Average IQ
by country.
Every ranking you have seen traces back to one dataset. Here it is in full — mapped, searchable and sorted — together with the part almost nobody publishes: which of these numbers are measurements, which are guesses, and why a national average tells you nothing at all about you.
What the country IQ table actually says
The short version, before the detail. Every figure below is taken from the same published dataset and can be checked against the full table further down this page.
Key findings
- Japan has the highest figure in the dataset at 107.01, ahead of Taiwan (106.47) and Singapore (105.89).
- The lowest listed figure is Nepal at 42.99 — a value the dataset’s own author later disowned, and one we would not republish without that warning.
- 13 countries sit at or above 100 — but two of those thirteen, including the sixth-placed entry, have never been given an IQ test at all.
- 53 of the 201 entries (26%) have no test data of any kind. Their score is an average of whichever neighbours do.
- Sample sizes behind the measured countries run from 19 people (Angola) to 62,649 (United States). We publish the sample size for every one.
- The unweighted mean of all 201 entries is 81.90; weighted by population the dataset’s own total is 86.05.
Average IQ by country, mapped
Darker blue is a higher published figure; orange is lower. Grey means the dataset has nothing for that territory at all. Hover or tap any country for its score and rank.
Published national IQ estimates, 201 countries
Lynn & Becker, The Intelligence of Nations (2019) — NIQ dataset V1.3.2, QNW+SAS+GEO column
Small island states and micro-states are drawn as dots so they stay visible at this scale. Countries shown in grey — including Greenland and Western Sahara — have no entry in the dataset.
See every country in the table →The map shows countries. It cannot show you.
Individual scores inside any country span roughly 70 to 130. The only number that describes you is your own — and it takes about twenty minutes to get it.
Countries with the highest average IQ
The leading group has barely changed across every version of this dataset since 2002: a tight cluster of East Asian economies, followed by northern and central Europe.
Japan
107.01Average IQTaiwan
106.47Average IQSingapore
105.89Average IQThe top 25, ranked
Three things are worth noticing about this list before drawing any conclusion from it.
The margins are tiny. First place and tenth place are separated by under six points — less than half a standard deviation, and well inside the measurement error of most IQ tests. Treating a ranking built on those margins as a league table of national ability is not something the data supports.
The leaders share circumstances, not ancestry. The countries at the top have long compulsory schooling, near-universal literacy, low childhood disease burden and a culture in which formal testing is routine from an early age. Those are exactly the conditions known to raise measured scores.
The same countries lead PISA. Singapore, Japan, South Korea, Taiwan, Hong Kong and Macau occupy the top of the OECD's international student assessments as well. Two different instruments pointing the same way tells you the schooling effect is real; it does not tell you the cause is innate.
Average IQ by country: all 201
Search for a country, filter by region, or sort any column. Values are read directly from the published dataset without alteration — including the ones we think are wrong, which are discussed below. The Sample column is the part every other ranking leaves out: est. means no test data of any kind, and sch. means school tests rather than an IQ study.
| Rank▲ | Country▲ | Average IQ▲ | Region▲ | Sample▲ |
|---|---|---|---|---|
| 1 | 107.01 | East Asia | 3,207 in 6 studies | |
| 2 | 106.47 | East Asia | 10,008 in 7 studies | |
| 3 | 105.89 | Southeast Asia | 1,593 in 5 studies | |
| 4 | 105.37 | East Asia | 22,021 in 8 studies | |
| 5 | 104.10 | East Asia | 51,500 in 6 studies | |
| 6 | 103.76 | East Asia | no data | |
| 7 | 102.35 | East Asia | 3,586 in 4 studies | |
| 8 | 101.60 | Europe | 13,824 in 2 studies | |
| 9 | 101.20 | Europe | 1,536 in 3 studies | |
| 10 | 101.07 | Europe | school tests | |
| 11 | 100.74 | Europe | 8,445 in 12 studies | |
| 12 | 100.74 | Europe | 10,581 in 11 studies | |
| 13 | 100.72 | Europe | 6,688 in 3 studies | |
| 14 | 99.87 | Europe | school tests | |
| 15 | 99.82 | East Asia | school tests | |
| 16 | 99.75 | Southeast Asia | 3,181 in 3 studies | |
| 17 | 99.52 | North America | 4,229 in 10 studies | |
| 18 | 99.24 | Oceania | 5,962 in 6 studies | |
| 19 | 99.24 | Europe | 7,848 in 2 studies | |
| 20 | 99.24 | Europe | 1,636 in 5 studies | |
| 21 | 99.18 | Europe | 6,960 in 6 studies | |
| 22 | 98.89 | North America | no data | |
| 23 | 98.60 | Europe | 8,569 in 7 studies | |
| 24 | 98.57 | Oceania | 5,949 in 5 studies | |
| 25 | 98.38 | Europe | 390 in 4 studies | |
| 26 | 98.26 | Europe | 550 in 2 studies | |
| 27 | 97.83 | Europe | 750 in 2 studies | |
| 28 | 97.49 | Europe | 1,112 in 3 studies | |
| 29 | 97.43 | North America | 62,649 in 58 studies | |
| 30 | 97.13 | Europe | 369 in 3 studies | |
| 31 | 97.00 | Europe | 1,241 in 2 studies | |
| 32 | 96.69 | Europe | 4,676 in 5 studies | |
| 33 | 96.35 | Europe | 8,864 in 9 studies | |
| 34 | 96.32 | Europe | 833 in 1 study | |
| 35 | 96.29 | Europe | 1,290 in 3 studies | |
| 36 | 95.89 | Europe | 1,779 in 3 studies | |
| 37 | 95.75 | Europe | 1,003 in 3 studies | |
| 38 | 95.20 | Europe | no data | |
