Tsoo Tsoon to be a Tsunami

Andrew Gillen at the Texas Public Policy Foundation says “Two Tsunamis are About to Hit Higher Education,” when :..the Department of Education released post graduate earnings and debt data broken down by college program — which will have a revolutionary impact on higher education.”

A bit of poking around on the web gets you to the TPPF webpage College Earnings and Debt, which ranks hundreds of degree programs by median student debt and after-graduation income.  It’s a nice interactive database, where you can compare programs among multiple colleges, or for a single college.

GIllen touts this information (he calls it the Gainful Employment Equivalent) as a game-changer for selecting college degree programs.

For years we’ve asked students to make one of life’s most important decisions essentially blindfolded. We’ve told them a college degree is the surest path to success but have given them little guidance on where to go to college or what major to choose once they get there. As a result, too many students leave with a mountain of debt and a credential that isn’t worth much on the labor market. The new data will help equip students — and their parents — with the information necessary to avoid these costly mistakes in several ways.

…the data will help students avoid risky programs within generally non-risky fields or colleges. Of the universities in the top 5 of the US News and World report college rankings, Harvard and Yale both had one program fail, and Columbia has 10 programs that fail. Helping students avoid these financial bad apples will help all students by keeping the pressure on individual academic programs, not allowing them to coast on a college’s (or field’s) reputation.

GEE-UTSA
Best Value Degree Programs at my school, UTSA (OPEID 010115)

Hey, the data is impressive, but don’t expect revolutionary change in our established preschool-to-penury pipeline.  The institutional inertia and 20th Century received wisdom that A College Degree Equals Success will pooh-pooh the idea of value shopping for a college degree.

Methodologically, the database has some glaring deficiencies, some of which will be remedied over time, as more data becomes available*:

  • it’s only one year’s worth of data*
  • it’s based solely on students who received federal financial aid*
  • some degree programs have zero information*
  • the statistics presented (median debt and debt-to-earnings ratio) are presented without any error estimates, rendering the summaries a bit sketchy.  Hey TPPF hackers, can you spell b-o-o-t-s-t-r-a-p?

Still, this is great first effort, and I look forward to refinements in the GEE summaries.  But don’t expect a tsunami.

Tip from the Instapundit, where most commenters respond with variations of “Well, duh.”

 

Counting is DIFFICULT

Eleven million? or 22 million? A new Yale/MIT study estimates the illegal alien population in the US somewhere in the range of 16.5 to 29.1 million (for us statisticians, that’s 22.8 ± 6.3 million). That’s a margin of error larger than the entire population of Los Angeles (3.99 million).  Worse yet, this estimate suggests that the Census Bureau’s annual American Community Survey report of 11 million is a seriously low-ball estimate. The Center for Immigration Studies is in the low-ball camp, but their argumentum ab auctoritate seems a bit shrill, and unwilling to admit to the possibility of systematic bias in previous estimates.

QuantosMojados

Not that counting is as easy as it appears.  I regularly open my basic statistics classes with an audience-participation version of the classic Bouba-Kiki experiment, and collect response data by having two or more student volunteers count hands.  Invariably, the student counts are not all the same.  The confusion provides a “teaching moment” illustrating that the simplest measurement method is prone to variation.

Don’t believe me?  If you’re a Windows computer user, download the freebie version of Wildlife Counts, and see how well you can count a static population of animals in a short time.

WildlifeCountsTrainer

Caught in the Draft

In December of 1969, the Selective Service held a lottery to determine the order in which young men would be called up for the Draft.  My number was a low 53, and that set the course for much of my adult life.  Turns out, the odds were against me.

DraftLotteryNumbers

draft-rank-by-month

  • Want to run more analyses? This article from the Journal of Statistics Education shows the way.

 

News Flash! Men and Women are Different…

..despite the fact that some folks wish is wasn’t so

In fact, the National Institute of Health requires that sex be included as a variable in all studies:

My favorite line from the review: “The mammalian brain is clearly a highly sex-influenced organ.”  As anyone who’s observed young GIs or frat boys would know.  It takes a PhD to believe in something as patently absurd as neurosexism.

Tip from Maggie’s Farm, where it’s always a bit skeptical.

Update:  Looks like the SAT is owned and operated by neurosexists.  Like I tell my students, “You knew that, you just didn’t know you knew that.”

 

To every thing, there is a season

Most of us are aware of the seasonal cycle of influenza outbreaks, which for Americans peak in the winter. In a new paper, Micaela Martinez, PhD, a scientist at the Columbia University Mailman School of Public Health, makes a case that all infectious diseases have a seasonal element. The “Pearl” article appears in the journal PLOS Pathogens. [my emphasis]

We all knew this, we just didn’t know we knew this.  Some folks are recognized as geniuses for explicating the obvious.  I’m look at you, Micaela Martinez.

CalendarOfEpidemics

Tip from Austin Bay writing at the Instatpundit,  who, like the BlogFather himself, can make even the most boring stuff sound interesting.