placestats

PISA science vs. Religiously unaffiliated

Fades after adjusting for income

A country is not a person. Countries where more people are counted as belonging to this group also tend to differ on the other measure, and that is all. It does not follow that the people in the group are the people with the different score. Making that leap is called the ecological fallacy: reading a pattern across places as a fact about individual people. It is the most common misuse of this kind of data. Religion also varies strongly with region, history and national income, so much of what looks religious here is really those. That is what the adjusted figures are for. The religion shares are estimates for two years only, and the survey questions are asked in rounds that can be ten years apart.

Across 87 countries, PISA science and Religiously unaffiliated rise and fall together at r = +0.68 (on a scale from −1 to +1, where 0 means no link). Comparing only countries with similar income (GDP per person) leaves r = +0.63, which could easily be chance (q = 0.13, allowing for the many pairs tested, and allowing for countries in the same region being alike).

Comparing countries across the middle half of pisa science, 403 to 491 PISA points, religiously unaffiliated is 21.2% of population higher at the top of that range than the bottom. Comparing only countries with similar national income, the gap is 28.5% of population.

Link before adjusting (r)+0.677p = 6.1e-13 · 87 countries
After adjusting for national income+0.628p = 9.8e-11 · likely range [+0.48, +0.74]
p, allowing for regions0.027standard error 0.183 · 5 regions
Check for luck (q)0.126across 12,497 pairs

How to read these.r runs from −1 (one goes up as the other goes down) to +1 (they rise together), and 0 means no link. Adjusting for national income means comparing countries with the same GDP per person, so differences in wealth can’t explain the link. Income is used in percentage terms, since an extra $1,000 means more to a poor country than to a rich one. p is how likely a link this strong would be if there were really none. Below 0.05 means it is unlikely to be chance. Very small values are written in short form: 1.1e-32 means a decimal point followed by 31 zeros and then 11, so very close to zero. The likely range is where the true figure probably lies, and a range that crosses zero means the link could easily be chance. Countries in the same region tend to resemble each other, so the third figure allows for that, which gives a fairer p. The standard error is the typical size of the error in r. Finally, testing this many pairs means some will look strong by luck alone. A q below 0.05 means this link is unlikely to be one of those.

PISA science · PISA pointslink with income +0.78 · high
Religiously unaffiliated · % of populationlink with income +0.51 · moderate

“Link with income” is how closely each measure tracks GDP per person across countries, from −1 to +1.