| 39 | 95.13 | Europe | 466 in 3 studies | |
| 40 | 94.92 | Europe | 363 in 1 study | |
| 41 | 94.79 | Europe | 146 in 1 study | |
| 42 | 94.23 | Europe | 5,717 in 5 studies | |
| 43 | 93.92 | Oceania | no data | |
| 44 | 93.92 | Oceania | no data | |
| 45 | 93.90 | Europe | 4,299 in 7 studies | |
| 46 | 93.48 | North America | 618 in 4 studies | |
| 47 | 93.39 | Middle East | 3,513 in 2 studies | |
| 48 | 92.87 | Europe | 1,989 in 3 studies | |
| 49 | 92.43 | Middle East | 3,705 in 6 studies | |
| 50 | 91.60 | Latin America | 117 in 2 studies | |
| 51 | 91.27 | Europe | 172 in 3 studies | |
| 52 | 91.20 | Southeast Asia | no data | |
| 53 | 91.03 | East Asia | 708 in 1 study | |
| 54 | 90.99 | Europe | 1,671 in 2 studies | |
| 55 | 90.77 | Europe | 1,584 in 3 studies | |
| 56 | 90.29 | Latin America | no data | |
| 57 | 90.07 | Europe | 132 in 1 study | |
| 58 | 89.98 | Europe | school tests | |
| 59 | 89.60 | Europe | 4,877 in 12 studies | |
| 60 | 89.53 | Southeast Asia | 917 in 3 studies | |
| 61 | 89.28 | Middle East | 2,976 in 3 studies | |
| 62 | 89.01 | Central Asia | 51 in 1 study | |
| 63 | 88.92 | Southeast Asia | 15,323 in 17 studies | |
| 64 | 88.89 | Central Asia | 617 in 3 studies | |
| 65 | 88.82 | Middle East | school tests | |
| 66 | 88.54 | Europe | 505 in 2 studies | |
| 67 | 88.34 | Latin America | 153 in 2 studies | |
| 68 | 87.94 | South Asia | no data | |
| 69 | 87.89 | Latin America | 2,393 in 5 studies | |
| 70 | 87.73 | Latin America | 1,590 in 4 studies | |
| 71 | 87.71 | Central Asia | 674 in 1 study | |
| 72 | 87.59 | Latin America | school tests | |
| 73 | 87.58 | Southeast Asia | no data | |
| 74 | 87.58 | Southeast Asia | 237 in 1 study | |
| 75 | 86.99 | Latin America | 723 in 2 studies | |
| 76 | 86.88 | Europe | 2,801 in 3 studies | |
| 77 | 86.80 | Middle East | 2,396 in 1 study | |
| 78 | 86.63 | Latin America | 6,110 in 5 studies | |
| 79 | 86.62 | South Asia | 326 in 3 studies | |
| 80 | 86.56 | Sub-Saharan Africa | 837 in 1 study | |
| 81 | 85.78 | Europe | school tests | |
| 82 | 85.63 | Latin America | school tests | |
| 83 | 85.49 | Central Asia | no data | |
| 84 | 84.81 | Middle East | school tests | |
| 85 | 84.50 | Middle East | school tests | |
| 86 | 84.29 | Latin America | no data | |
| 87 | 84.04 | Latin America | no data | |
| 88 | 83.96 | Oceania | no data | |
| 89 | 83.96 | Oceania | no data | |
| 90 | 83.96 | Oceania | no data | |
| 91 | 83.96 | Oceania | 407 in 1 study | |
| 92 | 83.96 | Oceania | no data | |
| 93 | 83.96 | Oceania | no data | |
| 94 | 83.96 | Oceania | no data | |
| 95 | 83.96 | Oceania | no data | |
| 96 | 83.90 | Latin America | 2,040 in 3 studies | |
| 97 | 83.87 | Latin America | 187 in 2 studies | |
| 98 | 83.60 | Middle East | 1,018 in 1 study | |
| 99 | 83.38 | Latin America | 7,645 in 23 studies | |
| 100 | 83.23 | Latin America | no data | |
| 101 | 83.13 | Latin America | 790 in 3 studies | |
| 102 | 82.99 | Latin America | 201 in 3 studies | |
| 103 | 82.24 | Latin America | no data | |
| 104 | 82.12 | South Asia | no data | |
| 105 | 82.05 | Latin America | 34 in 1 study | |
| 106 | 82.05 | Middle East | 5,159 in 1 study | |
| 107 | 81.99 | Latin America | 9,606 in 22 studies | |
| 108 | 81.91 | Europe | school tests | |
| 109 | 81.75 | Europe | school tests | |
| 110 | 81.70 | Middle East | 200 in 2 studies | |
| 111 | 81.64 | Southeast Asia | 3,145 in 3 studies | |
| 112 | 81.44 | Latin America | 2,702 in 9 studies | |
| 113 | 81.38 | Oceania | no data | |
| 114 | 80.99 | Southeast Asia | 142 in 4 studies | |
| 115 | 80.92 | North Africa | 7,000 in 9 studies | |
| 116 | 80.78 | Middle East | 1,135 in 1 study | |
| 117 | 80.70 | Middle East | 3,904 in 4 studies | |
| 118 | 80.54 | South Asia | no data | |
| 119 | 80.01 | Middle East | 6,517 in 3 studies | |
| 120 | 80.01 | Latin America | 96 in 1 study | |
| 121 | 80.00 | South Asia | 6,183 in 8 studies | |
| 122 | 79.34 | Latin America | no data | |
| 123 | 79.22 | North Africa | school tests | |
| 124 | 79.09 | Central Asia | 327 in 1 study | |
| 125 | 79.00 | Latin America | school tests | |
| 126 | 78.76 | Sub-Saharan Africa | 643 in 1 study | |
| 127 | 78.70 | Middle East | 14,627 in 6 studies | |
| 128 | 78.64 | Middle East | 15,346 in 4 studies | |
| 129 | 78.53 | Southeast Asia | 2,327 in 18 studies | |
| 130 | 78.53 | Oceania | no data | |
| 131 | 78.53 | Southeast Asia | no data | |
| 132 | 78.26 | Latin America | 126 in 4 studies | |
| 133 | 77.91 | Sub-Saharan Africa | no data | |
| 134 | 77.91 | North Africa | 41,001 in 18 studies | |
| 135 | 77.69 | Middle East | 5,876 in 5 studies | |
| 136 | 77.40 | Sub-Saharan Africa | no data | |
| 137 | 77.07 | Sub-Saharan Africa | no data | |
| 138 | 76.79 | Sub-Saharan Africa | no data | |
| 139 | 76.69 | Latin America | no data | |
| 140 | 76.53 | Latin America | 156 in 3 studies | |
| 141 | 76.42 | Sub-Saharan Africa | 2,759 in 3 studies | |
| 142 | 76.36 | Middle East | 11,633 in 8 studies | |
| 143 | 76.32 | North Africa | 23,147 in 9 studies | |
| 144 | 76.24 | South Asia | 20,299 in 20 studies | |
| 145 | 76.00 | North Africa | school tests | |
| 146 | 75.20 | Sub-Saharan Africa | 3,528 in 8 studies | |
| 147 | 75.10 | Sub-Saharan Africa | 19 in 1 study | |
| 148 | 75.08 | Latin America | 1,256 in 16 studies | |
| 149 | 74.95 | Sub-Saharan Africa | 4,070 in 5 studies | |
| 150 | 74.41 | Middle East | 6,012 in 6 studies | |
| 151 | 74.33 | South Asia | 9,043 in 5 studies | |
| 152 | 74.01 | Sub-Saharan Africa | 1,842 in 1 study | |
