When I started work at Brilliant a couple of weeks ago, I learned that one of my new colleagues, Michelle McSweeney, just published a book called OK, which is all about the word OK.

As we discussed the joys and miseries of publishing, Michelle mentioned that she had found a typo in the book after publication. So naturally I took it as a challenge to find the typo. While I was searching, I enjoyed the book very much. If you are interested in etymology, linguistics, and history, I recommend it!

As it turned out, I found exactly one typo. When I told Michelle, she asked me nervously which page it was on. Page 17. She looked disappointed – that was not the same typo she found.

Now, for people who like Bayesian statistics, this scenario raises some questions:

1. After our conversation, how many additional typos should we expect there to be?
2. If she and I had found the same typo, instead of different ones, how many typos would we expect?

As it happens, I used a similar scenario as an example in Think Bayes. So I was able to reuse some code and answer these questions.

You can read my solution here.

You can also click here to run the notebook with the solution on Colab.