Every country as a dot

PISA science · PISA points →Religiously unaffiliated · % of population →3475610%72.8%Albania: 376 PISA points, 7.65% of populationUnited Arab Emirates: 432 PISA points, 0.336% of populationArgentina: 406 PISA points, 9.23% of populationAustralia: 507 PISA points, 42.3% of populationAustria: 491 PISA points, 22.4% of populationBelgium: 491 PISA points, 39% of populationBulgaria: 421 PISA points, 10% of populationBosnia and Herzegovina: 398 PISA points, 1.05% of populationBelarus: 471 PISA points, 13.8% of populationBrazil: 403 PISA points, 13.5% of populationBrunei Darussalam: 446 PISA points, 0.156% of populationCanada: 515 PISA points, 34.6% of populationSwitzerland: 503 PISA points, 30.8% of populationChile: 444 PISA points, 30.3% of populationColombia: 411 PISA points, 9.94% of populationCosta Rica: 411 PISA points, 10.1% of populationCyprus: 411 PISA points, 6.57% of populationCzechia: 498 PISA points, 72.8% of populationGermany: 492 PISA points, 36.1% of populationDenmark: 494 PISA points, 16.6% of populationDominican Republic: 360 PISA points, 19.6% of populationAlgeria: 376 PISA points, 1.27% of populationSpain: 485 PISA points, 26.4% of populationEstonia: 526 PISA points, 43.6% of populationFinland: 511 PISA points, 25% of populationFrance: 487 PISA points, 42.6% of populationUnited Kingdom: 500 PISA points, 40.2% of populationGeorgia: 384 PISA points, 0.988% of populationGreece: 441 PISA points, 4.74% of populationGuatemala: 373 PISA points, 6.02% of populationHong Kong SAR, China: 520 PISA points, 71.4% of populationCroatia: 483 PISA points, 6.66% of populationHungary: 486 PISA points, 27% of populationIndonesia: 383 PISA points, 0.092% of populationIreland: 504 PISA points, 15.6% of populationIceland: 447 PISA points, 19.8% of populationIsrael: 465 PISA points, 4.37% of populationItaly: 477 PISA points, 13.3% of populationJamaica: 403 PISA points, 23.7% of populationJordan: 375 PISA points, 0.0474% of populationJapan: 547 PISA points, 57.5% of populationKazakhstan: 423 PISA points, 2.53% of populationCambodia: 347 PISA points, 0.079% of populationKorea, Rep.: 528 PISA points, 48.3% of populationLebanon: 384 PISA points, 0.0188% of populationLithuania: 484 PISA points, 7.08% of populationLuxembourg: 477 PISA points, 25.3% of populationLatvia: 494 PISA points, 17% of populationMacao SAR, China: 543 PISA points, 67.6% of populationMorocco: 365 PISA points, 0.131% of populationMoldova: 417 PISA points, 0.234% of populationMexico: 410 PISA points, 10.6% of populationNorth Macedonia: 380 PISA points, 0.516% of populationMalta: 466 PISA points, 5.24% of populationMontenegro: 403 PISA points, 1.14% of populationMongolia: 412 PISA points, 40.8% of populationMalaysia: 416 PISA points, 0.845% of populationNetherlands: 488 PISA points, 54.1% of populationNorway: 478 PISA points, 22.5% of populationNew Zealand: 504 PISA points, 51.4% of populationPanama: 388 PISA points, 6.21% of populationPeru: 408 PISA points, 5.11% of populationPhilippines: 356 PISA points, 0.0411% of populationPoland: 499 PISA points, 8.65% of populationPortugal: 484 PISA points, 13.8% of populationParaguay: 368 PISA points, 4.25% of populationWest Bank and Gaza: 369 PISA points, 0% of populationQatar: 432 PISA points, 0.274% of populationRomania: 428 PISA points, 0.94% of populationRussian Federation: 478 PISA points, 20.2% of populationSaudi Arabia: 390 PISA points, 0.112% of populationSingapore: 561 PISA points, 19.9% of populationEl Salvador: 373 PISA points, 11.9% of populationSerbia: 447 PISA points, 4.01% of populationSlovak Republic: 462 PISA points, 25.3% of populationSlovenia: 500 PISA points, 32.3% of populationSweden: 494 PISA points, 28.9% of populationThailand: 409 PISA points, 0.0126% of populationTrinidad and Tobago: 425 PISA points, 2.45% of populationTunisia: 386 PISA points, 0.441% of populationTurkiye: 476 PISA points, 2.53% of populationUkraine: 450 PISA points, 15.1% of populationUruguay: 435 PISA points, 52.4% of populationUnited States: 499 PISA points, 29.7% of populationUzbekistan: 355 PISA points, 0.552% of populationViet Nam: 472 PISA points, 67.7% of populationKosovo: 357 PISA points, 0.139% of populationCZEHKGJPNKHMMACPHLPOLSGPTURURYUZBVNM

best-fit line line after adjusting

Four ways to measure the link

MethodrpCountries
Standard (Pearson), not adjusted+0.6776.1e-1387
By rank (Spearman), not adjusted+0.7505.9e-1787
Standard (Pearson), adjusted for national income+0.6289.8e-1187
By rank (Spearman), adjusted for national income+0.6604.6e-1287

The rank version uses only each country’s place in line, from lowest to highest, so a few extreme countries count for less. The adjusted and unadjusted versions use the same 87 countries: those that report both measures and GDP per person. So the gap between them comes from the adjustment, not from a change in which countries are counted. Drop in the size of r after adjusting: +0.049 (a minus sign means it grew).

How solid is it?

Leaving out one country at a time, r ranges from +0.598 (without VNM) to +0.648 (without DOM). The bar above shows that range on a scale from −1 to +1, with the solid line at the full result. The single country that moves r most: VNM (-0.030).

