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 Alex explains Bayes' rule - Lindsey Kuper [entries|archive|friends|userinfo]
Lindsey Kuper

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 Alex explains Bayes' rule [Nov. 4th, 2009|08:39 pm] Lindsey Kuper More tales from the apparently Frozen Boreal Wasteland: Alex : *drawing a diagram* So, P(H) is the probability that it's a hot day, and P(I) is the probability that you see someone eating ice cream. Lindsey: And P(I|H) is the probability that you see someone eating ice cream... Alex: ...given that it's a hot day. Lindsey: *squinting* Okay. Let's say P(H) is, oh, I dunno, .1? Alex: Well, around here. It was 61 degrees today, by the way. Barely fall weather at all. I actually got sweaty raking leaves in the yard. (Previously.) Link Reply

Comments:
(Deleted comment)
 From: 2009-11-05 05:29 am (UTC) (Link)
It just happened to spring to mind! It was better than my first example: estimating whether somebody's from Italy, based on whether they're speaking Italian.

Which Jason?
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(Deleted comment)
 From: 2009-11-05 05:29 am (UTC) (Link)
Isn't the "hot days boost ice cream sales and murder rates" thing everyone's favorite correlation-versus-causation example?
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 From: 2009-11-07 03:46 pm (UTC) (Link)
It's mine. :D I've used it at least 5 times before.
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 From: 2009-11-07 03:47 pm (UTC) (Link)
But what I want to know is: does anyone have a good necessary versus sufficient causes example? I tried to explain that to some college freshmen and they were completely befuddled.
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 From: 2009-11-05 03:28 pm (UTC) (Link)
High of 83 on Sunday! It's been three years and "winter" here still confuses the heck out of me. Most of the people in my lab get cold when it's still in the 70s. :)
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From:
2009-11-05 04:35 pm (UTC)

### Hey look, conditional probability...

Aw man, I just can't get away from any of it!

**Is taking Psych 204 and Intro. Statistics right now**
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