Immigrants fared poorly compared to the native population differences between the native population and the migrant pupils' problem-solving skills were high in all the participating countries. In Finland, the main population, representing the students 'scores averaged 526 points, while second-generation immigrant students' backgrounds ¬ an average of 461 points and a first-generation 426 points. In Finland, migrant and native population, the difference between success was greater than in the participating countries on average.
Showing posts with label PISA. Show all posts
Showing posts with label PISA. Show all posts
April 2, 2014
Mandatory Finnish Content
Because Finland scores well on PISA tests, there has been much interest in that remote Northern land's rather laidback public education system. But that raises a problem: Finland hasn't been very diverse until recently despite having a huge border with a much poorer country (secret: land mines). So, many accounts of Finland's education system in America simply assert that immigrants do great in Finland. Only problem: not true. From a Google Translate version of a Finnish government account of the results of the latest PISA test, this one on "problem-solving:"
April 1, 2014
New PISA test on real world problem solving
The tireless PISA folks are back with the results of a test of math-related real world problem solving among 15 year olds in 44 upscale countries. (Check here for sample questions like how to find the quickest route on a map or how to adjust an air conditioner). The U.S. did not bad, scoring a little above the average for rich countries, but not as good as the Asians or the white countries with smart immigration policies (Canada, Australia, Finland).
| OECD average | 500 |
| Singapore | 562 |
| Korea | 561 |
| Japan | 552 |
| Macao-China | 540 |
| Hong Kong-China | 540 |
| Shanghai-China | 536 |
| Chinese Taipei | 534 |
| Canada | 526 |
| Australia | 523 |
| Finland | 523 |
| England (United Kingdom) | 517 |
| Estonia | 515 |
| France | 511 |
| Netherlands | 511 |
| Italy | 510 |
| Czech Republic | 509 |
| Germany | 509 |
| United States | 508 |
| Belgium | 508 |
| Austria | 506 |
| Norway | 503 |
| Ireland | 498 |
| Denmark | 497 |
| Portugal | 494 |
| Sweden | 491 |
| Russian Federation | 489 |
| Slovak Republic | 483 |
| Poland | 481 |
| Spain | 477 |
| Slovenia | 476 |
| Serbia | 473 |
| Croatia | 466 |
| Hungary | 459 |
| Turkey | 454 |
| Israel | 454 |
| Chile | 448 |
| Cyprus 1, 2 | 445 |
| Brazil | 428 |
| Malaysia | 422 |
| United Arab Emirates | 411 |
| Montenegro | 407 |
| Uruguay | 403 |
| Bulgaria | 402 |
| Colombia | 399 |
Shanghai came down to earth after its stratospheric scores on the last two PISAs. Poland was also down v. its PISA scores. Otherwise, there would appear to be a fairly high degree of correlation at the national level between the triennial PISA test of book smarts and the new PISA test of real world smarts, which is what the g Factor theory of intelligence would predict.
December 7, 2013
Eric Hanushek's $20 trillion idea
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| Click to enlarge |
This report uses recent economic modelling to relate cognitive skills – as measured by PISA and other international instruments – to economic growth. This relationship indicates that relatively small improvements in the skills of a nation’s labour force can have very large impacts on future well-being. Moreover, the gains, put in terms of current GDP, far outstrip today’s value of the short-run business-cycle management. This is not to say that efforts should not be directed at issues of economic recession, but it is to say that the long-run issues should not be neglected.
A modest goal of having all OECD countries boost their average PISA scores by 25 points over the next 20 years – which is less than the most rapidly improving education system in the OECD, Poland, achieved between 2000 and 2006 alone – implies an aggregate gain of OECD GDP of USD 115 trillion over the lifetime of the generation born in 2010 (as evaluated at the start of reform in terms of real present value of future improvements in GDP) (Figure 1).
A number of years ago, I suggested that the American Establishment drop its obsession with Closing the Gap -- in effect, boosting black and Hispanic scores by close to a standard deviation while not allowing whites and Asians to improve -- in favor of a fairer and far more feasible goal of improving all groups by an average of a half standard deviation. Hanushek looks at just boosting everybody by a quarter of a standard deviation on test scores (25 points on a PISA test or on a SAT test) and finds the net present value for the U.S. would be $20 trillion.
