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==Losing at the half, winning in the end==
Judging Statistics
 
The popular New York Times column [http://freakonomics.blogs.nytimes.com/2009/03/17/when-losing-leads-to-winning/ Freakonomics] had an interesting piece on basketball recently.  The academic article [http://qbox.wharton.upenn.edu/documents/mktg/research/Losing_and_Winning.pdf When Losing Leads to Winning] it quotes by Jonah Berger and Devin Pope of the University of Pennsylvania is even more interesting.  The following graph illustrates their main point:
From [http://www.nytimes.com/2009/03/28/us/28judges.html?_r=1&hp the ''New York Times] comes this triumph of statistics.  The graphic below summarizes why foul play was suspected in Luzerne County, PA on the part of two greedy judges who lacked a moral compass.  
 
   
 
<center>http://www.dartmouth.edu/~chance/forwiki/CN45-2.gif </center>


   
   
 
Discussion:
That is, based on about 6500 NCAA basketball games, although being behind at the half is usually more likely to produce a loss, a one-point deficit at the half has a (surprisingly) higher probability of a win (51.3%) than being tied at the half (50%). They postulate that losing can lead to winning and cite a concept of “loss aversion.”
   
 
1. Why is the graph so incriminating?  
Discussion
 
2. However, many statistics textbooks caution, "The data never speaks for itself."  What possible mitigating facts regarding variability are missing?
1. Why is the above graph symmetrical about zero (game tied at the half)?
 
3.  As interesting as the statistical data is, read the article itself as well as [http://www.nytimes.com/interactive/2009/03/28/us/20090328_JUDGES.html the audios of victims] to see the non-statistical evidence unearthed by the prosecution.  Which do you find more compelling?
2.   The following graph is not in the article itself but is courtesy of the authors:
 
   
   
This graph, unlike the previous one, is not symmetrical about zero.  However, regarding “When Losing Leads to Winning,” how is this graph similar to the previous one regarding the concept of “loss aversion”?  What new ingredient makes it different?
3. The following punch line is from the New York Times: “It’s an intriguing finding: being behind by a little yields the greatest possible effort. And while these researchers measure these effects on the basketball court, or on pounding keyboards [other investigations done by Berger and Pope in their article], their implications for the rest of our lives are even more intriguing. Want your workers to work harder? Tell them that they are running a close second in the race for promotion.”  Google Niccolò Machiavelli and see what he wrote on the subject of inspiring underlings to perform better.
Submitted by Paul Alper
Submitted by Paul Alper

Revision as of 17:16, 28 March 2009

Judging Statistics

From the New York Times comes this triumph of statistics. The graphic below summarizes why foul play was suspected in Luzerne County, PA on the part of two greedy judges who lacked a moral compass.


Discussion:

1. Why is the graph so incriminating?

2. However, many statistics textbooks caution, "The data never speaks for itself." What possible mitigating facts regarding variability are missing?

3. As interesting as the statistical data is, read the article itself as well as the audios of victims to see the non-statistical evidence unearthed by the prosecution. Which do you find more compelling?

Submitted by Paul Alper

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