Within each region

Countries are not separate, unrelated cases, and neighbors share a lot. A link that holds inside each region is far more believable than one that shows up only when comparing regions.

nr
East Asia & Pacific15+0.83
Europe & Central Asia44+0.49
Latin America & Caribbean15+0.41

By income third

If the link shows up only in the richest third of countries, it is a feature of rich countries, not a general pattern.

nr
Poorest third29+0.64
Middle third29+0.48
Richest third29+0.73

By largest religious group

Countries grouped by a label they share, such as main religion, rather than by a number. Groups of fewer than twelve countries are not shown. These groups differ in income, region and history all at once. So a gap between them is a place to start asking questions, not an answer.

nr
Christians55+0.54
Muslims18+0.02

By last european coloniser

Countries grouped by a label they share, such as main religion, rather than by a number. Groups of fewer than twelve countries are not shown. These groups differ in income, region and history all at once. So a gap between them is a place to start asking questions, not an answer.

nr
Spain14+0.43
United Kingdom14+0.82

Without outliers (countries far outside the middle half of countries on either measure, by more than one and a half times the width of that middle half): r = +0.629 after dropping 2 countries.

Two series, one country

Both measures over the years for one country you pick. The two charts are stacked so they share only the years along the bottom.

Loading…

Over time, within countries

Everything above compares countries with each other at one moment. This section compares each country only with itself over 0years. So a link here can’t come from anything about a country that stays the same, such as its history, geography, institutions or culture.

Not enough history inside each country to look at this over time. That needs countries measured for several years in a row, and at least one of these measures is measured too rarely.

The data


PISA points
% of population		Years
Singapore SGP56119.9%2022, 2020
Japan JPN54757.5%2022, 2020
Macao SAR, China MAC54367.6%2022, 2020
Korea, Rep. KOR52848.3%2022, 2020
Estonia EST52643.6%2022, 2020
Hong Kong SAR, China HKG52071.4%2022, 2020
Canada CAN51534.6%2022, 2020
Finland FIN51125%2022, 2020
Australia AUS50742.3%2022, 2020
New Zealand NZL50451.4%2022, 2020
Ireland IRL50415.6%2022, 2020
Switzerland CHE50330.8%2022, 2020
Slovenia SVN50032.3%2022, 2020
United Kingdom GBR50040.2%2022, 2020
United States USA49929.7%2022, 2020

OECD databases as named on each indicator: PISA, Social Expenditure Database (SOCX), Income Distribution Database, Development Assistance Committee statistics, Family Database, Government at a Glance, Corporate Tax Statistics, employment and environment statistics
Pew Research Center, Religious Composition by Country, 2010-2020. Pew Research Center bears no responsibility for the analyses or interpretations of the data presented here.
One of these measures is published under a licence that forbids changes. Values are shown exactly as published and must not be republished in a changed or rescaled form.

Sources

PISA science

PISA mean science score

OECD · via Our World in Data · CC BY 4.0 (OECD terms and conditions) · updated annual, except the snapshots noted per indicator

Religiously unaffiliated

Share of the population religiously unaffiliated

Pew Research Center · via Our World in Data · Pew Research Center terms of use, excerpts with attribution · updated decennial · comparable from 2010 only

People who belong to no religion: atheists, agnostics and those who say "nothing in particular". Pew estimated it from censuses and surveys for 2010 and 2020. Belonging is a third thing, beside the attendance and importance measures already here. A country can be almost all affiliated and rarely attend, as much of Europe is. With only two years, nothing here shows a trend. No "better" direction is set.

How this was computed

Data used: most recent value in 2010-2025; values come from 2015–2022. To adjust for income, each measure is first predicted from GDP per person (in percentage terms, on a log scale) with a straight-line fit. Only what is left over is then compared. This is called a partial correlation. The line is drawn the standard way (ordinary least squares), which picks the line that comes closest to all the countries at once. The error margins allow for countries in the same region resembling each other, using 5 World Bank regions. The q-value corrects for testing all 12,497 pairs at once, using the Benjamini–Hochberg method. Underlying data last updated DYB 2024. How the country data works · explore PISA science and Religiously unaffiliated

This page shows that two measures go together. It does not show that PISA science changes Religiously unaffiliated, or the reverse. These figures also describe countries, not individual people. See the ecological fallacy.

More links with PISA science or Religiously unaffiliated