PISA maths vs. Religious attendance
Holds up after adjusting for income
Across 75 countries, PISA maths and Religious attendance rise and fall together at r = -0.61 (on a scale from −1 to +1, where 0 means no link). Comparing only countries with similar income (GDP per person) shrinks it to -0.41 (q = 0.049, allowing for the many pairs tested). Much of the first figure is that both measures rise with national income, but a moderate negative link remains.
Comparing countries across the middle half of religious attendance, 16.4% to 47.3% of respondents, pisa maths is worse by 52.7 PISA points at the top of that range than the bottom. Comparing only countries with similar national income, the gap is 22.3 PISA points.
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.
Both of these rise and fall closely with national income, so a strong link between them before adjusting was close to certain. Read the adjusted figure, not the first one.
“Link with income” is how closely each measure tracks GDP per person across countries, from −1 to +1.
Every country as a dot
best-fit line line after adjusting
Four ways to measure the link
| Method | r | p | Countries |
|---|---|---|---|
| Standard (Pearson), not adjusted | -0.611 | 6.0e-9 | 75 |
| By rank (Spearman), not adjusted | -0.632 | 1.2e-9 | 75 |
| Standard (Pearson), adjusted for national income | -0.406 | 0.000 | 75 |
| By rank (Spearman), adjusted for national income | -0.419 | 0.000 | 75 |
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 75 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: +0.205 (a minus sign means it grew).
How solid is it?
Leaving out one country at a time, r ranges from -0.454 (without SGP) to -0.370 (without VNM). 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: SGP (-0.049).
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.
| n | r | ||
|---|---|---|---|
| East Asia & Pacific | 13 | -0.65 | |
| Europe & Central Asia | 44 | -0.36 |
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.
| n | r | ||
|---|---|---|---|
| Poorest third | 25 | -0.62 | |
| Middle third | 25 | -0.47 | |
| Richest third | 25 | -0.29 |
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.
| n | r | ||
|---|---|---|---|
| Christians | 49 | -0.48 | |
| Muslims | 14 | +0.02 |
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 = -0.406 after dropping 0 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.
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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 respondents | Years | |
|---|---|---|---|
| Singapore SGP | 575 | 42.6% | 2022 |
| Macao SAR, China MAC | 552 | 9.5% | 2022 |
| Hong Kong SAR, China HKG | 540 | 16.1% | 2022 |
| Japan JPN | 536 | 12.3% | 2022 |
| Korea, Rep. KOR | 527 | 22.8% | 2022 |
| Estonia EST | 510 | 8% | 2022 |
| Switzerland CHE | 508 | 16.2% | 2022 |
| Canada CAN | 497 | 16.4% | 2022 |
| Netherlands NLD | 493 | 14.3% | 2022 |
| Ireland IRL | 492 | 53.3% | 2022, 2010 |
| Belgium BEL | 489 | 18.9% | 2022, 2010 |
| Denmark DNK | 489 | 6.48% | 2022 |
| United Kingdom GBR | 489 | 16.1% | 2022 |
| Poland POL | 489 | 64.3% | 2022 |
| Russian Federation RUS | 488 | 16.3% | 2018, 2022 |
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
Haerpfer, C. et al., World Values Survey; EVS, European Values Study
Sources
PISA maths
PISA mean mathematics score
OECD · via Our World in Data · CC BY 4.0 (OECD terms and conditions) · updated annual, except the snapshots noted per indicator
The average score of 15-year-olds on the same test in every country taking part. It is scaled so the OECD average in the starting year was 500, with a standard deviation (a typical gap between students) of 100. Held every three years. The 2021 round was held in 2022, and the OECD says it can still be compared with earlier rounds despite the pandemic. The three subjects are treated as measuring the same thing. Their links with each other are above 0.95, and that close match is a fact about the test, not about schooling.
Religious attendance
Share attending religious services frequently
World Values Survey Association and European Values Study · via Our World in Data · Free for non-commercial use with attribution · updated irregular (survey waves, roughly every 5 years)
The share who attend religious services at least once a month. This measures taking part, not belief or belonging to a religion. Those are three different things, and they can differ sharply. A country can be almost entirely religious by belonging and yet rarely attend anything. No "better" direction is set, and none could be defended. Attendance describes how people live. It does not show whether a country is doing well, and calling either end the good one would be a claim this site has no basis for. The survey runs in waves, not every year, so data for each country are sparse and uneven.
How this was computed
Data used: most recent value in 2010-2025; values come from 2010–2022. 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 maths and Religious attendance
This page shows that two measures go together. It does not show that PISA maths changes Religious attendance, or the reverse. These figures also describe countries, not individual people. See the ecological fallacy.
More links with PISA maths or Religious attendance
- Frequent prayer vs Religious attendance before +0.89 → after adjusting +0.81
- Religion very important vs Religious attendance before +0.84 → after adjusting +0.71
- PISA maths vs Researchers before +0.81 → after adjusting +0.59
- Frequent prayer vs PISA maths before -0.76 → after adjusting -0.58
- PISA maths vs Religion very important before -0.73 → after adjusting -0.56
- Inequality-adjusted HDI vs Religious attendance before -0.76 → after adjusting -0.54
- Hospital beds vs PISA maths before +0.53 → after adjusting +0.52
- Health score vs PISA maths before +0.58 → after adjusting +0.51