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IQ and Religion

Research & Evidence

IQ and Religion: What the Research Actually Shows

Three meta-analyses agree: higher IQ goes with slightly weaker religious belief, r about -0.14 to -0.17, or four to five IQ points, with heavy overlap. What the numbers mean, what explains them, where they weaken and what they cannot show.

Two almost identical IQ bell curves, one for a more religious group (average 97.9) and one for a less religious group (average 102.1), overlapping by about 89 percent, drawn from a correlation of -0.14.

Yes, but only slightly. Across roughly a century of studies, higher IQ scores go with somewhat weaker religious belief, on average. The most recent large meta-analysis, published in 2022 (89 studies, 201,457 people), puts the correlation at r = −0.14. The figure most often quoted online, −0.24, comes from an earlier 2013 meta-analysis and applies to religious belief in adult samples; across all 63 studies in that review the mean was −0.16. Either way it is a small tendency across groups. It is not a verdict on any believer or non-believer, and it does not show that religion lowers intelligence or that intelligence erodes faith.

  • Direction: negative in most studies — 53 of 63 in the 2013 meta-analysis, 59 of 62 in a 2020 update, and 135 of 192 analysis specifications in 2022, with none significantly positive.
  • Size: small and stable. Three meta-analyses give overall correlations of −0.16, −0.17 and −0.14, which is about 2 to 3% of the differences in IQ, or roughly 4 to 5 IQ points between groups.
  • Weakest links: church attendance and other behaviour, spirituality, and samples younger than college age.
  • Cause: unknown. Several explanations are proposed and none has been shown to be the cause.

This article covers what the meta-analyses found, what the correlation means in IQ points, where the “atheists score six points higher” claim comes from, the main explanations, which variable seems to come first, where the link weakens, why country-level correlations deserve caution, and why nothing here supports ranking religions, or individual people, by IQ.

What do the meta-analyses show?

The first comprehensive quantitative review came from Miron Zuckerman, Jordan Silberman and Judith Hall in Personality and Social Psychology Review (2013). They pooled 63 studies from 52 sources. Fifty-three found a negative correlation between intelligence and religiosity and 10 a positive one. The mean across all studies was −0.16 (median −0.14, weighted mean −0.13). The often-quoted −0.24 is narrower: it is the mean for religious belief in college and adult samples once college scores were corrected for restricted range. The link was weaker for religious behaviour, such as attendance, and weaker below college age, where the best estimate for belief was about −0.08.

Zuckerman and colleagues repeated the exercise in 2020 with 83 studies. The belief correlation in college and adult samples came out at −0.20 to −0.23, and the cleaned 62-study set gave an overall correlation of −0.17 (95% confidence interval −0.20 to −0.14), negative in 59 of the 62. Florian Dürlinger and Jakob Pietschnig then updated the picture in PLOS ONE (2022) with 89 studies covering 105 independent samples and 201,457 participants. Their pooled correlation was −0.14 (95% confidence interval −0.17 to −0.12). They also ran 192 “reasonable” combinations of analysis choices: 135 of them (70.4%) gave a significant negative effect and none gave a significant positive one. The link was stronger when intelligence was measured with a psychometric test than with a proxy such as grade point average, and stronger for belief than for behaviour.

Three meta-analyses of intelligence and religiosity
2013 2020 2022
Authors Zuckerman, Silberman and Hall Zuckerman, Li, Lin and Hall Dürlinger and Pietschnig
Studies 63 83 (62 after cleaning) 89 (105 samples)
Overall correlation −0.16 (weighted −0.13) −0.17 −0.14
Belief in adult samples −0.24 −0.20 to −0.23 —
Negative results 53 of 63 59 of 62 135 of 192 specifications significant; none significantly positive

The overall estimate has barely moved across three reviews, and it is small in every one of them. The larger numbers people quote belong to narrower subsets.

How many IQ points is a correlation of -0.14?

A correlation feels abstract until it is converted into something concrete. Squaring it gives the share of the differences in IQ that religiosity accounts for: r² is about 0.02 at −0.14, or 2%. The other 98% is everything else.

To express it in IQ points, the 2013 authors used the standard conversion Cohen’s d = 2r / √(1 − r²), multiplied by 15, which treats the sample as two groups. For the belief measures that gave 6.2 to 7.8 points, about 7.3 on average, between believers and non-believers. The same conversion applied to the 2022 figure of −0.14 gives d = 0.28, or about 4 IQ points, with the two groups’ IQ distributions overlapping by roughly 89%. Pick one person at random from each group and the less religious person has the higher IQ about 58% of the time, against 50% for a coin flip. These are conversions from reported correlations, not measured group gaps, but they show the scale: a few points on average and very heavy overlap.

Two almost identical IQ bell curves, one for a more religious group (average 97.9) and one for a less religious group (average 102.1), overlapping by about 89 percent, drawn from a correlation of -0.14.
Two almost identical IQ bell curves, one for a more religious group (average 97.9) and one for a less religious group (average 102.1), overlapping by about 89 percent, drawn from a correlation of -0.14.

For comparison, the margin of error on a single good IQ test is itself a few points (see the IQ score margin of error explained), so an average gap of about four points is comparable to the uncertainty in one person’s result. The overlapping curves above are the same normal curve described on the IQ bell curve page.

Where does the "atheists score six points higher" claim come from?

Mostly from one 2009 study. Helmuth Nyborg analysed 3,742 white American teenagers in the National Longitudinal Survey of Youth (NLSY97) and reported that atheists averaged 111.1 on his general-ability estimate, agnostics 109.1, and the denominations he classed as “liberal” and “dogmatic” 107.3 and 105.2. The headline is a gap of 5.89 points between atheists and the “dogmatic” group. Three caveats matter. Only a few dozen atheists were in the sample. The denomination categories were the author’s own, and he noted that they are “highly debatable”. And the study is one teenage cohort in one country. The meta-analyses above, which pool far more people, put the average gap nearer 4 to 5 points on the same conversion.

