This is a fantastic explanation (which I like better than the ‘simple’ explanation retired urologist links to below), and I’ll tell you why.
You’ve transformed the theorem into a spatial representation, which is always great—since I rarely use Bayes Theorem I have to essentially ‘reconstruct’ how to apply it every time I want to think about it, and I can do that much easier (and with many fewer steps) with a picture like this than with an example like breast cancer (which is what I would do previously).
Critically, you’ve represented the WHOLE problem visually—all I have to do is picture it in my head and I can ‘read’ directly off of it, I don’t have to think about any other concepts or remember what certain symbols mean. Another plus, you’ve included the actual numbers used for maximum transparency into what transformations are actually taking place. It’s a very well done series of diagrams.
If I had one (minor) quibble, it would be that you should represent the probabilities for various hypotheses occuring visually as well—perhaps using line weights, or split lines like in this diagram.
But very well done, thank you.
(edit: I’d also agree with cousin_it that the first half of the post is the stronger part. The diagrams are what make this so great, so stick with them!)
This is a fantastic explanation (which I like better than the ‘simple’ explanation retired urologist links to below), and I’ll tell you why.
You’ve transformed the theorem into a spatial representation, which is always great—since I rarely use Bayes Theorem I have to essentially ‘reconstruct’ how to apply it every time I want to think about it, and I can do that much easier (and with many fewer steps) with a picture like this than with an example like breast cancer (which is what I would do previously).
Critically, you’ve represented the WHOLE problem visually—all I have to do is picture it in my head and I can ‘read’ directly off of it, I don’t have to think about any other concepts or remember what certain symbols mean. Another plus, you’ve included the actual numbers used for maximum transparency into what transformations are actually taking place. It’s a very well done series of diagrams.
If I had one (minor) quibble, it would be that you should represent the probabilities for various hypotheses occuring visually as well—perhaps using line weights, or split lines like in this diagram.
But very well done, thank you.
(edit: I’d also agree with cousin_it that the first half of the post is the stronger part. The diagrams are what make this so great, so stick with them!)