I did not mention a lot of assumptions. For example my problem statement also does not answer the question if Monty always gives you a choice to switch or only when you picked in a certain way. There are quite a few possible variations, all of which change the answer: https://en.wikipedia.org/wiki/Monty_Hall_problem#Other_host_...
In the derivation of the likelihood the assumptions are clearly stated.
While my knowledge on statistics is certainly unsatisfactory, your assessment of the education I had is quite wrong. My final exam in order to obtain a Master's degree in mathematics is next week. One of the subjects I chose is Bayesian Statistics, so wish me luck.
I do wish you luck. Fwiw I'd always work forward from the question and talk to the ambiguities present especially when people may come across this and not realize. Stating the Bayesian probabilities of one possible interpretation and having that as your way of stating assumptions is a bit like working backwards from one possible answer.
As an example of how presenting this way can hurt; The link you had for the sisters paradox doesn't talk to the ambiguities of a question that is well known to have no answer - https://en.wikipedia.org/wiki/Boy_or_girl_paradox . This information spreads and people see it restate it. This leads to a false belief that the sisters paradox has no ambiguities and that the answer is clearly 1/3 (the wikipedia page on this has the correct statement that it's ambiguous and the answer can be 1/3 or 1/2 depending on one of two reasonable interpretations).
I think a far better article would talk to ambiguities of each of these. Not subtly stating assumptions. I'll also point out that these types of ambiguous questions are commonly used in DS interviews (I've worked in big tech for many years now). The expected response of a strong candidate is a discussion on the ambiguities. You'll usually be prompted "is there any other interpretation of this question that leads to a different result?". If people read this as their guide rather than the more detailed wikipedia articles etc they may be misled which is why i'm strongly negative on this article as written. I'd hope no one reads and doesn't realize the assumptions here since they are critical.
In the derivation of the likelihood the assumptions are clearly stated.
While my knowledge on statistics is certainly unsatisfactory, your assessment of the education I had is quite wrong. My final exam in order to obtain a Master's degree in mathematics is next week. One of the subjects I chose is Bayesian Statistics, so wish me luck.