Why might IQ and religiosity be linked?

Zuckerman and colleagues proposed three interpretations, and later work has added others. Each is a hypothesis about why a correlation exists, and they are not mutually exclusive.

  • Nonconformity. More intelligent people may be less likely to accept a belief simply because their community holds it, and so more likely to resist religious dogma.
  • Analytic thinking. People who stop and reason through a problem, rather than following their first intuition, tend to report weaker religious belief. A 2016 meta-analysis in PLOS ONE (31 studies, 15,078 people) found a correlation of −0.18 between Cognitive Reflection Test performance and religious belief, and the 2020 update found analytic style partly mediated the intelligence link. Both are ability tests, so this may partly restate the same thing.
  • The functions religion serves. Religion can supply a sense of control, self-regulation, self-worth and secure attachment. Intelligence can supply some of the same things, so more intelligent people may have less need for religious belief.
  • Education. Schooling goes with both higher test scores and lower religiosity, but it explains little of the link. Across 15 studies with the relevant data, controlling for education moved the correlation only from −0.20 to −0.18. A 2016 re-analysis by Gregory Webster and Ryan Duffy argued the opposite, and the 2020 update disputed it.

In the 2016 analytic-thinking paper, 133 self-identified atheists scored 18.7% higher than 597 religiously affiliated people on a composite of analytic-thinking measures (Cohen’s d = 0.72), a far larger gap than the IQ correlations imply. That result concerns a thinking style, in small samples, and should not be read as an IQ gap. The wider point that intelligent people still make poor judgments is the subject of why smart people make bad decisions.

Which comes first, intelligence or religiosity?

Correlational data cannot say, and the 2013 authors were explicit about that. Two sets of results are, however, consistent with intelligence coming first. In four studies that measured intelligence 3 to 25 years before religiosity, the mean correlation was about −0.12. And the roughly 1,528 gifted children Lewis Terman selected in the 1920s, generally with IQs above 135 (see what an IQ of 135 means), grew up less religious than the general public in all four comparisons the 2013 authors could make, even though around 60% reported strict or considerable religious training as children.

The evidence is not one-directional, though. In the Lothian Birth Cohort 1921, a Scottish group tested at age 11 in 1932 and followed into their nineties, intelligence at age 11 was unrelated to religiosity at 83; only later-life intelligence correlated with religious belief. Neither belief nor attendance predicted cognitive change from age 11 to old age, or across the ninth decade of life. In that cohort religion neither protected nor harmed mental ability over time (Ritchie, Gow and Deary, Intelligence, 2014). The sociologist Darren Sherkat even proposed the reverse arrow for conservative Christian fundamentalism: by discouraging secular schooling and outside information, it may hold verbal ability back.

Where does the link get weaker or disappear?

Belief is not behaviour. In the Scottish cohort, religious belief was negatively related to intelligence but church attendance was not. A 2026 study in Frontiers in Psychology using two large US cohorts (NLSY79, N = 12,686; NLSY97, N = 8,984) found the same split within denominations in the NLSY97 data: among Catholics the correlation with belief was −0.09 but with religious behaviour +0.04, and among Protestants −0.06 and 0.00. Going to services for community, family or habit is a different thing from what a belief scale measures.

Spirituality is not religiosity. A 2024 analysis of the General Social Survey’s ten-word vocabulary test, a short measure of crystallised ability rather than a full IQ test (35,093 respondents across 14 cohorts spanning 1988 to 2022), found that religiosity correlated −0.13 with the score, while spirituality correlated +0.03, which is effectively nothing.

Younger samples. Both the 2013 and 2020 reviews found the link weaker below college age, at about −0.07 to −0.08.

Re-analyses disagree. Webster and Duffy re-analysed the 2013 data and argued that the negative link appeared only in samples of women and only in studies dated before 2010. The 2020 update and the 2022 meta-analysis, both with more studies, did not find those patterns to be robust. Two careful groups reaching different conclusions from overlapping literatures is a reason for humility about how stable the link is in recent samples.

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Why do country-level correlations deserve caution?

The most quoted single figure is from a 2009 paper by Richard Lynn, John Harvey and Helmuth Nyborg: across 137 nations, the correlation between national IQ estimates and the share of people disbelieving in God was 0.60. Look at their own table, though. Among the 69 countries with national IQs of 64 to 86 the correlation was 0.16, and among the 68 with IQs of 87 to 108 it was 0.54. The United States is itself an outlier, with unusually low disbelief for a high-IQ country. National IQ figures rest on small, uneven samples and on tests designed in Western countries, which is why country IQ rankings cannot bear much weight and why average IQ by country figures need heavy caveats. A correlation between countries also says nothing about individuals inside them, and wealth, schooling and life expectancy move with both variables. Webster and Duffy reported that the link became non-significant once they controlled for spatial dependence, the fact that neighbouring countries resemble each other.

Can you rank religions by IQ?

No dataset supports it. Nyborg’s teenage sample produced denominational averages, but the groups were small (some a few dozen respondents), the spread inside each was 10 to 15 points, and his own analysis found that denomination explained almost none of the variation in IQ (R² of about 0.001). Even the 2026 analysis of two large national cohorts could not compare Jewish or Muslim participants because there were too few of them. The meta-analyses above concern how strongly individuals hold religious belief, not which religion they hold, so they say nothing about traditions. The same discipline applies to any identity group; see IQ and political party for how survey comparisons of that kind should be read, and cultural bias in IQ tests for why the test itself can favour some backgrounds.

What can this research not tell you?

  • Anything about one person. An r of −0.14 leaves 98% of the variation unexplained. Every belief group, and every non-belief group, contains people at every IQ level, including the roughly one person in a hundred who scores 135 or higher and people well below average.
  • Which way the arrow points. Schooling, family background and country move with both variables, and schooling itself changes test scores. Education-level patterns are covered in average IQ by education level.
  • Anything about wisdom, ethics or wellbeing. IQ tests sample reasoning tasks. They do not measure kindness, meaning or judgment.

