Seeing Theory: A visual introduction to probability and statistics (2017)
Glad to see this once more.<p>Some Hacker News Discussions of this:<p>1. <a href="https://news.ycombinator.com/item?id=13735714" rel="nofollow">https://news.ycombinator.com/item?id=13735714</a><p>2. <a href="https://news.ycombinator.com/item?id=13760353" rel="nofollow">https://news.ycombinator.com/item?id=13760353</a><p>I wish they'd cover the sample space/parameter space distinction "harder", as it seems key to the numerous philosophical divides in the foundations of statistics & probability theory, and it seems like a very good candidate for colorful & animated visualization.<p>Also, note that the classic coin flipping example used there right in the beginning serves as an extremely bad & misleading analogy, see here for why:<p><a href="https://econ.ucsb.edu/~doug/240a/Coin%20Flip.htm" rel="nofollow">https://econ.ucsb.edu/~doug/240a/Coin%20Flip.htm</a><p>I wish we'd stop using it in Stats & Physics 101, or at least add huge disclaimers to it, something like "Coins don't actually behave this way, not even mathematically idealized ones".