I don’t think you’re missing anything. Bayesian reasoning allows you to treat your data without introducing errors, but the results you come up with are a product of the available data and the prior model. This is a point that is often overlooked: if you start with a completely false model, even with Bayesian reasoning the data will get you further away from the truth (case in point: someone who believes in an invisible dragon which has to invent more and more complicated explanation for the lack of evidence). Bayesian probability is just the way of reasoning that introduces the least amount of error. To counter at least partially our fallibility, it’s considered good practice to:
never put any assumption at precisely 0 or 1 probability;
leave always a reservoir of probability mass in your model to unknown unknows.
Other than that, findind the truth is a quest that needs creativity, ingenuity and a good dose of luck.
I don’t think you’re missing anything. Bayesian reasoning allows you to treat your data without introducing errors, but the results you come up with are a product of the available data and the prior model.
This is a point that is often overlooked: if you start with a completely false model, even with Bayesian reasoning the data will get you further away from the truth (case in point: someone who believes in an invisible dragon which has to invent more and more complicated explanation for the lack of evidence). Bayesian probability is just the way of reasoning that introduces the least amount of error.
To counter at least partially our fallibility, it’s considered good practice to:
never put any assumption at precisely 0 or 1 probability;
leave always a reservoir of probability mass in your model to unknown unknows.
Other than that, findind the truth is a quest that needs creativity, ingenuity and a good dose of luck.