Archive for category politics

Regions with aging populations are experiencing higher death rates!

If the USA moves to government-sponsored health care on the scale of Europe, death rates here (now 8.3 per thousand) are sure to increase to the trans-Atlantic level of 10.3 — that’s a fear which Economist Edward Lotterman rebuts in his newspaper column today.  As you educated readers might guess, the discrepancy in death rates can be easily explained by differing demographics: Due differing post-WWII dynamics, Europe’s population is older than ours, which can be seen in these animated population pyramids on Europe versus the United States developed by Professor Gerhard K. Heilig.

Specific statistics like this, when used indiscriminately by strongly-biased people, give statistics as a whole a bad name.  However, those who are not duly diligent in vetting inflammatory stats are just as much to blame as the originators misleading them.

“It is proven that the celebration of birthdays is healthy. Statistics show that those people who celebrate the most birthdays become the oldest.”  — Widely quoted as stemming from a PhD thesis by S. den Hartog (perhaps too good to be true!)

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USA health care system “Pareto-inefficient”?

Being a Certified Quality Engineer (CQE) I am well-versed in the Pareto Principle – a term coined by quality guru Joseph Juran for what’s commonly known as the 80-20 rule.  When I was the team leader for manufacturing improvement projects, I’d start by categorizing causes for failure and graphing them on an ordered bar chart — most to least, while keeping a running tally on the accumulation in terms of percent.  (See this primer on Pareto by the American Society of Quality.)  Typically the first 20 percent of causes created 80 percent of the failures – that’s where I first focused the firepower of my quality team.

Today I learned of another concept attributed to the great Italian economist*: Pareto inefficiency.  The Concise Encyclopedia of Economics explains that a “Pareto-optimal allocation of resources is achieved when it is not possible to make anyone better off without making someone else worse off.”  I found this detailing by The New School which is too much for me to completely digest, but my attention was caught by this heads up:

“An economy can be Pareto-optimal, yet still ‘perfectly disgusting’ by any ethical standards.”

 – Harvard Economics Professor Amartya Sen (1970)

So, while I am enticed by the idea that we can make most everyone (80 percent?) better off without making the others (20 percent?) worse off, I remain skeptical.  However, having seen what a focused quality improvement team can do with the aid of Pareto charts at a micro level, I remain hopeful that some big strides can be made at the macro level for health care nationwide.

*Vilfredo Pareto

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“Decisions taken by statistical professionals are final”

I’m just catching up on the Wall Street Journal issues that accumulated while I attended a statistical conference and then co-taught a workshop on Designed Experiments for Life Sciences.  A June 3rd article by WSJs “Numbers Guy” Carl Bialik caught my eye with a graphic showing that most UK citizens distrust official statistics.  This caused their government to create a Statistics Authority that will police other agencies on the numbers they release to the public.  Here some key points as reported at this UK government web site:

  • When preparing any publication containing statistics, including those drawn from administrative or management information, you must involve statistical professionals at the earliest opportunity
  • You must not use unpublished statistics without the advice of a statistical professional
  • You must not selectively quote favourable data from any unpublished dataset
  • Decisions taken by statistical professionals are final
  • So it seems that the number nerds will rule after all — just like they always dreamed when being belittled by the bullies who thought math and stats were simply a waste of time. Statisticians rule!

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    Political science (?) based on happenstance regression

    My daughter Carrie, a junior at University of Minnesota — majoring in political science, asked me to look over a paper she wrote last week for her quantitative-analysis class. Her assignment was to test “the theory that Christian religiosity, measured through church attendance, affected the outcome of the 2004 presidential election” (Bush over Kerry). Carrie considered many other variables that could logically have influenced voting decisions before settling on two alternative factors – per-capita income, and level of education.

    As I’d expected, her regression analysis (using the SPSS software) showed a positive correlation of “frequent church goers” voting for Bush (0.166 R2) and negative for “population with college degree or higher” (0.293). However, the highest correlation was seen with per-capita income, which surprised me by being negative – the more the voter earned, the more likely they were to NOT vote for Bush. I always thought that the Republicans were the party of the rich. But from this data one must conclude that they mainly appeal to poor, less-educated church-goers! (Please do not take the previous two ‘tongue-in-cheek’ statements seriously, I am only making a humorous point about how misleading statistics can be!)

    I don’t give too much credence to any of this – mainly due to my great skepticism of using statistics to dissect historical data and generate inferences on cause and effect relationships. However, it makes me curious as to the driving forces of today’s party politics in the USA. That’s about all I figure that regression of happenstance data really offers – some food for thought that may lead to more rigorous investigation.

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    In search of the non-obvious

    On Tuesday the United States Supreme Court will hear arguments on what should be considered obvious when older inventions are combined for a patent application. Lining up on the side of loosening standards are Microsoft, Intel and other companies that have sprung up more recently. Opposing them are companies like General Electric that hold strong patent positions. See detail on this case — KSR versus Telefex — at CNET news. All of you scientists and engineers working in the USA had better keep an eye out on this war in court. It may cause quite a shakeup in the aims of R&D.

    Meanwhile, at a more personal level, many of us will be looking for that perfect gift for the person who already owns everything. Obviously it must be something that is not obvious. For example, how about Smittens — specialty mittens that allow you to hold hands while walking or sitting? I saw this featured in one of humorist Dave Barry’s gift guides. His 2006 recommendations came out today in the Miami Herald column “What’s behind Santa’s Ho-Ho-Ho”. If I had season tickets to a team that supported tailgaters, I’d ask Santa for a Cruzin Cooler. How about two coolers for your favorite couple, one for him and the other for her, along with a set of Smittens for them to cruise hand-in-hand around the parking lot?

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    Surveys produce precisely inaccurate findings

    In New Brighton, Minnesota, my old home town, the city council paid $4,600 for a a survey that asked how many residents voted in the last election. It found that 47 percent of the 400 respondents said they “always” vote when, in fact, less that 18 percent showed up for the last election. Professor Sandford Weisberg, director of the University of Minnesota’s Statistical Consulting Service, wasn’t surprised by this. He says that “people always want to say what pleases people.” However, the pollster hired by New Brighton claims that the people he surveyed simply “misremembered” that they hadn’t voted. A recent article in New York Times opinion pages* provides much more alarming evidence of misleading surveys, for example, one by American Medical Association (AMA) that reported an alarming rate of binge drinking and unprotected sex among college women during spring break. The AMA survey, supposedly based on a random sample of 644 women, provided a margin of error of +/– 4 percent. However, according to the Times, the survey included only women who volunteered to answer questions — and only a quarter of them had actually ever taken a spring break trip! The article goes on to cite other cases of surveys that produced very misleading results, including one similar to the one done by New Brighton. Beware of what you read about what other people think, especially if it comes from a scientific survey.

    *Precisely False vs. Approximately Right: A Reader’s Guide to Polls, by Jack Rosenthal, August 27, 2006

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