“statistics”
27 posts under this tag.
This time a fascinating little gem from the cover article, The Expert Mind, of this month’s Scientific American: The month you were born plays decisive importance into whether you’ll become a professional soccer player or not. That’s a fact.
A 1999 study of professional soccer players suggests that they owe their success more to training than to talent. In Germany, Brazil, Japan and Australia, the players were much more likely than average to have been born in the first quarter (Q1) after the cutoff date for youth soccer leagues.. Because these players were older than their teammates when they joined the leagues, they would have enjoyed advantages in size and strength, allowing them to handle the ball and score more often. Their success in early years would have motivated them to keep improving, thus explaining their disproportionate representation in the professional leagues.
NOTE: The cutoff dates were August 1 for Germany, Brazil and Australia, and April 1 for Japan.
I’m reminded of Steven Pinker’s wonderful, mocking account of how he became a scientist (which appears in John Brockman’s Curious Minds, a book I’ve praised lavishly already).
Don’t believe a word of what you read in this essay on the childhood influences that led me to become a scientist. Don’t believe a word of what you read in the other essays, either. One of the curses of being an experimental psychologist is the habit of scrutinizing one’s own mental processes. Recounting childhood influences is a mental process no less subject to quirks and errors than falling for the visual illusions on the back of a cereal box. Everything I know about the recollection of childhood influences makes me approach this assignment with misgivings..
In a classic 1977 review, the psychologists Richard Nisbett and Timothy Wilson argued that many of the causes of our choices never enter our consciousness. Here is a simple example. If you present people with an array of articles of clothing and ask them to pick one to keep, they tend to pick the rightmost one. But if you then ask them to list the reasons they chose that article, no one says, “Because it was the one on the right.” They cite only the features of the objects themselves. Not having served in experiments in which the same items were presented in different orders, people have no grounds for knowing that a dumb factor like left-to-right position could be a cause of their behavior. And that’s a major problem for memories of what influenced us: None of us has taken part in the experiments that would isolate the causes of our choices in life.
[Ultimately,] chance must play an enormous role in development. We might be shaped by whether an axon zigged or zagged as our brains jelled in the womb, whether we got the top bunk or the bottom bunk, whether we were dropped on our head, whether we inhaled a virus. Needless to say, few people cite factors like these among their childhood influences..
Steven Pinker, How we may Have Become What We Are
Finally, in the richest country of the world, dumb matter’sEE last stalwart has fallen. A new U.S. study commisioned by Oxygen found that, given the choice, women would opt for tech items rather than luxury items like jewelry or vacations.” (via Yahoo! News) More precisely, “3 of 4 women would prefer a new plasma TV to a diamond necklace” and “86 percent would prefer a new digital video camera to a pair of designer shoes.” It’s all downhill for dumb matter now (and all down the rabbit hole for us).
How’s that for jargony singularity reporting?
As I said on a previous post, I believe Spanish, my mother tongue, has a low status on the web. And as I laid there pondering the subjectivity of my assessment, I remembered Mihaly CsikszentmihalyiWP’s fascinating account of how (and why) he became a scientist (it appears in John Brockman’s excellent Curious MindsAM, a compilation of similar tales by top-notch scientists and a sure recommendation to anyone).
The particular anecdote that came to mind was when he and a friend quarrelled over whose neigborhood was the more communist (the matter was relevant because he was living in Italy and the country was then in political turmoil). Their brilliant analytic idea to try to settle the question was to count out the circulation of the left- and right-leaning newspapers in each of their neighborhoods’s newsstands. This of course sent them into all sorts of interesting statistical considerations, but it put them on the path of finding the subtle answers to their question, and it was certainly better than “the hocus-pocus most adults rely on to bolster their arguments”.
So I want to try to do something similar with my question—what is the linguistic vitality in the web of 14 languages?—and this post will be the beginning of my investigation. For reasons of practicality and personal bias, the 14 languages I’m going to settle to are: EnglishWP, GermanWP, FrenchWP, PolishWP, JapaneseWP, DutchWP, ItalianWP, SwedishWP, PortugueseWP, SpanishWP, FarsiWP, ChineseWP, EsperantoWP, and HindiWP.
I had never before ventured inside the Wikipedia Statistics provided by the Wikimedia Foundation itself but it’s a wonderfully impressive place. Particularly interesting are its charts regarding all the language Wikipedias. It’s graph galore in there: number of wikipedians, active wikipedians_ articles, new articles per day, database bytes, links, words—you name it, and it all dates back to its inception. Not for the faint of bandwidth.
The above is a map of world happiness—the redder, the happier—Adrian White, Analytic Social Psychologist, University of Leicester, made in a meta-study that aggregated the results of over a 100 independent studies and surveys on subjective wellbeing from around the world. The study itself isn’t yet available, but there’s an intereresting (though hideous) press release were you can quote your country’s rank (the US is #23, Denmark #1, Switzerland #2, Austria #3 (cheers to Alexis!), and Mexico #51).
As I said, the source itself isn’t yet available, but Eurekalert—a science news service of sorts—provides some quotes on White’s meta-study.
My favorite one—because it confirms my individualistic prejudices of course:
We were surprised to see countries in Asia scoring so low, with China 82nd, Japan 90th and India 125th. These are countries that are thought as having a strong sense of collective identity which other researchers have associated with well-being.
It was also interesting to find out that health was the most closely correlated variable to happiness (I would have expected wealth to have that place):
Further analysis showed that a nation’s level of happiness was most closely associated with health levels (correlation of .62), followed by wealth (.52), and then provision of education (.51).
But there are several quotes that hint at the study’s agenda—and it sends a chill through my spine:
There is increasing political interest in using measures of happiness as a national indicator in conjunction with measures of wealth. A recent BBC survey found that 81% of the population think the Government should focus on making us happier rather than wealthier.
If government has proved itself so egregiously lousy and so disturbingly meddling when it started working under the banner of improving our welfare through last century, I can only shudder when imagining what a brand new world awaits us when it pursues “our” happiness.
| Population |
| Germany | 82,422,299 |
| United States | 298,444,215 |
| China | 1,313,973,713 |
| Japan | 127,463,611 |
| France | 60,876,136 |
| Netherlands | 16,491,461 |
| Britain | 60,609,153 |
| Italy | 58,133,509 |
| According to the CIA Factbook |
I just thought it interesting.
Wow. Just wow. A pretty weird way to begin the day.
Even longevity. In the 18th century, every year, we added a few days to human life expectancy. In the 19th century, we added a few weeks, every year, to human life expectancy—so this is double exponential growth. We’re now adding about 150 days, every year, to human life expectancy,
and with the revolutions coming in genomics, perdiomics, therapeutic cloning, rational drug design, and the other biotechnology revolutions, within 10 years we’ll be adding more than a year, every year, to human life expectancy.
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