I saw a neat twitter thread from Zachary Binney last week:

The ideas in Binney’s thread are really important if you want to understand testing, so I thought I’d share them with the boys this morning. We started by looking at the thread and then going to Wikipedia to get a few definitions:

Now we went through a few specific examples. For all three we assumed the test was 95% accurate. In our first example we assumed that 5% of the population would have a disease. What is your chance of having the disease if you test positive?

Next we looked at what would happen if only 1% of the population has the disease (sorry the camera wasn’t showing the bottom of the white board here ðŸ˜¦ ):

Finally we looked at what would happen if 30% of the population had the disease:

The problem we are looking at here is a pretty famous one in probability and statistics. Binney’s twitter thread made for a great opportunity to show how the ideas aren’t just theory or problem set problems, too.