Bringing all countries up to the average performance of Finland, OECD’s best performing education system in PISA, would result in gains in the order of USD 260 trillion (Figure 4). The report also shows that it is the quality of learning outcomes, not the length of schooling, which makes the difference.
December 4, 2013
PISA Heat Map more of a PISA Cool Map
The nice people at OpenHeatMap.com provide a free tool for making a "heat map," like this one I made of average overall 2012 PISA scores. Click on the map to enlarge it.
PISA discovering that accuracy = boredom to the press
Three years ago, Andreas Schleicher and the other well-funded folks at PISA were media darlings. This year ... not so much. You can sense that the bloom is off the rose.
A big part of PISA's new PR problem is that the results were so similar from 2009 to 2012. Now, you might think that stability is a good sign that suggests that the PISA people aren't just pulling these numbers out of thin air. But accuracy is boring. The media likes change for the sake of change. Who's up? Who's down? A school test that's more or less a giant budget IQ test doesn't produce enough random changes to maintain media interest.
Decades ago when the news magazine US News & World Report was launching their college ranking system, there was much interest from year to year as they improved their methodology, frequently casting overlooked colleges toward the top. But, after awhile, USNWR got pretty good at measuring as much as could be conveniently measured ... and then what? Colleges, it turns out, don't change much from year to year, so the future looked a lot like the present. And without trends, we don't have news.
So, USNWR came up with the idea of changing some of the fairly arbitrary weights in its formula each year to generate a new #1 frequently. One year, for example, Caltech shot up to #1, which generated a lot of press coverage. But it was almost all just churn for the sake of churn. Caltech was pretty much the same place before, during, and after its sudden rise and fall.
But spectators like churn. In fact, one side effect of bad quantitative methodologies is that they generate phantom churn, which keeps customers interested. For instance, the marketing research company I worked for made two massive breakthroughs in the 1980s to dramatically more accurate methodologies in the consumer packaged goods sector. Before we put to use checkout scanner data, market research companies were reporting a lot of Kentucky windage. In contrast, we reported actual sales in vast detail. Clients were wildly excited ... for a few years. And then they got kind of bored.
You see, our competitors had previously reported all sorts of exciting stuff to clients: For example, back in the 1970s they'd say: of the two new commercials you are considering, our proprietary methodology demonstrates that Commercial A will increase sales by 30% while Commercial B will decrease sales by 20%.
Wow.
We'd report in the 1980s: In a one year test of identically matched panels of 5,000 households in Eau Claire and Pittsfield, neither new commercial A nor B was associated with a statistically significant increase in sales of Charmin versus the matched control group that saw the same old Mr. Whipple commercial you've been showing for five years. If you don't believe us, we'll send you all the data tapes and you can look for yourselves.
Ho-hum.
Ho-hum.
It was pretty amazing that we could turn the real world into a giant laboratory (and this was 30 years ago). But after a few years, all this accuracy and realism got boring.
It turned out that clients kind of liked it back in the bad old days when market research firms held a wet finger up to the breeze and from that divined that their client was a creative genius whose new ad would revolutionize the toilet paper business forever. (New ads and bigger budgets mostly work only if your ad has some actual message of value to the consumers to convey: e.g., "Crest now comes with Unobtanium, which the American Dental Association endorses for fighting Tooth Scuzz.")
These parallels between the consumer packaged goods industry in the 1980s and the educational reform industry in the 2010s are not really coincidental. Everybody says they want better tests, but what they really want is more congenial results. So, when they get better tests, they aren't as happy as they thought they'd be.
PISA: Which countries to trust the least
How can you be confident that local officials didn't pull any fast ones with their PISA results? Well, you can't, but you can get some sense of how much room there is to pull the wool over your eyes by looking at the response rate.
Large countries have to test at least 4,500 students, and the sample is supposed to be carefully designed to represent the entire country's 15-year-olds. But projected coverage usually turns out less than perfect. For example, countries can exclude students with disabilities. This sounds reasonable -- it's hard for a blind person to take a pencil and paper test. But, what about cognitive disabilities, such as not being very bright? From the federal government's website on PISA:
PISA 2012 is designed to be as inclusive as possible. The guidelines allowed schools to be excluded for approved reasons (for example, schools in remote regions, very small schools, or special education schools). Schools used the following international guidelines on student exclusions:
Students with functional disabilities. These were students with a moderate to severe permanent physical disability such that they cannot perform in the PISA testing environment.
