methodology

feature / methodology / predictions / probability — 2 Comments
5
Mar 13

My favorite randomization device

My recent look at JavaScript as a contender for statistical modeling got me thinking about the different methods used to create random variates. All computers algorithms create Type 1 randomness, which is to say, completely deterministic once you either figure out the underlying algorithm or once you see every number in the algorithm’s period. Jumping outside of software to the hard world around us, it seems possible to create Type 2 or even Type 3 randomness, at least from perspective of an observer who can’t base their predictions on real-time analysis of the generating mechanism (ie, they can’t watch it tick).

My favorite example of a real-world solution to randomizing is shown in the video at top. More details about the construction of the device are here.

What’s your favorite (hardware or virtual) randomization device?

epistomology / feature / humor / methodology — 1 Comment
11
Dec 12

“We didn’t even bother to get the $7 coffee”

A couple weeks ago I highlighted the recommendation that researchers test their models (and the processes which generated them!) against random noise. This is an important “reality check” of their methods, to see how susceptible they are to detecting something in nothing. In the video above, Jimmy Kimmel gives a nice illustration of how this idea could be extended to a taste test, or any survey where participants are asked to differentiate between samples. Kimmel’s experiment also gives a nice illustration of how humans can be primed to find what we expect to find, even if it’s not there.