placestats

Confidence in religious institutions vs. Education score

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 104 countries, Confidence in religious institutions and Education score rise and fall together at r = -0.56 (on a scale from −1 to +1, where 0 means no link). Comparing only countries with similar income (GDP per person) shrinks it to -0.21, which could easily be chance (q = 0.26, allowing for the many pairs tested, and allowing for countries in the same region being alike). So the first figure mostly shows richer countries differing from poorer ones, not a link between these two things.

Comparing countries across the middle half of confidence in religious institutions, 47.4% to 76% of respondents, education score is worse by 0.363 typical gaps at the top of that range than the bottom. Comparing only countries with similar national income, the gap is 0.0971 typical gaps.

Link before adjusting (r)-0.562p = 5.4e-10 · 104 countries
After adjusting for national income-0.207p = 0.036 · likely range [-0.39, -0.01]
p, allowing for regions0.090standard error 0.103 · 7 regions
Check for luck (q)0.255across 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.

Confidence in religious institutions · % of respondentslink with income -0.57 · moderate
Education score · typical gaps (standard deviations)link with income +0.81 · proxy

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

Every country as a dot

Confidence in religious institutions · % of respondents →Education score · typical gaps (standard deviations) →7.91%99.8%-1.241.44Albania: 52.7% of respondents, 0.923 typical gaps (standard deviations)Andorra: 28.4% of respondents, 0.892 typical gaps (standard deviations)Argentina: 57.9% of respondents, 1.03 typical gaps (standard deviations)Armenia: 70.4% of respondents, 0.65 typical gaps (standard deviations)Australia: 31.3% of respondents, 1.03 typical gaps (standard deviations)Austria: 36.1% of respondents, 1 typical gaps (standard deviations)Azerbaijan: 69.6% of respondents, 0.629 typical gaps (standard deviations)Belgium: 36.2% of respondents, 1.25 typical gaps (standard deviations)Burkina Faso: 77.4% of respondents, -0.582 typical gaps (standard deviations)Bangladesh: 99.8% of respondents, 0.335 typical gaps (standard deviations)Bulgaria: 35.1% of respondents, 0.794 typical gaps (standard deviations)Bosnia and Herzegovina: 56.5% of respondents, 0.607 typical gaps (standard deviations)Belarus: 58.3% of respondents, 0.722 typical gaps (standard deviations)Bolivia: 49% of respondents, 0.634 typical gaps (standard deviations)Brazil: 66.9% of respondents, 0.731 typical gaps (standard deviations)Canada: 39.6% of respondents, 1.06 typical gaps (standard deviations)Switzerland: 33.7% of respondents, 0.92 typical gaps (standard deviations)Chile: 44.6% of respondents, 0.979 typical gaps (standard deviations)China: 20% of respondents, 0.674 typical gaps (standard deviations)Colombia: 55.4% of respondents, 0.63 typical gaps (standard deviations)Cyprus: 61.7% of respondents, 1.02 typical gaps (standard deviations)Czechia: 22.8% of respondents, 1.08 typical gaps (standard deviations)Germany: 31.5% of respondents, 0.938 typical gaps (standard deviations)Denmark: 59.1% of respondents, 0.941 typical gaps (standard deviations)Algeria: 67.8% of respondents, 0.663 typical gaps (standard deviations)Ecuador: 75% of respondents, 0.722 typical gaps (standard deviations)Egypt, Arab Rep.: 71.2% of respondents, 0.489 typical gaps (standard deviations)Spain: 32.6% of respondents, 0.983 typical gaps (standard deviations)Estonia: 34% of respondents, 0.841 typical gaps (standard deviations)Ethiopia: 92.2% of respondents, -0.777 typical gaps (standard deviations)Finland: 55% of respondents, 1.02 typical gaps (standard deviations)France: 38.9% of respondents, 0.907 typical gaps (standard deviations)United Kingdom: 36.9% of respondents, 1.19 typical gaps (standard deviations)Georgia: 77.4% of respondents, 0.697 typical gaps (standard deviations)Ghana: 89.3% of respondents, 0.168 typical gaps (standard deviations)Greece: 65.4% of respondents, 1.31 typical gaps (standard deviations)Guatemala: 70.5% of respondents, 0.22 typical gaps (standard deviations)Hong Kong SAR, China: 53.2% of respondents, 1.34 typical gaps (standard deviations)Croatia: 37.2% of respondents, 0.985 typical gaps (standard deviations)Hungary: 40.1% of respondents, 0.83 typical gaps (standard deviations)Indonesia: 98.3% of respondents, 0.591 typical gaps (standard deviations)India: 89.1% of respondents, 0.605 typical