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People make conclusions based on tiny sample sizes when the results fit their biases. Most studies are worthless due to small sample sizes and confounding vari
by danenania 5y ago
People make conclusions based on tiny sample sizes when the results fit their biases.
Most studies are worthless due to small sample sizes and confounding variables, and most “conclusions” are based on cherry-picked outliers. The fact that it’s common to do this doesn’t make it responsible or correct.
- anthonypasq 5y agohave you taken intro statistics? all small sample sizes do is require your effect to be more pronounced to still be statistically significant.
- danenania 5y agoAh, then I guess that's why so few "statistically significant" studies end up being contradicted by further research...
- myfavoritedog 5y agoYeah, given the track record of surveys/studies, you’re better off assuming the opposite conclusions that they claim to validate.
- mactrey 5y agoYou make it sound like those studies were bad because the sample size was too small. In reality bad study design or having an unrepresentative sample are more common issues.
- danenania 5y agoI think they go hand-in-hand. People naively apply intro-level statistics to messy real-world problems and then think they need an orders of magnitude smaller sample than they would need to even hint at the possibility of an interesting effect.
- majormajor 5y agoNeither a bad experiment nor an unrepresentative sample will be helped by a larger sample size, though.
- danenania 5y agoTrue, though no sample is ever truly representative along every dimension. Even when a lot of effort is put into making a sample as representative as possible, there will be variance in all the potential ways the sample can diverge from the population; this variance seems to be consistently underestimated.
- deleted 5y ago[deleted]