101–110 of 248 posts
I'm not sure why this sort of thing impresses people, it's obvious the 1984 ghostbuster group skews old.
Earlier quoted context omitted.
I agree that people could have a more effective BS filter, but I think there’s also some obligation to not publish BS in the first place at the risk of your trustworthiness reputation. People intentionally or repeatedly inadvertently publishing BS should be called out and their opinions down-weighted heavily. People having a good BS filter is one step in the chain towards this down-weighting, but isn’t the whole chai…
The post does exactly this, calling out Alex Berenson by name - but despite its best efforts, it will have very little impact on the people paying him to receive BS directly from his Substack. I don't think your opinion is unpopular because it's wrong. It's unpopular because it's empirically impractical. People don't suffer a reputational hit for publishing BS, and saying "But they should" doesn't get us anywhere (as…
Elizabeth Holmes is on trial for lying about things where she had a specific legal obligation to tell the truth. I’d never heard of Alex Berenson before today, but I doubt his situation is one in which he’s obligated to tell the truth. That’s okay. Sunday school preachers aren’t either and we’re cool with that. We’re good with the Santa and Easter Bunny myths.
This sort of thing is why "do your own research" is simply not plausible advice for 99% of people, even highly educated intelligent people with time on their hands. Most of the high level problems in our civilization require years of study to even be capable of formulating a valid opinion. The thing people have to do is to instead focus on evaluating people and deciding who probably knows who they are talking about.…
This is hard, possibly just as hard as “doing your own research”.
This reminds me of the sort of light poking of common "correlation is not the same as causation" and "beware of confounding factors" statistical failures behind the Church of the Flying Spaghetti Monster "clearly reduction in pirates has caused global warming!" [0]. But it's a major in modern public discourse, and one for once that I'm quite willing to lay heavily at the feet of the public education system. Easily on…
Earlier quoted context omitted.
No, most of those are "actually spurious" in the sense of the two time series having nothing to do with each other. A lot of them are pretty short series as well, so it's easy for them to be correlated. What we are looking at is Simpson's Paradox, where the true causal relationship is obscured by information that isn't obvious from the plot. Now before you correlation != causation, there is actually a causation here…
Simpson’s paradox is when a trend or correlation is observable in each of the sub-populations, but vanishes when the data is aggregated. For example, a drug that has a strong effect on men and women when analyzed separately, but shows little effect at the population level. This example is not Simpson’s paradox, it is simply the misuse of statistics. Statistics, being mechanical transformations of data, only have sema…
Yes, smugly mocking people's very valid concerns will surely win them over. Don't study the figures, just do as we say!
This reminds me of the sort of light poking of common "correlation is not the same as causation" and "beware of confounding factors" statistical failures behind the Church of the Flying Spaghetti Monster "clearly reduction in pirates has caused global warming!" [0]. But it's a major in modern public discourse, and one for once that I'm quite willing to lay heavily at the feet of the public education system. Easily on…
Statistics are meaningless without a rigorously examined causal model of the phenomenon under investigation. In my experience of statistics education, the art of crafting causal theories was scarcely addressed.
If we can get there, then we can talk about what we can do to improve things from there.
Earlier quoted context omitted.
No, most of those are "actually spurious" in the sense of the two time series having nothing to do with each other. A lot of them are pretty short series as well, so it's easy for them to be correlated. What we are looking at is Simpson's Paradox, where the true causal relationship is obscured by information that isn't obvious from the plot. Now before you correlation != causation, there is actually a causation here…
Simpson’s paradox is when a trend or correlation is observable in each of the sub-populations, but vanishes when the data is aggregated. For example, a drug that has a strong effect on men and women when analyzed separately, but shows little effect at the population level. This example is not Simpson’s paradox, it is simply the misuse of statistics. Statistics, being mechanical transformations of data, only have sema…
If you read to the end of the post, you'll see that the author was using this correlation to prove that the mistake is identical to another claim related to COVID [1]. This COVID-related correlation doesn't seem as spurious as the Ghostbusters one, but that's because it's much harder to spot errors like this when variables aren't so "random".
[1]: "Vaccinated English adults under 60 are dying at twice the rate of unvaccinated people the same age"
Tl;dr someone fell for Simpson's paradox [0] and wrote a (probably 'viral') post on how Covid-19 vaccines are killing us; this is a (slightly confusing at first without context, I thought - especially because it starts of joking about correlation/causation that seems a bit different to me) rebuttal. [0] - https://en.wikipedia.org/wiki/Simpson%27s_paradox#Correlatio...
Alternative explanation: He didn't "fall for" anything -- he's cynically exploiting a weakness in the UK stats presentation, with the help of selective citation, on a project of self-aggrandization. Try a scroll through the blog history. https://alexberenson.substack.com/