It doesn’t seem reasonable to say you’ve confirmed the 11% alternative.
In the context of the Bayesian confirmation theory, it’s not you who “confirms” the hypothesis. It’s evidence which confirms some hypothesis and that happens at the prior → posterior stage. Once you’re dealing with posteriors, all the confirmation has already been done.
what if you have to make this decision multiple times?
Do you get any evidence to update your posteriors? Is there any benefit to picking different alternatives? If no and no, then sure, you repeat your decision.
That would lead to status quo bias.
No, it would not. That’s not what the status quo bias is.
You keep on using words without understanding their meaning. This is a really bad habit.
If your problem is which tests to run, then you’re in the experimental design world. Crudely speaking, you want to rank your available tests by how much information they will give you and then do those which have high expected information and discard those which have low expected information.
In the context of the Bayesian confirmation theory, it’s not you who “confirms” the hypothesis. It’s evidence which confirms some hypothesis and that happens at the prior → posterior stage. Once you’re dealing with posteriors, all the confirmation has already been done.
Do you get any evidence to update your posteriors? Is there any benefit to picking different alternatives? If no and no, then sure, you repeat your decision.
No, it would not. That’s not what the status quo bias is.
You keep on using words without understanding their meaning. This is a really bad habit.
When I say throw out I’m talking about halting tests, not changing the decision.
If your problem is which tests to run, then you’re in the experimental design world. Crudely speaking, you want to rank your available tests by how much information they will give you and then do those which have high expected information and discard those which have low expected information.
True.