Sister:Just spent the last few minutes calculating Puxatony Phil's statistical accuracy. Of 114 years of forecasts, he has only been 39% accurate. Unfortunately, this means his shadow is not at chance, but instead is actually statistically *inaccurate* at p < 0.02 two-tailed. Based on his prognosis today, this makes me sad.

Sister's Friend:I'm not sure your statistical approach is valid, Laurie. I don't think long and short winters are equally likely, and Phil seems to have a bias towards seeing his shadow. We need to do a signal detection analysis.

Sister:Here are the actual stats in case anyone would like to run their own analyses: Sees Shadow- Phil was right 37 of 99 times. No Shadow- Phil was right 7 of 15 times

Sister's Friend:So early springs are more likely than long winters (69/114), and Phil tends to see his shadow more often than not (99/114). Since a shadow is supposed to predict a long winter, this accounts for the negative relationship. But that doesn't make Phil a useful anti-guide: d' = -0.4, which is pretty near chance.

Sister:Great work, [Friend]. Also nice to see that early springs are slightly though not statistically more likely than late winters.

For reference: http://www.lifeslittlemyst

That's awesome. This conversation reminded me of my graduate school days learning to use statistics and playing with data on a program called SPSS (I have a Masters and BA in applied psychology). I'd love to see that raw data on Puxatony's Phils and mess around with it.

ReplyDeleteOh, and the lifeslittlemysteries is an awesome website I haven't seen before! Bookmarked as well.

ReplyDeleteThanks for the kind words, Joey. It always makes my day to hear when people enjoy what I write, even if the only people who read it have advanced science degrees :-)

ReplyDeleteAw man, I think ANYBODY would benefit from this stuff if they just gave it a chance. I guess we're the few people who didn't get fully intimidated by this logic/math stuff. [There's a Fermi problem in there somewhere ;-)]

ReplyDeleteIn grade school I had horrible math teachers who made the subject frightening to me and it was only in college that I learned to appreciate this kind of stuff again.