Significant other is out of the "might die" zone. Has pneumonia in one lung, a GI infection and a bladder infection, but is recovering.
This is a very good thing, as the alternative would fuck up my life beyond all reckoning.
Well holy shit, I'm glad she's out of that zone. I hope she gets back into the "completely healthy" zone with all deliberate speed because good lord that sounds like God just went down the list of afflictions, checking boxes at random.
In an issue close to my heart, the US statistical association has made an official policy statement arguing against an over-reliance on p-values in scientific reasoning and clarified their definition.
FUCKING FINALLY. FUCKING finally. This opens up so many doors and relegitimizes so many fields that have been "discredited" because they don't readily admit statistical analysis. FINALLY. This is going to be a really, really important thing in helping science and fighting scientism.
yes
yesYESYeah, p-values sorta rely on sufficient sample sizes to get to levels where results are called "statistically significant", don't they? Which is absolutely impossible to get in certain circumstances without either something really weird happening or something really unethical happening.
Plus, ain't they sorta... frequentist?
this might be the last thing you said, but one of the gripes i have about the methodology is that,
by definition, 5% of all results are false if you're just relying on p-values - and let's not even get started on
spurious correlations, which i'm sure you're familiar with but which i love linking even when they're tangential at best
edit: there's lots of problems, and mine might be the most trifling of the lot - it sounds like vector, you, and i all have different concerns but we can all celebrate this
EDIT: Reading the statement, it appears that many of the things I thought I liked about this are due to misconceptions that this very statement was clearing up! So, while the bit about 5% of results being false isn't actually a real thing, the fact that I thought that in the first place suggests something isn't working right somewhere and that this was necessary.