FWIW, during this whole process, people reasonably described as “arm chair statisticians” have been putting out higher-quality and more accurate statistical analysis than any public-facing government or media source. The only high-quality analysis I’ve seen has been from “amateurs” (I.e. not employed by institutional sources of narrative information) and expensive subscription-only financial analysis services.
What is the size of the population of amateurs and what is the size of the population of experts? I am guessing the former is a lot bigger than the latter meaning more outcomes to pick from when retroactively trying to assign credit for accuracy.
What special knowledge do you think you need to interpret 5 months of COVID studies? That's almost two semesters of grad school.
You don't need a PhD to gain enough knowledge of covid from literature to speculate meaningfully on an internet forum, especially if you already have a graduate degree and practice research, as many people undoubtedly on HN do.
It sounds like you took offense to my comment which wasn't my intent. I was just making a lighthearted stats critique of someone complaining about statisticians.
That said, I think statistics is like most other skills in that you get better at it the more you do it. All things being equal, I would trust the person who has spent more time thinking about a subject.
There was a comprehensive literature review posted on /r/coronavirus some two months ago that strong (and statistically robust in my opinion as a professional data scientist) indicating that smokers were less likely to be infected with the virus, with possible mechanisms from previous viruses like SARS and MERS.
In fact that was one of the earliest common sources to mention ACE2 receptors. A month or so later there is at least one study looking at nicotine patches as prophylactic and/or treatment for covid. I'm having trouble finding the reddit thread, standby.
I opened the first link and went to the post exactly from a month ago to see what it said. This part was strangely fitting considering your original complaint:
>Having said all that, I am also dismayed that laymen put such pressure on epidemiologists to make forecasts. Imagine if it was your job when you see a leaf falling from a tree 40 feet overhead to place your foot on the exact spot where you “forecast” that the leaf will land.
eh lots of people could tell ihme model was wrong/doing inappropriate curve fitting, but los alamos model for example seems pretty good to me, as an armchair statistician.
FWIW, during this whole process, people reasonably described as “arm chair statisticians” have been putting out higher-quality and more accurate statistical analysis than any public-facing government or media source. The only high-quality analysis I’ve seen has been from “amateurs” (I.e. not employed by institutional sources of narrative information) and expensive subscription-only financial analysis services.