| 153 | 73.80 | Sub-Saharan Africa | 4,635 in 1 study | |
| 154 | 73.68 | Latin America | no data | |
| 155 | 72.50 | Sub-Saharan Africa | no data | |
| 156 | 72.09 | Sub-Saharan Africa | no data | |
| 157 | 70.85 | Sub-Saharan Africa | no data | |
| 158 | 70.48 | Latin America | no data | |
| 159 | 70.48 | Latin America | no data | |
| 160 | 70.36 | Sub-Saharan Africa | 4,054 in 1 study | |
| 161 | 69.95 | Sub-Saharan Africa | no data | |
| 162 | 69.70 | Sub-Saharan Africa | 268 in 1 study | |
| 163 | 69.63 | Latin America | school tests | |
| 164 | 69.45 | Sub-Saharan Africa | 140 in 1 study | |
| 165 | 68.87 | Sub-Saharan Africa | no data | |
| 166 | 68.87 | Sub-Saharan Africa | 6,704 in 15 studies | |
| 167 | 68.87 | Sub-Saharan Africa | no data | |
| 168 | 68.77 | Sub-Saharan Africa | 764 in 4 studies | |
| 169 | 68.74 | Sub-Saharan Africa | no data | |
| 170 | 68.43 | Sub-Saharan Africa | no data | |
| 171 | 68.42 | Sub-Saharan Africa | 707 in 6 studies | |
| 172 | 67.80 | Sub-Saharan Africa | no data | |
| 173 | 67.80 | Sub-Saharan Africa | 13,372 in 10 studies | |
| 174 | 67.67 | Sub-Saharan Africa | 2,440 in 1 study | |
| 175 | 67.03 | North Africa | 2,018 in 7 studies | |
| 176 | 66.19 | Sub-Saharan Africa | 103 in 1 study | |
| 177 | 66.03 | Latin America | 725 in 2 studies | |
| 178 | 65.23 | Sub-Saharan Africa | no data | |
| 179 | 64.92 | Sub-Saharan Africa | 549 in 8 studies | |
| 180 | 63.47 | Sub-Saharan Africa | no data | |
| 181 | 63.42 | Latin America | 174 in 1 study | |
| 182 | 62.97 | Sub-Saharan Africa | 88 in 1 study | |
| 183 | 62.97 | Sub-Saharan Africa | no data | |
| 184 | 62.86 | Middle East | 2,904 in 2 studies | |
| 185 | 62.55 | Latin America | school tests | |
| 186 | 62.55 | Sub-Saharan Africa | no data | |
| 187 | 62.16 | Latin America | school tests | |
| 188 | 59.76 | Sub-Saharan Africa | 206 in 1 study | |
| 189 | 59.76 | Sub-Saharan Africa | no data | |
| 190 | 58.61 | Sub-Saharan Africa | 4,363 in 5 studies | |
| 191 | 58.16 | Sub-Saharan Africa | no data | |
| 192 | 58.16 | Sub-Saharan Africa | 4,515 in 5 studies | |
| 193 | 53.48 | Sub-Saharan Africa | no data | |
| 194 | 52.69 | Latin America | 2,062 in 3 studies | |
| 195 | 52.14 | Sub-Saharan Africa | 2,770 in 1 study | |
| 196 | 51.54 | Sub-Saharan Africa | no data | |
| 197 | 49.78 | Sub-Saharan Africa | 2,591 in 6 studies | |
| 198 | 47.72 | Latin America | 5,385 in 7 studies | |
| 199 | 45.07 | Sub-Saharan Africa | no data | |
| 200 | 45.07 | Sub-Saharan Africa | 119 in 2 studies | |
| 201 | 42.99 | South Asia | 2,242 in 9 studies |
Found your country? Now find your number.
A national average is one figure standing in for millions of people. Your percentile against the full distribution is the measurement that actually applies to you.
The lowest figures — and what they measure
This is the part of the dataset that has drawn the heaviest criticism, and the part we would urge you to read most sceptically. We publish it because omitting it would be dishonest — not because we think these numbers mean what they appear to mean.
Read the bottom of this table with real caution
A national average below 60 would imply that most of a country's population meets the clinical threshold for intellectual disability. That is not what anyone observes in those countries, and it is not a conclusion the underlying studies can support. What such a figure usually reflects is a small, unrepresentative sample — often rural children, often tested in a second language, often on a test normed decades earlier on a different population, and often with no experience of formal testing at all.
Nepal’s listed value is the clearest example. Becker later published a corrigendum explaining that the Nepal, Sierra Leone, Guatemala and Gambia figures were produced by scoring errors, and the next revision of the dataset introduced a floor of 60 so that no sample could be reported below it. The version the whole internet still quotes — the one reproduced here — is the version from before that fix. We publish it because it is what circulates, and we flag it because it should not.
Average IQ by region
Each figure below is the unweighted mean of the countries listed in that region — a simple average of national values, not a population-weighted one.
East Asia
102.5The highest-scoring region in the dataset, and the one with the longest school years and the strongest test-taking culture.
Europe
95.0Forty-one countries inside a twenty-point band, with the spread tracking east-west differences in schooling and income.
North America
97.3Only four entries: Canada, Greenland, the United States and Bermuda. Canada and the US are two points apart, and the US figure rests on the largest sample in the whole dataset.
Oceania
86.9Australia and New Zealand score near 99; every Pacific island state carries one shared estimated value, not a measurement.
Southeast Asia
88.2A 27-point internal spread: Singapore leads the world, and Timor-Leste and Indonesia share a value 27 points below it.
Central Asia
86.0Five post-Soviet republics with inherited Soviet-era schooling systems and comparatively few modern samples.
Middle East
82.0Gulf states with high income score no higher than middle-income neighbours, which is itself evidence against a simple wealth story.
Latin America
78.2Thirty-eight countries spanning 44 points, from Barbados to Guatemala. Scores track years of schooling far more closely than they track GDP.
North Africa
76.2Six countries in the high 70s, with literacy and school-completion rates that lag the Mediterranean north.
