More like "here are the priors I'm plugging into the bright and shiny Bayes equation", without any indication of why the priors were plausible enough to be worth bothering with.
In Bayesian statistics there's the concept of 'weakly informative priors', which are priors that are quite broad and conservative, but don't concentrate almost all of their mass on values that no one thinks are plausible. For example, if I'm estimating the effect of a drug, I might choose priors that give low mass to biologically implausible effect sizes. If it's a weight gain drug, perhaps I'd pick a normal distribution with less than 1% probability mass for more than 100% weight increase or 50% weight decrease. Still pretty conservative, but mostly captu...
r/Fitness does a weekly "Moronic Monday", a judgment-free thread where people can ask questions that they would ordinarily feel embarrassed for not knowing the answer to. I thought this seemed like a useful thing to have here - after all, the concepts discussed on LessWrong are probably at least a little harder to grasp than those of weightlifting. Plus, I have a few stupid questions of my own, so it doesn't seem unreasonable that other people might as well.