Quick answers

Are atheists smarter than religious people?

On average, non-believers score a few IQ points higher in most studies, with almost complete overlap between the groups. That is a statistical tendency across large samples, not a statement about any one person.

Does religion lower IQ?

There is no good evidence that it does. In one long-running cohort, neither religious belief nor attendance predicted cognitive change from childhood to old age. The correlation describes who holds which beliefs, not a cognitive cost of holding them.

What is the average IQ of religious people?

No single figure exists. Studies report correlations and group differences on different tests, and religious people are not one group. The best summary is the meta-analytic correlation: small, negative, and mainly about the strength of belief.

Is IQ linked to spirituality?

Not meaningfully. In a 2024 analysis of 35,093 US respondents spirituality correlated +0.03 with a vocabulary-test score, against −0.13 for religiosity.

Is the link the same in every country and religion?

Unknown. Most of the individual-level evidence comes from Western, largely US samples, and most IQ tests were developed in Western cultures, so the pattern is best documented for the groups studied most.

The bottom line

Higher IQ scores go with slightly weaker religious belief across large samples. The best current estimate is about −0.14 to −0.17, roughly four to five IQ points between groups, with heavy overlap. The link is strongest for belief rather than behaviour, absent for spirituality, weaker in the young, contested in some re-analyses, and not evidence that religion harms thinking or that intelligence removes faith. It is a small fact about populations and a poor guide to any individual.

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Tagged analytic thinking, atheism, cognitive ability, confounding variables, correlation vs causation, effect size, intelligence research, IQ and religion, IQ Science, longitudinal study, meta-analysis, religion and intelligence, religiosity, research and evidence

IQ and Testosterone

Research & Evidence

IQ and Testosterone: Does the Correlation Chart Hold Up?

A popular online chart claims a clean link between testosterone and IQ. Real studies disagree with each other on direction and size, and the most rigorous test found no effect at all. What the actual research says, and why the meme persists.

Four cards comparing testosterone and cognition findings across studies: no correlation in 8 year old boys, positive at age 10, negative at age 12, and no association with memory in older men in a Mendelian randomization study.

No — not a consistent one, in either direction. A chart claiming a clean relationship between testosterone and IQ circulates widely online, but real studies measuring both disagree with each other on direction, size, and even which way the correlation points, and the most rigorous test of the idea — a study designed specifically to get at cause and effect rather than mere correlation — found no relationship at all. This article covers what actual studies have found, why the results keep contradicting each other, and why the popular chart is not backed by the research it claims to summarize.

Where the "IQ and testosterone chart" comes from

Search interest in “iq and testosterone chart” and “iq and testosterone chart meme” is real and substantial, which tells you something on its own: the chart is a social-media object first and a scientific claim a distant second. Versions of it typically carry no citation at all, or misread a single study far beyond what it actually found. The appeal is obvious — a simple story about two traits people already have strong intuitions about — and that is exactly the kind of claim worth checking against the underlying research rather than the picture.

What real studies actually find

One informative study followed the same group of boys at ages 8, 10 and 12, measuring salivary testosterone and fluid intelligence at each age. At 8, there was no significant correlation at all. By 10, a positive correlation had appeared. By 12, in the same children, the correlation had flipped negative. A relationship that changes sign three times in the same group of people over four years is not a relationship a single chart can honestly summarize with one arrow.

Four cards comparing testosterone and cognition findings across studies: no correlation in 8 year old boys, positive at age 10, negative at age 12, and no association with memory in older men in a Mendelian randomization study.
Four cards comparing testosterone and cognition findings across studies: no correlation in 8 year old boys, positive at age 10, negative at age 12, and no association with memory in older men in a Mendelian randomization study.

That kind of instability is itself the finding. If testosterone straightforwardly raised or lowered cognitive ability, the direction should not reverse twice in the same cohort as puberty progresses. What actually seems to be happening is that both testosterone and cognitive development are moving on their own timelines during this period, and any correlation that shows up at one snapshot in time is easy to mistake for a stable underlying relationship that is not really there.

Why anyone expected a link in the first place

The hypothesis is not baseless. Androgen receptors, the proteins testosterone binds to in order to affect cells, are present in brain regions tied to memory and spatial processing, including the hippocampus and areas of the prefrontal cortex, and animal research has linked testosterone to effects on neurogenesis, the growth of new neurons. That gives the idea real biological plausibility — a mechanism worth testing — which is different from evidence that the effect actually shows up reliably, at a meaningful size, in human cognitive test scores. Plenty of biologically plausible mechanisms fail to produce a detectable real-world effect once they are actually measured, and this appears to be one of them — a different outcome than the much better-supported evidence for a genetic contribution to IQ, which rests on a far larger and more consistent body of twin and family research than anything testosterone has produced.

Measurement noise makes the search harder than it looks. Testosterone is not a fixed trait like height; it follows a strong daily rhythm, typically highest in the morning and declining through the day, is released in pulses rather than at a steady level, and can spike temporarily with stress, competition or even a single interaction. A one-time blood or saliva sample is a noisy snapshot of a moving target, and comparing that snapshot against a single test score taken on a different occasion adds a second layer of noise on top of the first. Some of the disagreement between studies is a real biological story; some of it is almost certainly this.

The curvilinear theory

Some research on adults has proposed a curvilinear, inverted-U pattern instead of a straight line: moderate testosterone levels associated with the best fluid-intelligence performance, with both unusually low and unusually high levels associated with somewhat worse scores. Fluid vs. crystallized intelligence explains what fluid intelligence specifically measures — on-the-spot reasoning rather than accumulated knowledge, which is the ability most of these studies actually test. Even the curvilinear pattern is not consistent across every study, and it appears to depend on age, sex and how testosterone is measured, which is a more honest, and much less shareable, story than a single chart.

