Stats in the Wild

Form the Freakonomics blog: “The Value of Statistics“.

I like the last line of this post: “It goes to show that thinking up the right regression to run can be worth millions.”

Cheers.

Ever play Risk and notice the first person has a huge advantage? Apparently, Andrew Gelman has too, and he offers a simple solution to the problem here.

Cheers.

Here is a nice little post about the price and purity of cocaine over time. The second graph released by the Washington Office on Latin America shows a huge decline in the price of cocaine in the eighties and a much more gradual decline in price from the early nineties through 2008.

They conclude: “In a report released this week, WOLA points out that there has been a general downward trend in cocaine prices in recent decades, despite the occasional spikes, indicating that crackdowns on cocaine trafficking are not working.

I’m not an economist, but couldn’t this also be a result of less demand for cocaine? If anyone actually knows what they are talking about, I would love to hear from you.

Also as a note, the SITW blog officially does not endorse the use of cocaine. As Kurt Cobain once said, “Drugs are bad for you, They will fuck you up.” And you better believe we’re not going to censor that like the local Aberdeen authorities. Not on SITW.

Cheers.

I got into an argument with one of my friends who is in law school about lawyers salaries. So I searched around the internet, and I found this fascinating graph of 2008 starting lawyers salaries from this blog entry on elsblog.org .

The blog entry goes on to say:
“Of the 22,305 law school graduates in NALP’s sample (over half of all 2008 graduates), a remarkable 23% (5,130 ’08 grads) reported an entry-level salary of $160,000. In contrast, 42% of entry level lawyers reported salaries in the $40,000 to $65,000 range. Once again, the central tendencies are a poor guide to the distribution as a whole: whereas the mean salary is a $92,000, the median salary was $72,000. Further, the two modes ($50,000 and $160,000) are separated by $110,000.”

Some comments:
1.)They sample over 22,000 law school graduates, which they claim is over half of all graduates. I wonder, however, if there is any systematic bias in this sample (I have no evidence there is or is not). For instance, people making very low wages may choose not to respond. This could further inflate (or deflate, if the opposite was occuring) starting salary statistics.

2.) I’m sure if you ask law schools about job prospects after you graduate, they would be happy to site the average starting salary of $92,000. I’d also bet if you ask law students about how much they expect to make they would quote the $92,000 average starting salary. Judging by this graph though, I imagine there are a lot of jaded 1st year lawyers pulling in $60,000 a year, which is by no means a bad living except……..

3.) Debt. It would be interesting to see this same graph of 2008 first year salaries, but minus the loan payments. The standard repayment period according to this is 10 years. Accoridng to this the tuition at Harvard Law school in 2009 is $41,500.

Say you finance all of that and nothing else. You owe $124,500. At 5% over ten years you owe $1382.21 a month. At $160,000 you are making over $13,000/month. Not a problem at all. But if you’re making
$60,000 a month like a lot of first year lawyers, you are effectively only making $43.413.48=$60,000-$16,586.52 (salary-loan payments). I think that would be an interesting graph. Anyone have that data?

Cheers.

Here is an interesting excerpt from a review of the book The Lady Tasting Tea: How Statistics Revolutionized Science in the Twentieth Century: “Salsburg believes that the public is not fully aware of the degree to which recent developments in statistics impact the way we perceive the world. He correctly points out that the twentieth century saw the fading of a deterministic outlook and the rise of a statistical/probabilistic way of looking at the world. This ongoing revolution is not only in the physical sciences, it also touches the social sciences and even the humanities. Though profound, it is a quiet revolution that has been unnoticed by many.” –Marc H. Mehlman

SITW blog officially endorses the book The Lady Tasting Tea: How Statistics Revolutionized Science in the Twentieth Century by David Salsburg. A good review of the book can be found here.

Interesting fact: David Salsburg received the first Statistics Ph. D. granted by the University of Connecticut in 1966.

Cheers.

The New York Times printed an article today about how important statistics were in the real world which I mentioned in a previous blog post. One of the last paragraphs offers a great example of correlation versus causation which has now won the SITW Correlation of the Week! Congratulations 1940s public health experts.

“The rich lode of Web data, experts warn, has its perils. Its sheer volume can easily overwhelm statistical models. Statisticians also caution that strong correlations of data do not necessarily prove a cause-and-effect link.

For example, in the late 1940s, before there was a polio vaccine, public health experts in America noted that polio cases increased in step with the consumption of ice cream and soft drinks, according to David Alan Grier, a historian and statistician at George Washington University. Eliminating such treats was even recommended as part of an anti-polio diet. It turned out that polio outbreaks were most common in the hot months of summer, when people naturally ate more ice cream, showing only an association, Mr. Grier said.” – David Alan Grier, NY Times Article

Some notes: 1.) Whoops. 2.) If you’re name is David Alan Grier, and you’re not this David Alan Grier, go by David Grier. Just drop the Alan.

Cheers.