gaps (standard deviations)Ireland: 52% of respondents, 1.18 typical gaps (standard deviations)Iran, Islamic Rep.: 78.1% of respondents, 0.667 typical gaps (standard deviations)Iraq: 54.1% of respondents, -0.133 typical gaps (standard deviations)Iceland: 47.3% of respondents, 1.26 typical gaps (standard deviations)Italy: 52.6% of respondents, 0.94 typical gaps (standard deviations)Jordan: 67.3% of respondents, 0.68 typical gaps (standard deviations)Japan: 7.91% of respondents, 1.04 typical gaps (standard deviations)Kazakhstan: 79% of respondents, 0.74 typical gaps (standard deviations)Kenya: 79.4% of respondents, 0.0734 typical gaps (standard deviations)Kyrgyz Republic: 77.6% of respondents, 0.764 typical gaps (standard deviations)Korea, Rep.: 51.7% of respondents, 1.03 typical gaps (standard deviations)Kuwait: 75.9% of respondents, 0.25 typical gaps (standard deviations)Lebanon: 47.1% of respondents, 0.088 typical gaps (standard deviations)Lithuania: 68.1% of respondents, 0.928 typical gaps (standard deviations)Luxembourg: 42.1% of respondents, 0.66 typical gaps (standard deviations)Latvia: 47.9% of respondents, 0.923 typical gaps (standard deviations)Macao SAR, China: 52.8% of respondents, 0.965 typical gaps (standard deviations)Morocco: 65.3% of respondents, 0.345 typical gaps (standard deviations)Moldova: 77.3% of respondents, 0.734 typical gaps (standard deviations)Maldives: 75.6% of respondents, 0.427 typical gaps (standard deviations)Mexico: 61.7% of respondents, 0.636 typical gaps (standard deviations)North Macedonia: 74.4% of respondents, 0.658 typical gaps (standard deviations)Mali: 90% of respondents, -1.24 typical gaps (standard deviations)Malta: 76.3% of respondents, 0.945 typical gaps (standard deviations)Myanmar: 84.1% of respondents, -0.0676 typical gaps (standard deviations)Montenegro: 79.6% of respondents, 0.943 typical gaps (standard deviations)Mongolia: 21.8% of respondents, 0.749 typical gaps (standard deviations)Malaysia: 84.9% of respondents, 0.529 typical gaps (standard deviations)Nigeria: 88.2% of respondents, -0.241 typical gaps (standard deviations)Nicaragua: 67.3% of respondents, 0.168 typical gaps (standard deviations)Netherlands: 22.1% of respondents, 1.27 typical gaps (standard deviations)Norway: 50.2% of respondents, 1 typical gaps (standard deviations)New Zealand: 35.9% of respondents, 1.44 typical gaps (standard deviations)Pakistan: 97.2% of respondents, -0.556 typical gaps (standard deviations)Peru: 60.9% of respondents, 0.773 typical gaps (standard deviations)Philippines: 92.2% of respondents, 0.548 typical gaps (standard deviations)Poland: 55.2% of respondents, 0.952 typical gaps (standard deviations)Puerto Rico (US): 68.2% of respondents, 0.956 typical gaps (standard deviations)Portugal: 59.6% of respondents, 1.02 typical gaps (standard deviations)West Bank and Gaza: 68.1% of respondents, 0.564 typical gaps (standard deviations)Qatar: 86.2% of respondents, 0.734 typical gaps (standard deviations)Romania: 69.3% of respondents, 0.584 typical gaps (standard deviations)Russian Federation: 58.4% of respondents, 0.85 typical gaps (standard deviations)Rwanda: 60.2% of respondents, -0.127 typical gaps (standard deviations)Singapore: 58.3% of respondents, 1.26 typical gaps (standard deviations)Serbia: 55.7% of respondents, 0.761 typical gaps (standard deviations)Slovak Republic: 49.8% of respondents, 0.801 typical gaps (standard deviations)Slovenia: 22.5% of respondents, 1.18 typical gaps (standard deviations)Sweden: 47.4% of respondents, 0.968 typical gaps (standard deviations)Thailand: 69.9% of respondents, 0.764 typical gaps (standard deviations)Tajikistan: 76.4% of respondents, 0.525 typical gaps (standard deviations)Trinidad and Tobago: 65.3% of respondents, 0.581 typical gaps (standard deviations)Tunisia: 48.5% of respondents, 0.496 typical gaps (standard deviations)Turkiye: 70.4% of respondents, 1.03 typical gaps (standard deviations)Ukraine: 65.9% of respondents, 0.784 typical gaps (standard deviations)Uruguay: 37.4% of respondents, 0.9 typical gaps (standard deviations)United States: 53.1% of respondents, 1.11 typical gaps (standard deviations)Uzbekistan: 86.7% of respondents, 0.848 typical gaps (standard deviations)Viet Nam: 89.3% of respondents, 0.537 typical gaps (standard deviations)South Africa: 77% of respondents, 0.665 typical gaps (standard deviations)Zambia: 86.3% of respondents, -0.123 typical gaps (standard deviations)Zimbabwe: 68.3% of respondents, 0.181 typical gaps (standard deviations)CHNETHGRCIDNIRQJPNMLINLDPAKSVNUZB