South Asia
76.3Sample quality is the dominant issue here: several values rest on small, unrepresentative or decades-old studies.
Sub-Saharan Africa
66.9The most contested figures in the dataset. Wicherts and colleagues re-analysed these samples and reached materially different numbers.
Where these numbers actually come from
Almost every "average IQ by country" page on the internet — including the ones that rank above this one — is republishing the same single dataset. It is worth knowing what that dataset is.
The source is Richard Lynn and David Becker’s The Intelligence of Nations (2019), published by the Ulster Institute for Social Research, and the NIQ dataset released alongside it. The figures on this page are the QNW+SAS+GEO column of dataset version 1.3.2, read directly from Becker’s published workbook rather than from a secondary copy. It pools 669 studies covering 617,581 people and converts each onto a common scale anchored to a British mean of 100.
A note on where our numbers came from
Most “average IQ by country” pages copy one another. We checked, and the widely circulated list is wrong in 22 places — it puts Japan at 106.48 rather than 107.01, North Korea at 98.82 rather than 103.76 and Djibouti at 68.41 rather than 52.14, and it drops two entries altogether. Every figure here was read out of the original workbook instead, which is also how we can tell you which values are measurements and which are not.
A quarter of the table was never tested
Of the 201 entries, only 130 rest on actual IQ studies. Another 18 are derived from school-assessment scores rather than an IQ test. The remaining 53 — 26% of the table — have no test data of any kind; their figure is an average of the neighbouring countries that do.
This is not a footnote. North Korea ranks sixth in the world on this table, at 103.76, and there is no IQ study of North Korea in the dataset at all — the number is inferred from its neighbours. Liechtenstein, tenth at 101.07, has no IQ study either. Two of the thirteen countries scoring above 100 got there without anyone being tested.
You can see the mechanism in the table above without taking our word for it. Search for Fiji: it sits on 83.96, and so do the Solomon Islands, Samoa, Kiribati, Micronesia, Tonga, the Marshall Islands and the Cook Islands — identical to two decimal places. That is not eight findings. It is one estimate printed eight times.
Where that estimating step can be checked against real school testing, it does not work: for the countries whose value is purely geographic guesswork, the imputed figure correlates r = −0.376 with independently derived achievement scores — a negative relationship.
The samples were never designed to represent nations
A nationally representative cognitive survey is expensive, and very few countries have ever run one. What exists instead is a patchwork: school classes, army recruits, university volunteers, clinical comparison groups. The United States entry pools 62,649 people across 58 studies. Angola’s rests on 19 people in a single study; the Dominican Republic’s on 34; Uzbekistan’s on 51; Namibia’s on 103. Every one of those figures is printed to two decimal places, exactly like the American one. That is why we show the sample size beside every country.
The studies span seventy years, and scores moved over that time
Measured IQ rose substantially across the twentieth century — the Flynn effect. A study run in 1975 and a study run in 2015 are not on the same footing unless that drift is corrected for, and countries are not all represented by studies from the same era. Some of the gaps in this table are gaps in time as much as gaps in ability.
Why different websites give your country a different score
Because they are quoting different things. Some sites use the quality-weighted column of the 2019 dataset (the one on this page); others use the unweighted column, the older 2012 revision, or the 2002 Lynn & Vanhanen figures. A few publish averages from their own self-selected online visitors, which is a different measurement entirely and usually runs much higher. If two pages disagree about your country by ten points, the disagreement is almost always about which dataset — not about your country.
How reliable is national IQ data?
Short answer: reliable enough to be interesting, nowhere near reliable enough to rank populations by intelligence. Here is the case against it, made properly rather than waved away.
Half the evidence was left out — and the half that was kept scored lower
This is the single most damaging finding against the dataset. When Wicherts, Dolan and van der Maas systematically reviewed the published IQ literature for sub-Saharan Africa, they found that the 11 samples Lynn had used averaged 67.4 (N = 2,056) — while the 27 comparable samples he had not used averaged 80.4 (N = 7,759). Same region, same era, same kinds of test. The difference was which studies made it into the pool.
Wicherts, Dolan & van der Maas (2010), IntelligenceAnd the only thing that predicted exclusion was the score itself
Following up across more than a hundred samples covering over 37,000 people, the same team examined the compilers’ judgements about which African samples were “unrepresentative”. Those judgements bore no relation to objective criteria such as stratified random sampling, or to what the original authors said about their own samples. What they tracked was the sample’s IQ. Low samples were kept; high ones were more likely to be judged unrepresentative.
Wicherts, Dolan, Carlson & van der Maas (2010)By the compilers’ own coding, only a third of the samples are national
Sear’s audit — a preprint, not yet peer reviewed, but one whose figures we checked against the dataset ourselves — covers all 683 samples. Just 223 of them, 32.7%, are coded ‘national’ by Lynn and Becker themselves. The rest are regional (16.5%), urban (29.6%), rural (10.2%), or drawn from refugees and migrants tested outside their country of birth (1.8%). 37% of samples cover fewer than 1,000 people, and 30% of countries rest on a single sample.
Sear (2022)There is no stated method, so nobody can replicate or audit it
The dataset publishes no search strategy and no inclusion or exclusion protocol. The full methodological description is that studies were “collected, selected according to suitability, corrected as necessary, and averaged”. The consequences show: a malaria sub-sample was excluded in Angola but an equivalent one included in Uganda. Decisions of that kind, made case by case with no rule, are exactly where the previous two findings come from.
Sear (2022)A quarter of the countries were never tested at all
Lynn and Becker produced a figure from actual test data for 149 countries. The remaining 52 of 201 (25.9%) are imputed from the three countries with the longest shared land borders. Warne — the dataset’s most sympathetic serious auditor — recommends deleting them outright, and shows that where the imputation can be checked against real school testing it correlates r = −0.376 with achievement: a negative relationship.
Warne (2022), Evolutionary Psychological ScienceSeveral of the primary studies say in their own abstracts that they should not be used this way
The study behind Mali’s national figure states plainly that use of the Raven’s test “may substantially underestimate the intelligence of children in Mali” and that this “can be particularly problematic when comparisons are made across cultures using the same test and norms.” A study behind the DR Congo figure carries a similar warning. Those cautions did not survive into the table.
