3 ms·
Why do you think it's a bad thing for your beliefs to remain the same in the absence of new data?
by da39a3ee 3y ago
Why do you think it's a bad thing for your beliefs to remain the same in the absence of new data?
- Dylan16807 3y agoI didn't say anything about what should happen to your beliefs.
- da39a3ee 3y agoYou said that the prior dominating is a bad thing. The prior is your beliefs about a parameter prior to observing data (as I suspect you know!). Maybe I'm not getting what you're saying.
- Dylan16807 3y agoI was assuming these are general purpose statistics, which means you might want to share them with someone. It's bad for those to get tainted by your personal priors. If it's a purely personal calculation then sure that's fine.
- hnfong 3y agoThat's an interesting observation. Let's say you have a personal belief that something is going to happen with probability x. Would you actually want to tell others that the probability is y, because that's what the data says, without letting people know that for other reasons that are not reflected in the data, you truly believe it is x?
- Dylan16807 3y agoYou can give your informed opinion on the probability in addition to what you've derived from the dataset, but you shouldn't conflate them. Your informed opinion incorporates this dataset, but you shouldn't imply it's "based on" this dataset.
- da39a3ee 3y agoThat's fine and I would agree - you could share the summary statistic used, or the likelihood ratio between the null and some alternative models. But you shouldn't share a frequentist parameter estimate or confidence interval if you have prior information that would influence it non-negligibly, at least not without sharing that prior information also.
- scotty79 3y agoShould you have any beliefs in the absence of data? And if you have some prior data but no additional data now why carve out past as separate thing and call it prior? Why not just call everything you have - data?
- da39a3ee 3y agoThat's precisely how Bayesian inference works! But rather than having to repeat all analysis of prior data sets, we summarize that analysis in the form of a posterior, which becomes the prior for the next analysis.