Students with intellectual disabilities. These were students with a mental or emotional disability and who have been tested as cognitively delayed or who are considered in the professional opinion of qualified staff to be cognitively delayed such that they cannot perform in the PISA testing environment.
Students with insufficient language experience. These were students who meet the three criteria of not being native speakers in the assessment language, having limited proficiency in the assessment language, and having less than 1 year of instruction in the assessment language.
Overall estimated exclusions (including both school and student exclusions) were to be under 5 percent of the PISA target population.
Buried in a PISA appendix entitled Annex 2A are PISA figures for what percentage of the target populations of 15-year-olds didn't get tested. America didn't come close to getting 95% representation, and many Third World countries were far worse.
"Coverage Index 3: Coverage of 15-year-old population" shows what percentage of the cohort are represented if the test taking sample was projected to the whole country. I subtracted this percentage from 100% to come up with the % Missing index. For example, Costa Rica only managed to test half the people they were supposed to, and Albania only tested 55%. Vietnam, which made a splashy PISA debut with high scores, somehow couldn't find 44% of their 15-year-olds. At the other end, the dutiful Dutch managed to test slightly more students than were thought to be around.
| % Missing | |
| Costa Rica | 50% |
| Albania | 45% |
| Vietnam | 44% |
| Mexico | 37% |
| Colombia | 37% |
| Indonesia | 37% |
| Turkey | 32% |
| Brazil | 31% |
| Thailand | 28% |
| Peru | 28% |
| Uruguay | 27% |
| Liechtenstein | 25% |
| Bulgaria | 23% |
| Shanghai-China | 21% |
| Malaysia | 21% |
| Argentina | 20% |
| Kazakhstan | 19% |
| Macao-China | 19% |
| Hungary | 18% |
| United Arab Emirates | 17% |
| Canada | 17% |
| Chile | 17% |
| Hong Kong-China | 16% |
| Czech Republic | 15% |
| Serbia | 15% |
| Latvia | 15% |
| Lithuania | 14% |
| Jordan | 14% |
| Australia | 14% |
| Italy | 14% |
| Greece | 13% |
| New Zealand | 12% |
| Korea | 12% |
| Austria | 12% |
| Portugal | 12% |
| Spain | 12% |
| France | 12% |
| United States | 11% |
| Chinese Taipei | 11% |
| Poland | 11% |
| Luxembourg | 11% |
| Montenegro | 10% |
| Israel | 9% |
| Denmark | 9% |
| Japan | 9% |
| Ireland | 9% |
| Slovak Republic | 9% |
| Tunisia | 9% |
| Switzerland | 9% |
| Norway | 8% |
| Estonia | 8% |
| Russian Federation | 8% |
| Iceland | 7% |
| Sweden | 7% |
| United Kingdom | 7% |
| Slovenia | 6% |
| Qatar | 6% |
| Croatia | 6% |
| Germany | 5% |
| Singapore | 5% |
| Belgium | 5% |
| Finland | 4% |
| Romania | 4% |
| Cyprus | 3% |
| Netherlands | -1% |
In general, Third World countries were bad at getting good coverage, suggesting that the First World v. Third World gap is even larger than the test scores imply.
Top scorer Shanghai missed 21%, so we should take its flashy scores with a few grains of salt.
America was at 11% missing, down from 18% missing in 2009, which may account for the slight decline in U.S. scores?
Consistent high-flier Finland had only 4% missing, so they aren't cheating on this measure more than the competition is.
Top scorer Shanghai missed 21%, so we should take its flashy scores with a few grains of salt.
America was at 11% missing, down from 18% missing in 2009, which may account for the slight decline in U.S. scores?
Consistent high-flier Finland had only 4% missing, so they aren't cheating on this measure more than the competition is.
A major question is how random were the missing test-takers. If the missing were purely random, then no harm no foul. But of course, many of the missing are dropouts, or in special day classes, or in juvy hall, or whatever.