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The strongest test we have says: nothing

The most methodologically convincing study on this question used Mendelian randomization in older men: rather than simply comparing testosterone levels and cognitive scores at one point in time, which cannot separate cause from effect or rule out some third factor driving both, researchers used genetic variants known to predict testosterone levels, which are assigned effectively at random at conception. That design mimics the logic of a randomized trial and largely removes reverse causation from consideration. The result: genetically predicted testosterone showed no association with delayed word-recall scores or Mini-Mental State Examination scores. When the method best suited to detecting a causal effect finds nothing, that carries more weight than another simple correlation would, in either direction.

Why prenatal exposure is a different question entirely

A separate and more active research area looks at prenatal testosterone exposure, often estimated using the ratio between the length of the second and fourth fingers, and its relationship to spatial ability specifically, not general intelligence. That research strand asks a genuinely different question — what happened during fetal development, not what someone’s hormone level measures today — and conflating the two is a common way this topic gets muddled online. A finding about prenatal exposure and spatial skill is not evidence about whether an adult with higher testosterone right now has a higher IQ.

The best-known version of this separate research strand is Simon Baron-Cohen’s “extreme male brain” theory of autism, which proposes that elevated prenatal testosterone exposure shifts cognitive style toward systemizing over empathizing. It remains a debated theory rather than settled fact within autism research, and it is worth naming here specifically because it sits right next to this topic and gets folded into it constantly online, even though it is about neurodevelopmental style and a specific diagnosis, not about IQ as this article is discussing it.

Sex differences complicate the picture further, in a way the broader research on IQ and sex differences runs into constantly. Circulating testosterone levels differ by roughly an order of magnitude between adult men and women, so a study population that is all-male, all-female, or mixed is effectively asking a different question each time, and the studies summarized above span all three designs. A correlation measured within the male range, where testosterone varies across a comparatively narrow band, is not automatically comparable to one measured across the much wider combined range, which is one more reason a single chart cannot honestly compress this literature into one line.

One counter-intuitive finding worth knowing

A study of prepubertal children found that boys of average intelligence actually had significantly higher testosterone levels than both intellectually gifted boys and boys with intellectual disability — the opposite of a simple “more testosterone, more IQ” pattern, and a useful reminder that a single study can cut against the popular narrative just as easily as it can support one. It should be read with the same caution as every other single study here: one sample, one age group, not a settled fact.

Why the meme persists anyway

A chart with a clean line is more shareable than a paragraph explaining that the real answer depends on age, sex, measurement method and study design. That gap between what spreads easily and what the evidence actually supports is not unique to this topic; average IQ by college major is a useful contrast — a genuinely stable, replicated finding that happens to be less dramatic than a meme, which may be exactly why it circulates less.

The bottom line

No study reviewed here supports a simple, stable link between testosterone and IQ in either direction. The correlation flips sign across childhood in the same children, adult findings depend heavily on age and sex, and the single most rigorous causal test available found no effect at all. The popular chart is describing a relationship the research does not actually show.

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Tagged biological factors, cognitive ability, correlation vs causation, fluid intelligence, gender differences, hormones, IQ Science, myths and misconceptions, prenatal development, research and evidence, testosterone

High IQ and Mental Health

Understanding IQ

High IQ and Mental Health: What the Research Actually Shows

A widely cited 2018 study found sharply higher rates of anxiety and depression among members of a high-IQ society. Why that finding is far from the whole story, what a century of gifted research actually shows, and what seems to matter more than IQ itself.

Bar chart comparing self-reported anxiety and mood disorder diagnosis rates between the general population, about 10 percent each, and a 2018 survey of 3,715 members of a high IQ society, about 20 percent anxiety and 27 percent mood disorder.

The evidence is genuinely mixed, and both sides of the debate can point to a real study. The finding that gets shared the most — sharply higher rates of anxiety and depression among members of a high-IQ society — comes from one widely cited 2018 survey with real limitations. A much larger and older body of research on gifted people, running for decades, found close to the opposite: that gifted children and adults were, on average, at least as well-adjusted as everyone else. This article covers both bodies of evidence, why they disagree, what a much older stereotype gets wrong, and what seems to matter more than the IQ number itself.

The idea that intelligence and mental fragility travel together is far older than any of this research, and the popular link between IQ and creativity carries a version of the same stereotype. Aristotle is often paraphrased as observing that eminent philosophers, poets and artists tend toward melancholy, and the Romantic era built an entire aesthetic around the tortured genius. The stereotype hardened into something resembling a scientific claim with the Italian criminologist Cesare Lombroso, whose 1889 book “The Man of Genius” argued that genius was itself a form of hereditary degeneration related to insanity — a theory taken seriously in its own time and thoroughly discredited since. Modern research did not invent the “sad genius” idea; it inherited a stereotype that predates any actual data on the question by more than a century, which is worth knowing before treating either side of the current debate as the first word on the subject.

The study behind the headlines

Psychologist Ruth Karpinski and colleagues at Pitzer College surveyed 3,715 members of American Mensa, whose entry requirement sits around the 98th percentile on a standard IQ test, roughly 132 or higher. Published in the journal Intelligence in 2018, the survey found that about 20% of respondents reported having been diagnosed with an anxiety disorder, and nearly 27% reported a mood disorder such as major depression or bipolar disorder — against typical general-population estimates of roughly 10% for each. The researchers proposed a “hyper brain, hyper body” explanation: heightened psychological and physiological reactivity to stimuli, sometimes called overexcitability, that produces more intense rumination and worry alongside a higher measured rate of physical conditions like allergies, asthma and autoimmune disease in the same sample. The “hyper body” half of that name is doing real work — the survey’s central claim is not just about mood, it is that the same heightened nervous-system reactivity shows up in both the mind and the immune system at once.

Bar chart comparing self-reported anxiety and mood disorder diagnosis rates between the general population, about 10 percent each, and a 2018 survey of 3,715 members of a high IQ society, about 20 percent anxiety and 27 percent mood disorder.
Bar chart comparing self-reported anxiety and mood disorder diagnosis rates between the general population, about 10 percent each, and a 2018 survey of 3,715 members of a high IQ society, about 20 percent anxiety and 27 percent mood disorder.