Sear (2022), citing Dramé & Ferguson (2019)Statistically, national IQ is close to indistinguishable from a development index
Wicherts, Borsboom and Dolan ran a principal components analysis of national IQ alongside 17 development and geography variables across 78 countries. A single component absorbed 65% of the variance, with national IQ loading 0.873 on it — sitting beside secondary-school enrolment (0.943), fertility (0.910), child mortality (0.908) and sanitation (0.895). On the numbers, it behaves like one more measure of how developed a country is.
Wicherts, Borsboom & Dolan (2010), Personality and Individual DifferencesEven its most sympathetic auditor says it does not measure national intelligence
Warne set out to defend the dataset against wholesale rejection, and still concluded: “it is not justified to say that mean IQ score differences across nations reflect mean differences in intelligence.” His recommended reading of the figures is as a measure of current average developed cognitive performance — a phenotype, shaped by circumstances, not a fixed property of a people.
Warne (2022)A learned society has formally asked researchers to stop using it
The European Human Behaviour and Evolution Association’s standing statement says these datasets “fall far short of the standards of scientific rigour, validity, and transparency required for reliable evolutionary research”, noting estimates “often based on extremely small, unrepresentative samples or on data from children”. Papers built on the dataset have been retracted: Clark et al. (2020) was withdrawn from Psychological Science at the authors’ own request after they judged some of the data “highly questionable”, and a Proceedings of the Royal Society B paper was retracted by its editors over the authors’ objection.
EHBEA statement on national IQ datasets; Bauer (2020)And the dataset does not come without an agenda attached
Anyone republishing these numbers should say where they come from. Chapter 4 of The Intelligence of Nations lists strategies for raising national IQs; the fourth and fifth are “positive eugenics” and “negative eugenics”, discussed without reference to the human-rights record of such policies. We reproduce the data because it is already everywhere. We do not endorse the book it comes from, and we think you should know what it argues.
Sear (2022), quoting Lynn & Becker (2019), p.318Where mainstream psychology actually stands
Measured differences between groups are real as measurements — nobody serious disputes that the numbers differ. What the evidence does not support is a genetic explanation for them. The American Psychological Association’s task force concluded there was no direct evidence favouring a genetic hypothesis, and the 2012 follow-up review by Nisbett, Flynn, Turkheimer and colleagues reported that this “conclusion stands today”. Their companion paper was titled, without hedging, Group differences in IQ are best understood as environmental in origin.
Two points are worth holding on to. An IQ score is a phenotype — a snapshot of developed performance under particular conditions — not a genotype. And high heritability within a population carries no logical implication about the cause of a difference between populations; that inference is a well-known statistical error, not a finding.
So why publish the table at all?
Because it is the dataset the whole internet is already quoting, almost always with none of the above attached. Anyone searching for their country’s average IQ will find these numbers within one click whatever we do. The useful thing is not to hide them — it is to publish them with the provenance, the sample sizes and the criticism in the same place, so the number can be weighed rather than simply believed.
What the data will support is modest and worth saying plainly: measured cognitive performance differs between countries; those differences track schooling, health and nutrition closely; and they move — sometimes by most of a standard deviation within two generations — when those conditions change. What it will not support is a ranking of peoples by innate ability.
Why average scores differ between countries
Measured differences between countries are real as measurements. What produces them is much better understood than the rankings suggest — and almost all of it is environmental and changeable.
Years of schooling
The best-evidenced causal factor there is. A meta-analysis of 142 effect sizes across 615,812 people found that one additional year of education raises IQ by 1 to 5 points, depending on study design, with a headline estimate of 3.4 points — and the gain persists across the lifespan.
+1 to +5 IQ points per school year · Ritchie & Tucker-Drob (2018)Iodine and early nutrition
Meta-analyses put the cost of iodine deficiency at roughly 7 to 13 IQ points — Qian and colleagues found a 12.45-point gap between children in iodine-sufficient communities and those in severely deficient areas, and supplementation during pregnancy recovers about 8.7 of them. Iodised salt is one of the cheapest interventions in public health, and its footprint is visible in national test data.
8–13.5 IQ points · Qian et al. (2005); Bougma et al. (2013)Child health
Across 78 countries, national IQ correlates −0.84 with child mortality, −0.79 with neonatal mortality and +0.72 with access to sanitation. Repeated early infection, and the malnutrition that travels with it, cost development during the years when it matters most. (The once-cited “parasite stress” paper on this topic was later retracted; these correlations come from a separate, standing analysis.)
Wicherts, Borsboom & Dolan (2010), N = 78 countriesFamiliarity with testing itself
A timed, abstract, multiple-choice reasoning test is a cultural artefact. People who have sat dozens of them since primary school perform better on them than equally able people who have never seen one. This is a measured effect, not a hypothetical one, and it maps almost exactly onto national schooling systems.
Practice and familiarity effects are well documentedLanguage and translation
A large share of the underlying studies tested people in a language that was not their first. Even “culture-fair” matrix tests come with spoken instructions, and comprehension of the instructions is scored as though it were reasoning ability.
A systematic downward bias, uncorrected in the headline figuresIncome — but less than schooling
National income does correlate with these scores, at about r = 0.69 against log GDP per capita. Educational attainment correlates far more tightly, at r = 0.92. The Gulf states are the standing counter-example: among the highest GDP per capita in the world, with scores no higher than middle-income neighbours. Money that has not been converted into schooling and child health does not show up.
Meisenberg (2012); Lynn & Meisenberg (2010)Our own explainer on the factors that affect IQ test results covers how several of these operate at the level of a single test sitting rather than a whole country.
The Flynn effect — and the reversal
Measured IQ is not fixed at the level of a population either. It rose for most of the twentieth century, nearly everywhere it was measured, and in some rich countries it has since started falling again.
Scores rose by roughly three points per decade through the twentieth century — around thirty points in total. A person scoring exactly at the 1930s average would land near the second percentile against today’s norms. The meta-analytic estimate across 285 studies is 2.31 points per decade, rising to 2.93 on modern Wechsler and Stanford-Binet tests. Nothing about human biology changed over those hundred years. Schooling, nutrition, family size and the sheer amount of abstract symbolic work in ordinary life all did.
This matters directly for the table above: a country represented by a study from 1975 and a country represented by one from 2015 are not being compared on equal terms. Some of the spread in any national IQ ranking is a gap in when people were tested rather than in how they scored.
And in several rich countries it has reversed
Norwegian male conscripts, birth cohorts 1962–1991. Scores climbed to a peak of 102.3 for the cohort born in 1975, then fell to 99.4 by the 1989 cohort — a loss of about three points in fourteen birth years. Because the decline shows up between brothers within the same families, it cannot be explained by immigration or by changing family composition. Whatever is driving it is environmental. Plotted from the trends reported in Bratsberg & Rogeberg (2018), PNAS, n = 736,808.