This may help excuse slightly Argentina's horrible scores. The Argentineans misplaced only 20% of their 15-year-olds compared to the 37% of Mexicans who went missing.
Swedes accuse PISA of fabricated data
Via Staffan's Personality Blog, here's an article from a Swedish (ahem, sore loser, ahem) newspaper accusing PISA of using fabricated data from Slovenia, Italy, and the United Arab Emirates. The charges don't involve students, but high school principals. The principals were supposed to fill in a 184 question survey for the Nosey Parkers at PISA, but there is evidence that dozens of principals just cut and pasted somebody else's answers, which wouldn't be hugely surprising with a survey that is 184 questions long.
A general problem with comparing results of countries in international tests are differing levels of motivation. It's remarkable how plausible the PISA results are in general considering how much this factor is likely to vary from place to place and time to time.
A general problem with comparing results of countries in international tests are differing levels of motivation. It's remarkable how plausible the PISA results are in general considering how much this factor is likely to vary from place to place and time to time.
The 5 most expensive words in the world: "We'll fix it in post"
Commenter Power Child notes:
"We'll fix it in post" are known to production guys as the five most expensive words in filmmaking.
"We'll fix it in post" is also the reasoning behind an awful lot of government spending on education, welfare, medicine, prisons, and many other Gaps caused by lack of care upfront in the production of residents of America.
PISA by state by race: Massachusetts, Connecticut, Florida
The PISA test was given to large samples sizes in three American states. From the federal National Center for Educational Statistics:
| PISA 2012 | |||||
| Race / Ethnicity | Mean | Math | Science | Reading | |
| Massachusetts | |||||
| White | 538 | 530 | 545 | 540 | |
| Black | 467 | 458 | 466 | 476 | |
| Hispanic | 460 | 446 | 460 | 475 | |
| Asian | 578 | 569 | 580 | 584 | |
| Multiracial | NA | NA | NA | NA | |
| Connecticut | |||||
| White | 542 | 534 | 547 | 546 | |
| Black | 434 | 421 | 433 | 447 | |
| Hispanic | 456 | 442 | 463 | 463 | |
| Asian | 548 | 534 | 553 | 558 | |
| Multiracial | 512 | 496 | 520 | 521 | |
| Florida | |||||
| White | 512 | 499 | 520 | 518 | |
| Black | 429 | 413 | 425 | 449 | |
| Hispanic | 474 | 458 | 475 | 489 | |
| Asian | NA | NA | NA | NA | |
| Multiracial | 486 | 467 | 500 | 492 | |
| White-Black Gaps | |||||
| Massachusetts | 72 | 72 | 79 | 64 | |
| Connecticut | 109 | 113 | 114 | 99 | |
| Florida | 83 | 86 | 95 | 69 | |
| White-Hispanic Gaps | |||||
| Massachusetts | 78 | 84 | 85 | 65 | |
| Connecticut | 86 | 92 | 84 | 83 | |
| Florida | 38 | 41 | 45 | 29 | |
The standard deviation is supposed to be 100, so you can just put a decimal place in front of those gap numbers to convert them into rough z scores.
We can see patterns here that shouldn't be unexpected. Massachusetts, home to the education-industrial complex since 1636, has smart whites. Connecticut, home to the hedge fund industry, has smart whites.
Florida, not so much. Still, this would be a good time for an old anecdote about how Florida isn't wall-to-wall Parrot Heads. I had a girlfriend in college who went to the public high school in Cocoa Beach, FL (the town that was the setting for the 1960s sit-com I Dream of Jeannie). She told me she scored 1580 on the SAT (M+V, old-style). I exclaimed:
We can see patterns here that shouldn't be unexpected. Massachusetts, home to the education-industrial complex since 1636, has smart whites. Connecticut, home to the hedge fund industry, has smart whites.
Florida, not so much. Still, this would be a good time for an old anecdote about how Florida isn't wall-to-wall Parrot Heads. I had a girlfriend in college who went to the public high school in Cocoa Beach, FL (the town that was the setting for the 1960s sit-com I Dream of Jeannie). She told me she scored 1580 on the SAT (M+V, old-style). I exclaimed:
"You must have had the highest score in your high school!"