best-fit line line after adjusting

Four ways to measure the link

MethodrpCountries
Standard (Pearson), not adjusted-0.5625.4e-10104
By rank (Spearman), not adjusted-0.6192.5e-12104
Standard (Pearson), adjusted for national income-0.2070.036104
By rank (Spearman), adjusted for national income-0.2700.006104

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 104 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: +0.355 (a minus sign means it grew).

How solid is it?

Leaving out one country at a time, r ranges from -0.230 (without IRQ) to -0.164 (without QAT). 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: QAT (+0.043).

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 & Pacific15-0.33
Europe & Central Asia48-0.21
Latin America & Caribbean13-0.36
Middle East, North Africa, Afghanistan & Pakistan13-0.22

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 third35-0.11
Middle third34-0.24
Richest third35-0.41

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
Christians61-0.10
Muslims27-0.23

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
Never a European colony15-0.05
Spain12+0.05
United Kingdom24-0.45

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 = -0.262 after dropping 9 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


% of respondents

typical gaps (standard deviations)
Years
Bangladesh BGD99.8%0.3352022, 2024
Indonesia IDN98.3%0.5912022, 2023
Pakistan PAK97.2%-0.5562022, 2024
Ethiopia ETH92.2%-0.7772022, 2023
Philippines PHL92.2%0.5482022, 2024
Mali MLI90%-1.242010, 2023
Viet Nam VNM89.3%0.5372022, 2023
Ghana GHA89.3%0.1682014, 2024
India IND89.1%0.6052022, 2025
Nigeria NGA88.2%-0.2412022, 2023
Uzbekistan UZB86.7%0.8482022, 2025
Zambia ZMB86.3%-0.1232010, 2024
Qatar QAT86.2%0.7342014, 2024
Malaysia MYS84.9%0.5292022, 2024
Myanmar MMR84.1%-0.06762022, 2020

Haerpfer, C. et al., World Values Survey; EVS, European Values Study
uis; undp_hdr; wdi

Sources

Confidence in religious institutions

Share with confidence in churches and religious organisations

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)

"A great deal" or "quite a lot" of confidence, as against "not very much" or "none". Confidence in an institution is not belief in what it teaches. The gap between this and the importance of religion shows how far religious people trust their clergy. No "better" direction is set.

Education score

Education score

PlaceStats · via PlaceStats · Derived work; each member keeps its own licence · updated recomputed with the panel

The average of 10 measures from 3 publishers. Each measure is first put on a common scale: 0 is the average country in an average year, and 1 is a typical gap between countries (a standard deviation). Each is turned so that higher is better. Measures are averaged within each publisher first, so a publisher with many measures does not count for more. Members: Primary completion, Expected schooling, Mean years of schooling, Adult literacy, Pupil-teacher ratio, Primary enrollment, Out of school, primary, Secondary enrollment, Tertiary enrollment, Researchers.

How this was computed

Data used: most recent value in 2010-2025; values come from 2010–2025. 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 7 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 Confidence in religious institutions and Education score

This page shows that two measures go together. It does not show that Confidence in religious institutions changes Education score, or the reverse. These figures also describe countries, not individual people. See the ecological fallacy.

More links with Confidence in religious institutions or Education score