The same direction shows in international schooling data: average OECD performance in PISA fell 15 points in mathematics and 10 in reading between 2018 and 2022, the sharpest drop since the programme began. Whether that is a lasting reversal or a pandemic scar is still argued. Either way it undercuts any reading of a national IQ table as a permanent ordering of peoples — the countries at the top are the ones currently moving down.
What national IQ tracks
National IQ estimates are not random noise. They correlate strongly with other measures of cognitive performance — which is exactly why the environmental explanation is the compelling one.
Here is what they actually track, from the published literature. National IQ correlates with educational attainment at r = 0.92, with international student assessments such as PISA and TIMSS at 0.85, with mean years of schooling at 0.76, with adult literacy at 0.64 — and with child mortality at −0.84. Against log GDP per capita it manages 0.69.
Notice the ordering. The tightest relationships are all with schooling and child health; income comes some way behind. And when Wicherts, Borsboom and Dolan placed national IQ in a principal components analysis alongside 17 development and geography indicators, a single component absorbed 65% of the variance, with national IQ loading 0.873 on it — right beside secondary-school enrolment at 0.943, fertility at 0.910, child mortality at 0.908 and sanitation at 0.895. Statistically, the measure behaves like one more indicator of a country’s development level.
The arithmetic that the rankings leave out. Mean years of schooling run from 14.3 in Germany to 1.4 in Niger. At the meta-analytic rate of 3.4 IQ points per additional school year, that 12.9-year gap is worth about 44 IQ points on its own — larger than the entire 32.5-point gap between the East Asian and sub-Saharan African regional averages that the table reports. One well-measured environmental variable more than accounts for the difference it is usually invoked to explain. Sources: UNDP Human Development Report; Ritchie & Tucker-Drob (2018).
The PISA cross-check
The OECD’s PISA programme tests fifteen-year-olds in 81 education systems on a common instrument, with proper sampling — everything the national IQ dataset lacks. Its 2022 leaders were Singapore (575 in mathematics), Macau, Taiwan, Japan, South Korea and Hong Kong, with Estonia the highest-scoring non-Asian system and Canada, Ireland and Switzerland close behind. That is very nearly the top of the IQ table, arrived at independently.
The instructive case is Vietnam: 34th in PISA, well above what its income or its average schooling would predict, and 60th in the IQ table at 89.5 — noticeably higher than its neighbours and its GDP per capita would suggest. Countries that invest early in schooling outperform their wealth on both measures. That is a policy finding, not a genetic one.
Why a country average says nothing about you
This is the single most misread thing on this page, so it is worth showing rather than asserting. Two national distributions ten points apart still overlap almost completely.
Two countries, ten points apart. Each curve is a full national distribution with a standard deviation of 15. The shaded region is the overlap: roughly three quarters of both populations fall inside it. Pick one person at random from the lower-scoring country and one from the higher-scoring country, and the person from the lower-scoring country scores higher about 32 times out of 100. A national average is a fact about a distribution. It is not a prediction about a person.
So stop reading the table and take the test.
Twenty minutes, scored against the full population curve, with your percentile, a certificate in your name and a breakdown of four reasoning abilities measured separately.
What counts as a good IQ score?
IQ is not a raw total. It is a position on a curve, built so that the population mean is 100 and the standard deviation is 15. That construction is what makes any of these comparisons possible.
The IQ distribution. Half of all people score between 90 and 110. About 1 in 6 score above 115, roughly 1 in 44 above 130, and about 1 in 741 above 145. The same curve is used to place every score on this page, which is why a national average of 85 and one of 100 are only one standard deviation apart.
| IQ range | Usual label | Percentile | How common |
|---|---|---|---|
| 130 and above | Very superior / gifted | 97.7th and up | 1 in 44 |
| 120 – 129 | Superior | 90.9th – 97.7th | 1 in 11 at 120 |
| 110 – 119 | High average | 74.8th – 90.9th | 1 in 4 at 110 |
| 90 – 109 | Average | 25.2nd – 74.8th | 1 in 2 |
| 80 – 89 | Low average | 9.1st – 25.2nd | 1 in 11 at 80 |
| 70 – 79 | Borderline | 2.3rd – 9.1st | 1 in 44 at 70 |
| Below 70 | Extremely low | Below the 2.3rd | 1 in 44 |
We go through this in more depth in IQ score ranges explained, the IQ level chart and IQ classifications. If you are curious where the threshold for the top tier sits, what counts as a genius IQ level covers it, and what an average IQ test score means is the companion piece to this page.
A closer look at ten countries
The same figure means slightly different things depending on how it was collected. These are the countries people search for most, with the context the ranking alone leaves out.
India — 76.24
The most-searched figure on this page, and one of the least secure. India’s value rests largely on studies of rural schoolchildren, several of them decades old, tested on Western norms and often not in their first language — in a country with 22 official languages and enormous variation in school access. It is not a national measurement in any meaningful sense. Online tests taken by self-selected Indian visitors routinely return figures 15 to 20 points higher; that is not a contradiction, because a self-selected internet sample and a rural school sample are not measuring the same population.
Rank #144 of 201United States — 97.43
Backed by the largest sample in the dataset at 62,649 people, which makes it one of the more solid entries. Worth pairing with PISA 2022, where the US placed 18th overall — ninth in the world in reading but below the OECD average in mathematics. A single national number hides very large internal variation.
Rank #29 of 201United Kingdom — 99.18
The reference point for the whole scale: the Greenwich norm sets Britain at 100, and every other country in the table is expressed relative to it. That is a historical convention, not a statement about Britain — had the dataset been anchored elsewhere, every number on this page would shift together.
Rank #21 of 201China — 104.10
Consistently near the top, and consistently drawn from urban and coastal samples that are not representative of the country as a whole. China’s PISA entries have similarly come from its wealthiest provinces. The score is real for the people tested; it is not a national average in the way the table implies.
Rank #5 of 201Japan — 107.01
First in the table, and the entry with the least controversy attached: long compulsory schooling, near-universal literacy, low childhood disease burden and decades of well-documented testing. Japan also sits fourth in PISA 2022. Note the margin, though — first and tenth are separated by under six points.
Rank #1 of 201Singapore — 105.89
Third in this table and first in the world in all three PISA domains, by a clear margin. Singapore is the strongest case that a national cognitive score is largely a report card on an education system: it has risen dramatically within living memory, over a period far too short for anything but schooling and public health to have changed.