"Oh, no, I was fourth-highest."
"Fourth? Who were the other three? The children of rocket scientists?" (In my defense, this was a relatively new witticism in 1979.)
"Yes."
Massachusetts has pretty smart blacks, going back to Phillis Wheatley and W.E. Du Bois. Connecticut and Florida, not so much.
Florida has pretty smart Hispanics, although the wealthy Cubans and other rich Latin Americans are getting diluted more and more.
Americans students have trouble with "higher cognitive demands"
From the "Country Note" for the United States from PISA:
Students in the United States have particular weaknesses in performing mathematics tasks with higher cognitive demands, such as taking real-world situations, translating them into mathematical terms, and interpreting mathematical aspects in real-world problems. An alignment study between the Common Core State Standards for Mathematics and PISA suggests that a successful implementation of the Common Core Standards would yield significant performance gains also in PISA.
The key phrase there is "a successful implementation."
How does PISA really work? "Fix it in Post"
How can PISA claim to fairly test in 65 countries in dozens of languages?
My vague hunch is that modern Item Response Theory testing, of which the PISA test's Rasch Model is an example, allows testers to say, much like movie directors of sloppy productions: "We'll fix it in Post."
You tell me that during the big, expensive action scene I just shot, the leading man's fly was open and in the distant background two homeless guys got into a highly distracting shoving match? And you want to know whether we should do another take, even though we'd have to pay overtime to 125 people?
"Eh, we'll fix it in Post."
Modern filmmakers have a lot of digital tricks up their sleeves for rescuing scenes, just as modern psychometricians have a lot of computing power available to rescue tests they've already given.
For example, how can the PISA people be sure ahead of time that their Portuguese translations are just as accurate as their Spanish translations?
Well, that's expensive to do and raises security problems. But, when they see the results come in, they can notice that, say, smart kids in both Brazil and Portugal who scored high overall, did no better on Question 11 than kids who don't score well on the other questions, which suggests the translation of Question 11 might be ambiguous. Oh, yeah, there are, now that we think about it, two legitimately right answers to Question 11 in the Portuguese translation. So we'll drop #11 from the scoring in those two countries. But, in the Spanish-speaking countries, this anomaly doesn't show up in the results, so maybe we'll count Question 11 for those countries.
This kind of post-hoc flexibility allows PISA to wring a lot out of their data. On the other hand, it's also a little scary.
Israel's PISA scores: Arab v. Hebrew-speakers
From Globes, an Israeli business publication:
The PISA exam shows substantial gaps between Hebrew and Arabic-speaking pupils. In the math exam, Hebrew speakers achieved a score of 489 points, while Arabic speakers achieved a score of 388 points. Arabic speakers scored 98 points less than Hebrew speakers in the science exam.
Graph of 2012 PISA scores for 65 countries/economies
This graph displays the mean of the Math, Science, and Reading test scores from the OECD's 2012 Programme for International Student Assessment. American scores are red, white countries are blue, East Asians countries are yellow, Muslim countries are green, and Latin American countries are brown.
So, Asian Americans outscored all large Asian countries (with the exception of three rich cities); white Americans outperformed most, but not all, traditionally white countries; and Latino Americans did better than all Latin American countries. African Americans almost certainly scored higher than any black majority country would have performed.
Bear in mind that many countries did not take part in PISA, such as India, which dropped out after a trial run in two states produced average scores below any seen on this chart. For a broader sampling of Third World scores, see the 2011 TIMSS Math and Science scores.
The reality is that there is not much difference in PISA or TIMSS scores within major racial blocs of countries. The Northeast Asians all tend to score well, the European and white Anglosphere countries tend to score fairly well, the Latin American countries tend to score fair to middling, and on down from there. The rank order of continents is very much like the rank order of racial/ethnic groups on NAEP or SAT or CST tests. Newcomers to the topic like Amanda Ripley, author of The Smartest Kids in the World, get excited about minor differences in PISA scores within continents, but those often are statistical noise.
So, Asian Americans outscored all large Asian countries (with the exception of three rich cities); white Americans outperformed most, but not all, traditionally white countries; and Latino Americans did better than all Latin American countries. African Americans almost certainly scored higher than any black majority country would have performed.
