Great security! Too much wear can be a bad thing. From cheezburger.com, thanks Laura.

## Monday, September 30, 2013

## Monday, September 23, 2013

### Simpson's Paradox

Simpson's paradox fools many. Percentages can favor women over men across each of several subgroups but then reverse, favoring men over women when the subgroups are combined into one. At one level this seems illogical. We seem to expect that patterns observed consistently for portions of a whole should also apply when the portions are aggregated together into one. This simple view misses lurking variables. In a famous example, graduate admission to Berkeley seemed biased against women when considered overall, but when the admissions were considered by individual departments there was no bias or bias in favor of women. The lurking variable is that "not all departments are equally easy to enter." and "the proportion of women applicants tends to be high in departments that are hard to get into and low in those departments that are easy to get into".

Lewis Lehe and Victor Powell at UC Berkeley have produced interactive applets to illustrate Simpson's paradox. As Flowing Data mentions "Sometimes when you zoom in, you see a completely opposite trend of what you saw overall".

We've considered Simpson's paradox before where even microbes can be used to illustrate it.

Lewis Lehe and Victor Powell at UC Berkeley have produced interactive applets to illustrate Simpson's paradox. As Flowing Data mentions "Sometimes when you zoom in, you see a completely opposite trend of what you saw overall".

We've considered Simpson's paradox before where even microbes can be used to illustrate it.

## Monday, September 16, 2013

### Top of the Line

Upscale neighborhood. Greatest frequency of wear is on the premium.

Forwarded by a colleague (thanks Jun). Originally, I think, from Reddit.

Forwarded by a colleague (thanks Jun). Originally, I think, from Reddit.

## Monday, September 9, 2013

### Probability WONK

.

Robert Jernigan WONK Challenge from American University on Vimeo.

I finally saw my American University WONK Challenge Spot on the Jumbotron at the Washington Nationals game on August 27. Here's me pointing, and the Nationals won!

Robert Jernigan WONK Challenge from American University on Vimeo.

I finally saw my American University WONK Challenge Spot on the Jumbotron at the Washington Nationals game on August 27. Here's me pointing, and the Nationals won!

Foul balls have really hit the news lately with a fan in Cleveland catching 4 in one game this last month! As I mention in the spot some put the probability of catching a foul ball in any
game at about 1 in 1000. This, of course, varies with where you sit. Defending
or attacking this figure was not possible in such a short spot, so if
we accept it, we compute the probability that you catch at least one
foul ball in say, n, games. We can compute this probability by first
finding the probability of its complement. The complementary event of catching at least one foul ball is
catching no foul balls. In one game our chance of not catching a foul
ball is 1-0.001=0.999. If our catching a foul ball is independent from
game to game, then our chance of not catching a foul in n games is
(0.999)

^{n}. Subtracting this from one, we get the probability of catching at least one foul ball in n games: 1- (0.999)^{n}. If we want this result to be at least 50-50 (that is, 0.50) we need to find the value of n so that: 0.50 < =1- (0.999)^{n}. You can do this by trial and error on a calculator or by using logarithms to solve for n. This will be the number of home games you must attend to increase your chances of catching at least one foul ball to at least 50-50. Now convert this to seasons of home games. There are 162 games in a season, but only 81 are home games. You should get an answer of 8 home seasons plus about half of a ninth season, hence choice B in the video.
This was fun to do.

## Monday, September 2, 2013

### Wear Pattern in "Bedrock"

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