Why one study should not settle the question

The sample was self-selected twice over: people who sought out membership in a high-IQ society in the first place, then volunteered to answer an online survey about their health. Every diagnosis was self-reported rather than clinically verified, which opens the door to recall and disclosure differences. And the general-population comparison numbers came from separate sources using different methodologies, not a matched control group given the identical instrument — a design that can widen or narrow an apparent gap for reasons that have nothing to do with intelligence itself, including how comfortable a highly educated, self-selected group is with reporting a mental-health diagnosis in the first place.

The older, larger, more optimistic picture

Long before this survey, Lewis Terman’s “Genetic Studies of Genius” — a longitudinal study that began following gifted California children in 1921 and continued tracking many of them for the rest of their lives — found gifted children to be, on average, physically healthier and at least as socially and emotionally well-adjusted as their peers, directly contradicting the popular “sad genius” stereotype. That study has its own limits: a sample drawn overwhelmingly from white, middle-class children in one state, assessed with the diagnostic categories and social norms of the 1920s through 1950s. Neither study is the final word; each was built to answer the question in a different, imperfect way.

What later research on gifted adults adds

The Study of Mathematically Precocious Youth, running continuously since 1971, has tracked profoundly gifted people into midlife and generally found life satisfaction and psychological well-being comparable to or better than the general population on average. The same body of research also documents real, specific challenges for profoundly gifted children in particular — asynchronous development, where a child’s intellectual, emotional and physical development advance at different rates, and social mismatch with same-age peers who do not share their interests. A ten-year-old reading at a college level but still navigating a ten-year-old’s friendships and emotional regulation is the practical shape this takes, and it is a real source of strain even though it is not the same claim as elevated adult rates of diagnosed anxiety or depression.

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Overexcitability: an interesting theory, not a settled fact

The framework behind the “hyper brain, hyper body” idea traces back to Kazimierz Dabrowski’s Theory of Positive Disintegration, popular in gifted-education circles for decades. Dabrowski described five domains of overexcitability — psychomotor, sensual, intellectual, imaginational and emotional — and proposed that gifted individuals experience several of them more intensely than average, with the resulting inner turmoil framed as a necessary stage on the way to a more advanced personality, not simply a deficit. It is a genuinely interesting lens, and it is also a theory with limited independent empirical validation outside the research groups that developed it, which is a different status than an established, broadly replicated finding.

A separate honesty check worth naming: the Mensa sample sits at the extreme tail of the distribution, roughly the 98th percentile and above. Nothing about that survey speaks to whether someone with an above-average but non-extreme score — say, 115 or 120 — carries any elevated risk at all. If the “hyper brain, hyper body” pattern is real, the current evidence does not show whether it appears gradually across the range or only shows up near the far tail that this specific sample was drawn from.

What seems to matter more than the number itself

Across both bodies of research, the environmental details show up more consistently than intelligence itself as a driver of outcomes: social isolation from same-age peers, boredom in a school setting that is not matched to a child’s pace, and simply being treated as strange for thinking differently. Signs of a gifted child covers identification in more depth, and the twice-exceptional overlap covered in high IQ and ADHD shares the same underlying thread: giftedness does not automatically come with better self-regulation or emotional coping, and IQ and emotional intelligence are measuring genuinely separate skills that develop on separate tracks.

As with other striking single-study claims about high-IQ populations — see IQ and testosterone for a similar case — a dramatic finding from one sample is not the same thing as a settled scientific consensus, and the honest version of this story is messier and less quotable than either headline.

If you are actually concerned about this

It is worth separating this from test anxiety, a narrower and more solidly established phenomenon: nervousness during the test itself, which can lower a score, rather than a general claim about mood or anxiety disorders in daily life. A high or low score on a cognitive test is not a mental-health diagnosis in either direction. Genuine, persistent anxiety or low mood is worth raising with a real clinician regardless of where anyone falls on any test, and a self-administered online quiz result is not a substitute for that conversation in either direction.

The bottom line

One striking survey found a wide gap; a much larger, older research tradition found close to none. Both have real limitations, the theory offered to explain the gap is more provisional than it sounds in a headline, and the factors that show up most consistently across the research — isolation, mismatch, being misunderstood — point more toward environment and social fit than toward intelligence itself as the thing driving mental health.

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Average IQ by College Major

Research & Evidence

Average IQ by College Major: What 70 Years of Data Actually Show

Average test scores really do differ by college major, and the rank order has barely moved in 70 years. What a landmark cross-dataset analysis found, why SAT and GRE scores are not IQ scores, and what the ranking cannot tell you about one student.

Bar chart ranking average standardized test scores by college major across five US datasets from 1946 to 2014, with engineering, physical sciences and math or computer science highest and education lowest.

Yes, on average — and the gap has held remarkably steady for decades. Students who go on to major in engineering, the physical sciences, or math and computer science score higher, on average, on the standardized tests researchers have studied than students heading into fields like business or education, and that basic ranking has barely moved since researchers first started tracking it in 1946. This article covers what the research actually measured, what the ranking looks like, why it has stayed so stable, and — just as important — what a group average like this cannot tell you about any individual student, including the one reading this article about their own major.

What the research actually measured

The most thorough version of this analysis comes from psychologist Jonathan Wai, who lined up five different measures of American students’ academic aptitude spanning 1946 to 2014 and compared them by intended field of study. The datasets include Project Talent, a stratified sample of roughly 400,000 American high school students tested in the early 1970s, and more than 1.2 million people who took the Graduate Record Examination between 2002 and 2005 and reported an intended graduate major, alongside SAT data. None of this is a single study of a single year; it is a comparison across independent samples, tests and generations.

One caveat belongs up front: “intended major” is not the same as “final degree.” Students switch fields, and a first-year plan is not a guarantee. The analysis captures where students stood when they declared an interest, not a lifetime outcome.