Bear in mind that many countries did not take part in PISA, such as India, which dropped out after a trial run in two states produced average scores below any seen on this chart. For a broader sampling of Third World scores, see the 2011 TIMSS Math and Science scores.
The reality is that there is not much difference in PISA or TIMSS scores within major racial blocs of countries. The Northeast Asians all tend to score well, the European and white Anglosphere countries tend to score fairly well, the Latin American countries tend to score fair to middling, and on down from there. The rank order of continents is very much like the rank order of racial/ethnic groups on NAEP or SAT or CST tests. Newcomers to the topic like Amanda Ripley, author of The Smartest Kids in the World, get excited about minor differences in PISA scores within continents, but those often are statistical noise.
December 3, 2013
Steve in Taki's: PISA, Piece by Piece
From my new column at Taki's Magazine:
PISA, Piece by Piece
by Steve Sailer
With the release of new PISA test scores for 65 countries’ 15-year-olds this week, it’s worth taking a look at TIME reporter Amanda Ripley’s latest book The Smartest Kids in the World: And How They Got that Way.
Ripley came up with the clever idea of following three American high schoolers as exchange students in Finland, South Korea, and Poland. She chose Finland and South Korea because they are perennial PISA powerhouses, while Poland has improved its ranking significantly in this century.
Her sample size of three American kids abroad is hardly foolproof, and yet it’s a start. Everybody has opinions on schooling, but few people have firsthand experience with different countries’ school systems because it’s immensely time-consuming to sit in on classrooms long enough that the teacher runs out of her dog-and-pony shows for visitors and finally gets down to normal business.
Having only recently become interested in the topic of education, Ripley is a true believer in PISA scores.
Should you be? In truth, nobody seems to really know how much to trust PISA and its ace salesman Andreas Schleicher. ... The sheer logistical challenge of what PISA attempts to do should raise common-sense questions about how perfectly 65 countries can be compared. Translation of tests, selection of representative samples, and prevention of local authorities putting their thumbs on the scale are challenges so daunting to get exactly equal around the world that most observers just seem to hope for the best and trust that Schleicher has somehow devised a globally level playing field.
Please read the whole thing there.
Mandatory Finnish Content: Finland still #1 in Europe
There has been much talk about how Finland plummeted from its traditional top spot in the PISA scores, but:
- Finland was always only tops in white countries. Some Northeast Asians would typically beat the Finns.
- Finland is still #1 in white countries if you weight Math (519 for Finland), Science (545), and Reading (524) equally, for an overall score of 529, ahead of runner-up Estonia (526). This go-round of PISA emphasized Math, on which Finland came in fifth among white countries behind Liechtenstein, Switzerland, Netherlands, and Estonia.
Overall, though, across all three subjects, Finland was still #1 in Europe and its diaspora.
In contrast, the Scandinavian countries did not excel in 2012, with overall means of 498 for Denmark, 496 for oil-rich Norway, and 482 for Sweden. Among members of the OECD, the rich countries' club, Sweden beat only Israel, Slovakia, Greece, Turkey, Chile, and Mexico. (Some of those countries that Sweden edged out are in the rich countries' club only for "courtesy" or "aspirational" reasons.)
