I'm rereading my statistics book and wanted to better understand the effects on the distribution function when the number of samples and the probability changes so I created this:

It's interesting to me that the maximum probability is at a minimum when p=0.5 and goes to a maximum at p=[0,1]. This is entirely obvious at the extreme — if something is certain to happen (or not happen), then it's going to happen (or not happen) every single time.

I started this as an R notebook with ggplot graphs and then made it interactive with shiny, which I really liked - and then layered on ggplotly which added some nice features but I ended up scrapping all that for javascript/d3 because I didn't want to have R running on my little host all the time.

The source code is available on github