5 ms·

Correlation is usually accidental. e.g. http://www.tylervigen.com/spurious-correlations http://www.tylervigen.com/spurious-correlations

josquindesprez 9y ago
Saying that correlation is usually accidental is a stretch. Basing that claim on that (admittedly amusing) website is even more of a stretch: the time series on that website are all highly autoregressive with minuscule sample sizes, which makes spurious correlations extremely likely [1]. Speaking (very) roughly, the fact that they are autoregressive constrains how 'kinky' the shapes can be. Visually speaking, the time series will have a small number of inflection points and will appear interpolated between these points. This greatly reduces the search space: you just need to line up a couple of kinks in a space of ten samples, or match two smooth and vaguely line-shaped objects, rather than find a convincing relationship for 100s of observations not tied together in time. [1] http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.611.5055&rep=rep1&type=pdf http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.611...
- kbutler 9y ago
  I've got some homeopathic remedies to sell you. People took them, and they got better!
TimPC 9y ago
I think if you measure random unrelated data sets against each other you're quite likely to find spurious correlations. If you design an experiment between potentially related variables with a potential hypothesis on how they are related and then observe data that matches the hypothesis, you probably have a reasonable chance the hypothesis is actually the explanation.
- surement 9y ago
  That is the point of experiments.
esmi 9y ago
I see your blog post and raise you a youtube video. minutephysics Correlation CAN Imply Causation! | Statistics Misconceptions https://www.youtube.com/watch?v=HUti6vGctQM https://www.youtube.com/watch?v=HUti6vGctQM

josquindesprez 9y ago

Saying that correlation is usually accidental is a stretch. Basing that claim on that (admittedly amusing) website is even more of a stretch: the time series on that website are all highly autoregressive with minuscule sample sizes, which makes spurious correlations extremely likely [1]. Speaking (very) roughly, the fact that they are autoregressive constrains how 'kinky' the shapes can be. Visually speaking, the time series will have a small number of inflection points and will appear interpolated between these points. This greatly reduces the search space: you just need to line up a couple of kinks in a space of ten samples, or match two smooth and vaguely line-shaped objects, rather than find a convincing relationship for 100s of observations not tied together in time. [1] http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.611.5055&rep=rep1&type=pdf http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.611...

kbutler 9y ago
I've got some homeopathic remedies to sell you. People took them, and they got better!

TimPC 9y ago

I think if you measure random unrelated data sets against each other you're quite likely to find spurious correlations. If you design an experiment between potentially related variables with a potential hypothesis on how they are related and then observe data that matches the hypothesis, you probably have a reasonable chance the hypothesis is actually the explanation.

surement 9y ago
That is the point of experiments.

esmi 9y ago

I see your blog post and raise you a youtube video. minutephysics Correlation CAN Imply Causation! | Statistics Misconceptions https://www.youtube.com/watch?v=HUti6vGctQM https://www.youtube.com/watch?v=HUti6vGctQM