Is Your Model So Dependent on the Prior?

The more dity you get, the narrower the distribution gets. It's a self consistent way of building up these inferences. But we have to be careful, right? Because that narrow ing does rely on the assumptions that we put into our model. If you build a bad model, it will narrow to a bad value,. It will pull away from what we actually see. And so alwas to be cognizant of that, right? In frequent tis inference, there's thi feeling of walk is, choose this model, this likelihood, and then i'm done and i get some answer out. Unfortunatelythat's a misreading of how frequent statistics work. To do a