The ranking

  • Engineering and the physical sciences (physics, chemistry, earth science) rank highest across every dataset Wai examined, a position they have held since the earliest data in 1946.
  • Math and computer science follow close behind, with the biological sciences not far after that.
  • The humanities and social sciences occupy the middle of the field, scoring above most of the remaining majors but well behind the top group.
  • Business and education post the lowest average scores among the nine broad fields in the analysis.

The gap between the top and bottom of that list is real but should not be overstated: these are group averages built from broad fields that each contain enormous internal variation, not a precise scoring ladder where every engineering student outscores every education student.

One reason business and education sit at the bottom is not just about ability — it is partly arithmetic. Fields like physics and engineering draw a smaller, more self-selected pool of students who already committed to a demanding quantitative track well before declaring a major. Business and education are among the largest, most broadly accessible majors in the country, drawing a wider cross section of every incoming class. A more selective, smaller pool sitting further out in the distribution will almost always show a higher average than a large, open one, independent of any difference in how demanding the coursework itself turns out to be later on.

Bar chart ranking average standardized test scores by college major across five US datasets from 1946 to 2014, with engineering, physical sciences and math or computer science highest and education lowest.
Bar chart ranking average standardized test scores by college major across five US datasets from 1946 to 2014, with engineering, physical sciences and math or computer science highest and education lowest.

Why the order has barely moved in 70 years

What makes this finding worth taking seriously is not any single number but the stability: the same rough ranking shows up in a 1970s high-school sample, in SAT data, and in GRE data collected decades later, across a period when college attendance, the applicant pool, and the tests themselves all changed substantially. A pattern that survives that much churn in the underlying population is more likely to reflect something structural about how students sort themselves into fields than an artifact of any one test or one generation.

It is not one kind of ability doing all the work

“Smarter” is not a single dial, and the majors at the top of this ranking are not uniformly ahead on every kind of ability. Much of what separates STEM fields specifically from the rest of the ranking is concentrated in quantitative and spatial reasoning rather than verbal ability, which is spread far more evenly across majors. Verbal vs. non-verbal IQ scores covers that distinction directly: a student with outstanding verbal reasoning and average quantitative reasoning can post a perfectly strong composite score while still looking unremarkable on the specific subscore this ranking is really tracking.

This also means the same overall composite number can hide very different profiles. Two students with identical total scores can arrive at them in very different ways — one carried mostly by verbal reasoning, the other by quantitative and spatial reasoning — and a ranking built from composite or subject-specific test scores by major is really describing the second kind of ability more than the first.

Your own number

Where would your own score land?

Take the IIF-certified assessment and get your score with the scale it was measured on, the percentile it corresponds to and the confidence range around it — the three figures most online tests leave out.

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SAT and GRE scores are not IQ scores

It matters that none of this comes from an IQ test. SAT score to IQ conversion covers the relationship in detail: research correlating the SAT with general cognitive ability has found a strong relationship, on the order of 0.8 once statistical corrections for range restriction are applied, but “strongly correlated” is not “identical.” An admissions test is built, timed and scored for a different purpose than a clinical IQ test, and converting one into the other always adds a layer of approximation that a “your major means your IQ is X” headline tends to erase.

Self-selection, not causation

Nothing about this ranking shows that choosing engineering raises a score, or that choosing education lowers one. Students sort into majors well before they finish a degree, partly on the basis of ability and preparation they already had going in — a pattern that is self-selection, not something the major itself causes. Does school raise IQ and Does IQ predict school success both cover pieces of the mechanism this ranking depends on without directly showing it.

One concrete mechanism behind that self-selection: choosing an engineering or physical-science major in college is downstream of choosing calculus and physics in high school, and access to that coursework is not distributed evenly. A student who never had a school offering a calculus track is far less likely to arrive at college even considering a major that assumes it, regardless of their underlying ability. The major-level ranking partly reflects years of unevenly distributed opportunity to prepare for exactly the kind of quantitative reasoning these tests measure, compounded well before anyone sits the SAT or the GRE.

Access and preparation are part of the story too. Socioeconomic status and IQ and stereotype threat in test-taking both cover factors that shape who arrives at a selective major already well-prepared for a standardized test, well before any question of raw ability comes into it. Wai’s data also shows differences in which fields men and women disproportionately choose; IQ tests and gender differences is a better starting point for that separate and more contested question than this article.

What this ranking does not tell you

The variation within any one major dwarfs the gap between majors. Plenty of education majors outscore plenty of engineering majors on any given test; the distributions overlap heavily, and only the averages pull apart. A ranking like this describes a large group compared with other large groups — it says nothing reliable about any one student’s ability, potential, or how they will actually perform once they are in a program.

How this compares to average IQ by occupation

Average IQ by occupation covers a related but distinct question: where people end up working, often years after graduation and shaped by factors well beyond a college major. A major chosen at eighteen and a career entered at thirty are not the same measurement, even though the two rankings tend to rhyme.

The bottom line

Average IQ by college major belongs to a long list of variables people search for a link to intelligence. Not all of them hold up the same way once real data is examined; IQ and testosterone is a good example of one that does not. This one does have real, replicated data behind it — a consistent rank order across 70 years and multiple independent tests — which makes it worth taking seriously as a description of groups, and exactly as useless as any other group average for judging one person.

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Tagged academic aptitude, average IQ, career and iq, cognitive ability, college major, education and iq, GRE score, IQ Science, research and evidence, SAT score, standardized testing, STEM

Can Your IQ Be Zero?

Scores & Scales

Can You Have an IQ of 0? Why Zero and Negative IQ Scores Do Not Exist

Mathematically, the IQ scale has no floor built in – but no test has ever reported a zero. Where the deviation IQ scale actually stops working, why real tests bottom out around 40, and what a score that low would even require.

Three cards showing where 100 the average, about 40 a real test's practical floor, and 0 sit on the same deviation IQ scale, with zero about 6.7 standard deviations below the mean.

No. Nobody has an IQ of 0, and no test can print one. The main adult tests report Full Scale IQs from 40 to 160, so even a person who gets every item wrong is scored at the floor, not at zero. On the deviation scale, a score of 0 would sit 6.7 standard deviations below the average of 100, about 1 person in 76 billion, which is more than nine times the number of people alive. The phrase “IQ below zero” is internet shorthand, not a score.

