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midnightking t1_jdxbyz0 wrote

Yep, a good example is anything to do with racial bias.

''OK but did this study control for [insert variable].''

And then you open the study and it has already been controlled for.

Another thing I saw with a lot of studies on police violence and hiring discrimination where people in comments will say it's class and then when you show them a study that did try to control for class and still found an effect, they move the goalpost.


Darwins_Dog t1_jdxta49 wrote

My favorite was the article about a recent uptick of strokes in young people. So many comments blaming the COVID vaccines but the data in the study was from 2018.


nerd4code t1_je05bcc wrote

Damn that Fauci, stuffin’ ’em vaccines fulla tachyons!


Stalagmus t1_jdzy532 wrote

This right here is what I see as the biggest problem on this sub. The top comments are always questioning the fundamental accuracy and utility of statistical analysis; sample size, sample composition, controls, confounding factors, bias, etc, despite all of these things essentially being statistics 101 that any undergrad would know to do. These aren’t advanced concepts that entire teams of professional scientists using outside funding somehow forgot to address, and that the entire scientific community somehow didn’t catch these basic problems and allowed the research to be published anyway.

What is really happening is that Redditors find a study in which they don’t agree with the conclusion, and proceed to undermine the credibility of the study (or the field) until other people start agreeing with them.