesian Storytelling
I launched a newsletter yesterday. So far, the feedback has been good. A few readers said that they felt drawn in by the writing. In any case, the purpose of the first few posts is simply to get myself warmed up. Any extra flutter the posts generate is a bonus. Amit Varma recommends not looking at the stats for a couple of years.
It taught me quite a few things. Particularly that I need to be smart about the data analysis. It’s important to remember that this isn’t a work project. It’s meant for a general audience, so there is such a thing as too much detail. For example, detailed handwritten notes on every single table in the HCES isn’t important. You could have dealt with each table independently. Only focusing on the tables needed for the problem in question should have sufficed. On the other hand, cleaning and denormalizing the data and releasing it on GitHub was a good idea; and the tweet announcing this has 10 reposts, 69 likes, 52 bookmarks, and has gained me 12 new followers. This is what Austin Kleon calls “showing your work” (Mahima Vashist says “your journal is your art”). Perhaps one needs to think carefully about what shareable and useful assets can be created in the service of a larger, transcending work.