  • Lowest reported score: about 40 on the WAIS-IV and the Stanford-Binet 5 (a range of 40 to 160).
  • Why not zero: the scale is built around the middle of the population; at 0 there is no group left to compare against.
  • Negative IQ: a formula can print one (below z = −6.67), but it describes no person and no test result.
  • Very low scores in practice: clinicians use adaptive-behaviour measures and age-equivalent scores, not an IQ number, where a test hits its floor.

Mathematically, yes: the deviation IQ scale used by every major test today has no built-in floor, and the arithmetic behind it continues cleanly through zero and into negative numbers. In practice, no test has ever reported a score of zero, and no real test ever will. This article covers how the scale is actually built, where real testing stops working long before it gets anywhere near zero, what a score that low would actually require of a person, and how clinical practice handles the small number of people whose ability genuinely cannot be captured in a single number at all.

That gap between the math and the reality is not a flaw in the test. A ruler with a foot of usable markings can still, in principle, describe a distance of ten miles — the formula never stops working, but nothing anyone would actually measure with it gets anywhere close.

How the modern IQ scale is actually built

Every mainstream test in current use — the Wechsler scales, the Stanford-Binet 5 — reports what is called deviation IQ: a score built around a mean of 100 with a standard deviation of 15 (some scales use 16). How IQ is scored by age covers the mechanics in full, but the short version is that a deviation IQ score is really a statement about rarity relative to same-age peers, not a raw count of correct answers. Scoring 115 does not mean answering 15% more questions right; it means scoring higher than roughly 84% of people the same age who took the same test.

This is a relatively modern convention. Early twentieth-century testing used ratio IQ instead: mental age divided by chronological age, multiplied by 100. Deviation IQ vs. ratio IQ explains why psychologists abandoned that formula, but it matters directly here: under the old arithmetic, a very low score genuinely was reachable. A ten-year-old assessed at a one-year mental age computed to a ratio IQ of 10, mechanically, no special case required. Deviation IQ does not work that way at all, which is a real part of why zero does not come up today even in principle for anyone who can be meaningfully tested.

Why zero is "on" the scale but never reached

Zero sits 100 points below the mean, which on a standard deviation of 15 works out to about 6.7 standard deviations below average. To see how fast that escalates: about 68% of people fall within 1 standard deviation of the mean (85 to 115), about 95% fall within 2 (70 to 130), and about 99.7% fall within 3 (55 to 145). Each additional standard deviation past that point does not shrink the remaining share by a little; it shrinks it by orders of magnitude. By roughly 6.7 standard deviations out, the normal-curve model treats the remaining share as rarer than one person in the entire population that has ever lived, let alone the few thousand people in any single test’s norming sample. Long before a real distribution gets anywhere near that far out, the bell-curve approximation has already stopped describing anything real. There is no group of people zero could be measured against, because no such group exists to be rare within.

How rare would an IQ of 40, 25, 10 or 0 be?

Normal-curve arithmetic shows how fast the numbers fall away at the bottom of the scale. A score of 70 is about 1 in 44; by 40, a score the main tests treat as their floor, it is already about 1 in 31,600, and below 10 it is rarer than one person in a billion. A zero is 1 in 76.4 billion on a standard deviation 15 scale. The real distribution at the bottom is not a smooth normal curve (many causes of very low ability are medical, not statistical), so the table is a model of the formula, not a head count.

How rare low scores would be on the standard deviation 15 scale (normal-curve arithmetic)
IQ score z score About 1 person in
70 -2.00 1 in 44
55 -3.00 1 in 741
40 -4.00 1 in 31,600
25 -5.00 1 in 3,490,000
10 -6.00 1 in 1,010,000,000
0 -6.67 1 in 76,400,000,000

The mirror image sits at the top of the scale: an IQ of 160 is also 4 standard deviations from the mean, and the highest IQ ever recorded shows where tests stop being able to tell scores apart in that direction. For the middle of the low range, see what an IQ of 70 means and what an IQ of 65 means.

Does IQ even have a "true zero"?

This is a different, more technical question than whether a zero score has ever been recorded, and it has a clean answer: no. Measurement theory distinguishes an interval scale, where equal gaps mean the same thing at any point but zero is arbitrary, from a ratio scale, where zero means a true absence of the thing being measured. Temperature in Celsius is an interval scale — 0°C is not “no temperature,” it is just where water freezes — while weight is a ratio scale, where 0 kg really does mean no mass. Deviation IQ is built as an interval scale. It supports statements like “115 is 15 points above 100,” but it was never built to support a statement like “an IQ of 150 is twice as smart as an IQ of 75,” because doubling and halving are ratio-scale ideas that do not carry over. Even in the hypothetical world where a test could reach all the way down to 0, that score would not mean “zero intelligence” any more than 0°C means zero heat — the scale simply is not built to make that kind of claim in the first place.

That also covers the colloquial use of the phrase, which shows up constantly online as an insult — “their IQ is zero,” “IQ below zero.” As internet shorthand for “acting foolishly,” it is harmless hyperbole. As a literal claim about a measured score, it is not just false in practice, as this article covers throughout; it is not really a coherent claim on this kind of scale to begin with.

Can an IQ be negative?

On paper, yes, and in practice never. A deviation IQ is 100 plus 15 times a z score, so any z score below −6.67 would give a negative number, and the arithmetic does not stop at zero. What stops is the data: no standardisation sample contains anyone that far out, and a test that cannot score a 10 certainly cannot score a −10. The old ratio IQ cannot go negative at all, because mental age divided by age is never below zero; the lowest ratio score is a mental age of zero, which means no measurable test performance at all.

