I know, I know. It's been a while since I've posted anything. Crazy-busy semester. Again. I'll be back in action soon, but in the meantime have a look at this amazing animation showing why (classical) measurement error leads to attenuation bias. It looks like you can even make the animation yourself in R. Thank you, Lionel Page, for tweeting about this and Maarten van Smeden for making it.
It always made sense to me: Random noise has zero correlation with anything. As you add more noise to a variable, you'll get closer to that zero correlation. But to see it in an animation, that's just really cool.
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