Rank #3 of 201Pakistan — 80.00
An exactly round value of 80.00 is itself a warning sign — real measurements rarely land on round numbers. Like several of its neighbours, Pakistan’s figure comes from a thin evidence base, and should be read as an order of magnitude rather than a measurement.
Rank #121 of 201Nigeria — 67.80
Africa’s largest economy and most populous country, with a listed figure that the underlying studies cannot support. Nigeria has among the widest gaps in the world between children in and out of school; the samples reflect that access gap rather than the population’s capability.
Rank #173 of 201Brazil — 83.38
Mid-table, and a good illustration of how little wealth alone predicts. Brazil’s score sits close to countries with a fraction of its GDP, and its PISA results (60th of 81) track its schooling outcomes far more closely than its income.
Rank #99 of 201Australia — 99.24
Tied to two decimal places with Hungary and Switzerland — a reminder of how fine the distinctions in the middle of this table are, and how little meaning should be read into a difference of one or two ranks.
Rank #18 of 201Country IQ: common questions
Which country has the highest average IQ?
In the dataset every ranking is built from — Lynn & Becker’s The Intelligence of Nations (2019) — Japan is first at 107.01, followed by Taiwan (106.47), Singapore (105.89), Hong Kong (105.37) and China (104.10). Most sites republishing this table list Japan at 106.48, which comes from a mis-transcribed copy. Either way the top five sit inside two points of one another — within the measurement error of any IQ test — so treating this as a settled ordering is not something the data supports.
Which country has the lowest average IQ?
The lowest figure in the table is Nepal at 42.99. It should not be taken at face value. A national average in the forties would mean most of the population met the clinical threshold for intellectual disability, which is not what is observed in Nepal or anywhere else. The dataset’s own authors flagged the figure as implausible and it has been publicly challenged in Nepal’s national press. It reflects a poor sample, not a population.
What is the average IQ in India, and where does India rank?
India’s listed value is 76.24, placing it 144th of 201. That number rests largely on studies of rural schoolchildren, several of them decades old, tested against Western norms and often not in their first language — in a country with 22 official languages and very wide variation in school access. It is not a representative national measurement. Online tests taken by self-selected Indian visitors typically return figures 15–20 points higher, because a self-selected internet sample and a rural school sample are not the same population. Take the test and you will get your own score rather than a contested national one.
What is the average IQ in the world?
The unweighted average of the 201 entries is 81.90. Weighted by population, the dataset’s own total is 86.05. Both sit below 100 because 100 is not a world average — it is the British norm the scale was anchored to, and every other country is expressed relative to it.
Are average IQ by country rankings reliable?
Only up to a point. 53 of the 201 countries have no test data of any kind and carry a neighbour’s value instead — North Korea, sixth in the world on this table, is one of them; where that estimating step can be checked against real school testing it correlates negatively with the outcome it is supposed to predict. Sample sizes behind national means run from 19 people to 62,649. Eighteen countries moved by more than ten points between the 2012 and 2019 revisions. The rankings are a reasonable guide to broad regional patterns in school achievement and a poor guide to anything else.
Why do IQ scores differ between countries?
Overwhelmingly because of environment and measurement, not ancestry. Years of schooling alone are worth 1–5 IQ points per year; iodine deficiency costs 8–13.5; childhood disease burden, testing familiarity, and being tested in a second language all push scores down independently of ability. The 12.9-year schooling gap between Germany and Niger is arithmetically worth about 44 IQ points — more than the entire 32.5-point gap between the highest and lowest scoring regions.
Why do East Asian countries score highest?
The countries at the top share long compulsory schooling, near-universal literacy, low childhood disease burden and a culture of frequent formal testing from an early age. They also lead the OECD’s PISA assessments, which sample properly and test school achievement directly. Two instruments agreeing tells you the schooling effect is real. Neither tells you the cause is innate — and Singapore’s rise happened far too quickly for anything but schooling and public health to explain.
Is IQ genetic or environmental?
Within a population, individual differences in IQ have a substantial heritable component that rises with age. That is a separate question from why group averages differ, and the second does not follow from the first. Average scores have moved by around 30 points over a century, and by roughly three points inside fourteen birth cohorts in Norway — changes far too fast to be genetic. On the evidence available, national differences in measured IQ are best explained by schooling, health, nutrition and testing conditions.
Why do different websites give my country a different IQ?
Because they are quoting different datasets. Some use the quality-weighted column of the 2019 Lynn & Becker data (the one on this page), others the unweighted column, the 2012 revision, or the 2002 Lynn & Vanhanen figures. Some publish averages of their own self-selected online visitors, which usually run much higher because people who choose to take an IQ test are not a random sample. Always check which dataset and which year a page is quoting.
What is the Flynn effect, and is it still happening?
The Flynn effect is the rise in measured IQ over the twentieth century — roughly three points per decade, about 30 points in total. It is still running in much of the developing world. In several rich countries it has reversed: Norwegian conscript scores peaked with the 1975 birth cohort at 102.3 and fell to 99.4 by 1989, and because the decline appears between brothers in the same families it cannot be immigration or changing family composition.
Is average IQ falling in developed countries?
In some, on some measures, yes. The Norwegian conscript data show a clear reversal, and OECD average PISA scores fell 15 points in mathematics and 10 in reading between 2018 and 2022 — the largest drop since PISA began. Whether that is a lasting trend or a pandemic effect is still being argued.
Do PISA scores measure the same thing as IQ?
Not the same thing, but they overlap heavily. PISA tests fifteen-year-olds on applied reasoning in mathematics, reading and science with proper national sampling. National IQ estimates and international achievement datasets correlate at r = 0.84–0.98 across 201 nations. PISA is the better-built instrument by a wide margin; where the two disagree, PISA is generally the one to trust.
Does a higher national IQ mean a richer country?
The two correlate, but the relationship is loose and the causal direction runs both ways at once. The Gulf states are the standing counter-example: among the highest GDP per capita in the world, with scores no higher than middle-income neighbours. Vietnam is the mirror image — well above what its income predicts on both IQ and PISA. Wealth that has been converted into schooling and child health shows up in the scores; wealth that has not, does not.
Does education raise IQ?
Yes, and this is the strongest causal evidence in the whole field. A meta-analysis of 142 effect sizes covering 615,812 people found that one extra year of schooling raises IQ by 1–5 points depending on the study design, with the effects persisting across the lifespan and across every broad ability domain.
