There is an interesting article in today's NY Times on executive
compensation and who get paid the most in academia:
http://www.nytimes.com/2009/02/23/education/23pay.html?_r=1&scp=1&sq=salaries%20university&st=cse
 
or
http://tinyurl.com/cgpest 
(check out the multimedia section)

Because colleges/universities are centers of learning, promoting
the development of valid knowedge, and serve as the storehouses
of the wisdom of the ages, it is only fitting that this person earned
the most in 2007:

|Pete Carroll, the head football coach at U.S.C., received $4,415,714 
|in 2007, about four times as much as the president of the university, 
|Steven B. Sample.

They do love their footbal at the Uni of Southern Cal.  The runner-up
may be somewhat more acceptable:

|Dr. David N. Silvers, the Columbia dermatologist, received $4,332,759, 
|compared with $1,411,894 for Lee C. Bollinger, the president of the 
|university. And he was not the only Columbia employee who out-earned 
|the president: Dr. Jeffrey W. Moses, a professor of medicine, received 
|$2,532,713.

The info for the salaries comes from the Chronicle of Higher Education;
see:
http://chronicle.com/indepth/compensation/ 
(access to some info may require either a subscription or additional fees).

Hmmm, if these are the jobs with the greatest positive reinforcements,
shouldn't we all be motivated to get them?

-Mike Palij
New York University
[email protected]

P.S. On a somewhat unrelated note, Nate Silver, famed for baseball
statistics and predicting the recent presidential election, also predicted
the big winners for the Oscars ("New York Magazine" had an article
on it last week).  Using logistic regression, Nate provided probabilities
for the different candidates for the top six awards.  Result?  He correctly
predicted 4 of 6 winner or a .66667 hit rate (I believe someone claimed
this was as accurate as having a chimpanzee throw bananas at pictures
of the candidates as a method of choosing the winner).  What does this 
say about the use of regression models for making predictions?  How
would using the "recognition heuristic" produced different results? I mean,
how many people have really seen "Slumdog Millionaire"?  According
to www.boxofficemojo.com "The Curious Case of Benjamin Button"
drew twice as much in income and "The Dark Knight" has broken the
$billion mark worldwide ($=proxies for number of people who have
seen the films).  Yes, I know, it depends upon the members of the
Academy of Motion Picture Arts and Sciences, but still.





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