Overall PISA rankings, including America by race
Here are today's 2012 PISA average scores ranked by the mean across the three subjects. Americans' scores by race are broken out to make the comparisons less misleading. In summary, each race in America appears to average a little better than their racial cousins overseas. (By the way, in the following list, the italicized names refer to non-OECD places):
| Country or "Economy" | Reading | Science | Math | Mean | |||
| OECD average | 496 | 501 | 494 | 497 | |||
| Shanghai-China | 570 | 580 | 613 | 587 | |||
| Singapore | 542 | 551 | 573 | 556 | |||
| Hong Kong-China | 545 | 555 | 561 | 554 | |||
| Asian Americans | 550 | 546 | 549 | 548 | |||
| Korea, Republic of | 536 | 538 | 554 | 542 | |||
| Japan | 538 | 547 | 536 | 540 | |||
| Chinese Taipei | 523 | 523 | 560 | 535 | |||
| Finland | 524 | 545 | 519 | 529 | |||
| Estonia | 516 | 541 | 521 | 526 | |||
| Liechtenstein | 516 | 525 | 535 | 525 | |||
| Massachusetts All Races | 527 | 527 | 514 | 523 | |||
| Macao-China | 509 | 521 | 538 | 523 | |||
| Canada | 523 | 525 | 518 | 522 | |||
| Poland | 518 | 526 | 518 | 521 | |||
| Netherlands | 511 | 522 | 523 | 519 | |||
| Switzerland | 509 | 515 | 531 | 518 | |||
| White Americans | 519 | 528 | 506 | 518 | |||
| Connecticut All Races | 521 | 521 | 506 | 516 | |||
| Vietnam | 508 | 528 | 511 | 516 | |||
| Ireland | 523 | 522 | 501 | 516 | |||
| Germany | 508 | 524 | 514 | 515 | |||
| Australia | 512 | 521 | 504 | 512 | |||
| Belgium | 509 | 505 | 515 | 510 | |||
| New Zealand | 512 | 516 | 500 | 509 | |||
| Multiracial Americans | 517 | 511 | 492 | 507 | |||
| United Kingdom | 499 | 514 | 494 | 502 | |||
| Austria | 490 | 506 | 506 | 500 | |||
| Czech Republic | 493 | 508 | 499 | 500 | |||
| France | 505 | 499 | 495 | 500 | |||
| Slovenia | 481 | 514 | 501 | 499 | |||
| Denmark | 496 | 498 | 500 | 498 | |||
| Norway | 504 | 495 | 489 | 496 | |||
| Latvia | 489 | 502 | 491 | 494 | |||
| United States | 498 | 497 | 481 | 492 | |||
| Luxembourg | 488 | 491 | 490 | 490 | |||
| Spain | 488 | 496 | 484 | 490 | |||
| Italy | 490 | 494 | 485 | 490 | |||
| Portugal | 488 | 489 | 487 | 488 | |||
| Hungary | 488 | 494 | 477 | 487 | |||
| Iceland | 483 | 478 | 493 | 484 | |||
| Lithuania | 477 | 496 | 479 | 484 | |||
| Croatia | 485 | 491 | 471 | 482 | |||
| Sweden | 483 | 485 | 478 | 482 | |||
| Florida All Races | 492 | 485 | 467 | 481 | |||
| Russian Federation | 475 | 486 | 482 | 481 | |||
| Israel | 486 | 470 | 466 | 474 | |||
| Slovak Republic | 463 | 471 | 482 | 472 | |||
| Greece | 477 | 467 | 453 | 466 | |||
| Hispanic Americans | 478 | 462 | 455 | 465 | |||
| Turkey | 475 | 463 | 448 | 462 | |||
| Serbia, Republic of | 446 | 445 | 449 | 447 | |||
| Cyprus | 449 | 438 | 440 | 442 | |||
| United Arab Emirates | 442 | 448 | 434 | 441 | |||
| Bulgaria | 436 | 446 | 439 | 440 | |||
| Romania | 438 | 439 | 445 | 440 | |||
| Thailand | 441 | 444 | 427 | 437 | |||
| Chile | 441 | 445 | 423 | 436 | |||
| African Americans | 443 | 439 | 421 | 434 | |||
| Costa Rica | 441 | 429 | 407 | 426 | |||
| Mexico | 424 | 415 | 413 | 417 | |||
| Kazakhstan | 393 | 425 | 432 | 416 | |||
| Montenegro, Republic of | 422 | 410 | 410 | 414 | |||
| Malaysia | 398 | 420 | 421 | 413 | |||
| Uruguay | 411 | 416 | 409 | 412 | |||
| Brazil | 410 | 405 | 391 | 402 | |||
| Jordan | 399 | 409 | 386 | 398 | |||
| Argentina | 396 | 406 | 388 | 397 | |||
| Tunisia | 404 | 398 | 388 | 397 | |||
| Albania | 394 | 397 | 394 | 395 | |||
| Colombia | 403 | 399 | 376 | 393 | |||
| Indonesia | 396 | 382 | 375 | 384 | |||
| Qatar | 388 | 384 | 376 | 383 | |||
| Peru | 384 | 373 | 368 | 375 |
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