Where a real test actually stops measuring

Most standardized tests can reliably measure down to somewhere in the neighborhood of 40, depending on the specific instrument and its norming sample; scores below roughly 20 to 25 are generally treated as unreliable regardless of test. This is a floor effect: once someone is missing nearly every item on the easiest end of a test, the instrument can no longer tell a true score of 35 apart from a true score of 15, because too few people in the norming sample ever scored that low for the statistics to be trustworthy. Researchers have specifically studied how to compute meaningful index scores for children who “floor” the WISC-IV in this way, precisely because the standard scoring tables simply run out.

Three cards showing where 100 the average, about 40 a real test's practical floor, and 0 sit on the same deviation IQ scale, with zero about 6.7 standard deviations below the mean.
Three cards showing where 100 the average, about 40 a real test’s practical floor, and 0 sit on the same deviation IQ scale, with zero about 6.7 standard deviations below the mean.

When a test hits this wall, a competent report does not print a guess. It reports a ceiling on the estimate instead — something like “below 40” — rather than pretending to distinguish one very low score from another with a precision the data cannot support. How to read an IQ test report covers what a real report actually contains, which is always a range and a set of index scores, never a single bare number standing in for a person’s whole ability.

Your own number

Where would your own score land?

Take the IIF-certified assessment and get your score with the scale it was measured on, the percentile it corresponds to and the confidence range around it — the three figures most online tests leave out.

Find your IQ score now! →

Secure & encryptedInstant results10–20 minutes

What is the lowest IQ a test can report?

Most major tests print a floor of about 40. The WAIS-IV reports Full Scale IQs from 40 to 160, built from ten core subtests whose scaled scores run from 1 to 19, so a person who scores the minimum on every subtest still receives the lowest composite, not a zero. Clinical systems go below that only in words. The World Health Organization’s ICD-10 describes profound mental retardation (its term) as an IQ under 20, which in adults it equates to a mental age below 3 years, and the DSM-5-TR dropped IQ bands altogether, grading severity by adaptive functioning instead. IQ and mental age sets the ICD-10 bands out in full, and low IQ versus learning disability explains why a score and a diagnosis are different things.

What a score that low would actually require

Getting close to a test’s floor means missing nearly every item written for the easiest end of the norming sample — typically material aimed at very young children on an adult-normed test. Below that point, the practical problem stops being about reasoning ability at all. Sitting through a timed, instructed, standardized assessment requires baseline attention, motor coordination and communication just to produce a response in the first place. Someone whose impairment is severe enough to theoretically approach a near-zero score is, in the overwhelming majority of cases, someone for whom those basic prerequisites cannot be assumed either — which means the instrument cannot separate “very low reasoning ability” from “unable to engage with this particular kind of task” at all.

For research purposes, specialists sometimes work with extended or extrapolated norms that project a curve mathematically below a test’s actual floor, the same way extended norms exist above a test’s ceiling for profoundly gifted children. Those extrapolated numbers are useful for research comparisons across studies, but nobody treats them as a directly observed score in the way a report hands a family a number like 92. They are a modeling tool, built on the assumption that the same statistical pattern continues past the point where it was ever actually observed — which is exactly the assumption that stops being trustworthy the further out it is pushed.

How very low ability is actually assessed today

Clinical practice has moved well past the idea of a single IQ cutoff for this reason. The DSM-5 and the American Association on Intellectual and Developmental Disabilities both define the severity of intellectual disability primarily through adaptive functioning — conceptual, social and practical skills for daily life — with a test score treated as supporting evidence rather than the sole basis for a diagnosis. That shift happened specifically because a bare number was never an adequate description on its own, at either end of the scale but especially at the low end, where the measurement itself becomes least trustworthy exactly where the stakes for getting it right are highest.

The high end runs into the identical problem, in reverse

The ceiling effect is the mirror image of everything above: every test also has a highest score it can report, set by how many people in its norming sample answered every item correctly, and claims that outrun it deserve the same scrutiny. The highest IQ ever recorded covers what happens when a headline number tries to describe someone past the point where any real test can actually distinguish one score from another — the same honest-measurement problem this article covers, just at the opposite tail.

The bottom line

A score of zero is a real point on the deviation IQ formula and a point no test has ever measured, for the same reason: the formula is built to describe the middle of a distribution precisely, and it keeps working on paper long after the actual population it describes has run out. This is the same idea behind a ranking like average IQ by college major being meaningful only as a group comparison, never a verdict on one person: a score only means something next to the sample it was measured against, and at either extreme of the curve, that comparison sample has already run out.

Quick answers

  • Can you have an IQ of 0? No. No test reports it, and a person scoring the minimum on every subtest still gets about 40 on the WAIS-IV.
  • Can your IQ be negative? Only as a formula result below z = −6.67. No test or person has produced one.
  • Does anyone have an IQ of 0? No. As a joke, “0 IQ” means acting foolishly, not a measured score.
  • What is the lowest IQ ever recorded? Most tests print a floor near 40, and scores below roughly 20 to 25 are generally treated as unreliable, so no reliable record of a lower IQ exists.
  • What is the lowest possible IQ score? About 40 on the WAIS-IV and the Stanford-Binet 5. Below that, clinicians use adaptive behaviour and age-equivalent measures.
  • How rare would an IQ of 0 be? About 1 in 76.4 billion on the standard deviation 15 scale.

Sources

  • Wechsler Adult Intelligence Scale, Fourth Edition (Pearson, 2008): the Full Scale IQ range of 40 to 160, built from ten core subtests.
  • World Health Organization, ICD-10 (via the NHS ICD-10 browser): F70 to F79, approximate IQ ranges and adult mental-age equivalents for mild, moderate, severe and profound classes.
  • American Psychiatric Association: Diagnostic and Statistical Manual of Mental Disorders, fifth edition, text revision (DSM-5-TR), intellectual developmental disorder: severity graded by adaptive functioning.
  • Rarity figures are computed from the normal distribution with a mean of 100 and a standard deviation of 15.

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Tagged deviation iq, floor effect, intellectual disability, iq classifications, iq percentile, iq scale, IQ Science, IQ Score, lowest iq, norm-referenced testing, psychometrics, ratio iq, standard deviation