Are IQ tests culturally biased against non-Western countries?
The tests used in much of this dataset were normed on Western populations, sometimes decades before they were administered elsewhere, frequently in a second language, and often to people with no prior experience of timed formal testing. Each of those depresses scores independently of ability. “Culture-fair” matrix tests reduce the problem but do not remove it, because comprehension of the instructions is still scored as if it were reasoning.
How is a country’s average IQ actually calculated?
Researchers collect published studies that administered an IQ test in that country, convert each result onto a common scale anchored to a British mean of 100, adjust for the age of the norms, weight the studies by sample size and quality, and average them. Where no study exists, the value is estimated from neighbouring countries. The 2019 edition pools 669 studies covering 617,581 people across 201 entries, 53 of which have no study behind them at all.
Can I compare my own IQ score to my country’s average?
You can, but it is less informative than it sounds. National averages come from different tests, different decades and very different samples, so the comparison is rarely like for like. Your percentile against the full population distribution is a far more meaningful figure — and it is what our test reports. Take the IQ test to get it.
What is a good IQ score?
About 68% of people score between 85 and 115, so anything in that band is squarely average. Roughly 16% score above 115, about 1 in 44 above 130 and about 1 in 741 above 145. Our guides to IQ score ranges and IQ classifications go through each band in detail.
Is an IQ of 120 good? Is 130 genius level?
An IQ of 120 puts you at about the 91st percentile — roughly 1 person in 11. 130 is the conventional threshold for “very superior” or gifted, at about the 98th percentile, or 1 in 44. Whether that counts as genius is a matter of definition rather than measurement; what counts as a genius IQ level covers where the various thresholds are drawn.
Where does the data on this page come from?
The country values are the quality-weighted column of Richard Lynn and David Becker’s The Intelligence of Nations (Ulster Institute for Social Research, 2019) and the accompanying NIQ dataset. The critical analysis draws on Warne (2022), Sear (2022), Wicherts and colleagues, Ritchie & Tucker-Drob (2018), Bratsberg & Rogeberg (2018) and OECD PISA 2022. Every source is listed at the foot of this page.
Sources & how we built this page
We publish the dataset in full, name it, and publish the criticism of it in the same place. Every figure on this page can be traced to one of the sources below.
How this page was built
- Country values are the quality-weighted column of the 2019 Lynn & Becker national IQ dataset, reproduced without alteration. We have not adjusted, smoothed or re-ranked anything.
- Entries marked est. in the table share an identical value with two or more other countries — the visible signature of geographic imputation rather than measurement.
- Regional figures are unweighted means of the countries listed in each region, computed from the same table. They are not population-weighted.
- Percentiles, band shares and the distribution figures are computed directly from a normal curve with mean 100 and standard deviation 15.
- Flag images are served by flagcdn.com. Map geometry is derived from Natural Earth (public domain), drawn on a Robinson projection.
Sources & further reading
- Lynn, R. & Becker, D. (2019). The Intelligence of Nations. Ulster Institute for Social Research. NIQ-DATASET V1.3.2, sheet NAT, column QNW+SAS+GEO — the source of every country value on this page, read from the published workbook rather than a secondary copy. View source
- Wicherts, J. M., Dolan, C. V. & van der Maas, H. L. J. (2010). “A systematic literature review of the average IQ of sub-Saharan Africans.” Intelligence, 38(1), 1–20. The source of the 67.4-versus-80.4 finding on which studies were and were not included. View source
- Wicherts, J. M., Dolan, C. V., Carlson, J. S. & van der Maas, H. L. J. (2010). “Another failure to replicate Lynn’s estimate of the average IQ of sub-Saharan Africans.” Learning and Individual Differences. Shows that representativeness judgements tracked the sample’s own score. View source
- Wicherts, J. M., Borsboom, D. & Dolan, C. V. (2010). “Why national IQs do not support evolutionary theories of intelligence.” Personality and Individual Differences, 48(2), 91–96. Source of the 18-variable principal components analysis and the child-mortality correlations. View source
- Sear, R. (2022) [preprint, not peer reviewed]. “‘National IQ’ datasets do not provide accurate, unbiased or comparable measures of cognitive ability worldwide.” PsyArXiv. Source of the sample-type audit (223 of 683 coded national), the missing-method critique, the Mali and DR Congo primary-study warnings, and the eugenics chapter. View source
- Warne, R. T. (2022). “National mean IQ estimates: validity, data quality, and recommendations.” Evolutionary Psychological Science. Source of the 149-versus-52 imputation count, the sample-size range and the r = −0.376 finding. View source
- European Human Behaviour and Evolution Association. Statement on ‘National IQ’ datasets (first issued 27 July 2020, subsequently revised), asking researchers not to use them in evolutionary research. View source
- Nisbett, R. E., Aronson, J., Blair, C., Dickens, W., Flynn, J., Halpern, D. F. & Turkheimer, E. (2012). “Intelligence: new findings and theoretical developments” and “Group differences in IQ are best understood as environmental in origin.” American Psychologist. View source
- Ritchie, S. J. & Tucker-Drob, E. M. (2018). “How much does education improve intelligence? A meta-analysis.” Psychological Science. 142 effect sizes, 615,812 participants — the 1–5 points per school year figure. View source
- Bratsberg, B. & Rogeberg, O. (2018). “Flynn effect and its reversal are both environmentally caused.” PNAS. 736,808 Norwegian conscripts — the source of the reversal chart. View source
- Trahan, L., Stuebing, K. K., Fletcher, J. M. & Hiscock, M. (2014). “The Flynn effect: a meta-analysis.” Psychological Bulletin. 285 studies — 2.31 points per decade, 2.93 on modern tests. View source
- Meisenberg, G. (2012); Lynn, R. & Meisenberg, G. (2010). Sources of the GDP (r = 0.69), schooling (0.76) and educational-attainment (0.92) correlations quoted above. View source
- Qian, M. et al. (2005); Bougma, K. et al. (2013). Meta-analyses of iodine deficiency and supplementation — the 7–13 IQ point range quoted above. View source
- Barnett, S. M. & Williams, W. (2004). “National intelligence and the emperor’s new clothes.” Contemporary Psychology: APA Review of Books. Judged the cross-country comparisons “virtually meaningless”. View source
- OECD (2023). PISA 2022 Results (Volume I). Source for every PISA figure quoted, and for the 2018–2022 OECD decline. View source
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