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IQ percentile table

IQ percentiles: convert scores to percentile rank

An IQ percentile tells you the approximate share of the norm group that scored below a given IQ score. It is often easier to understand than the score alone.

View percentile table Open score chart
IQ percentile and score distribution

IQ percentile conversion table

These values are approximate and assume a common IQ scale with mean 100 and standard deviation 15.

Percentile Approx. IQ score Range Score page
1% 65 Below average IQ range IQ 65
2% 69 Below average IQ range IQ 69
5% 75 Low IQ range IQ 75
10% 81 Low average IQ range IQ 81
25% 90 Average IQ range IQ 90
50% 100 Average IQ range IQ 100
75% 110 High average IQ range IQ 110
90% 119 High average IQ range IQ 119
95% 125 Superior IQ range IQ 125
98% 131 Very high IQ range IQ 131
99% 135 Very high IQ range IQ 135

What does IQ percentile mean?

A percentile is a rank in a comparison group. The 75th percentile means a score is higher than about 75% of the norm group and lower than about 25%.

Percentile is not the same as percent correct. IQ tests convert raw performance into standardized scores, then those scores can be mapped to percentile ranks.

Because tests have different norms and confidence intervals, percentile values should be treated as approximate unless they come from the official test report.

Quick examples

  • IQ 100 is close to the 50th percentile on many common IQ scales.
  • IQ 115 is roughly around the upper quarter of the norm group.
  • IQ 130 is uncommon and is often around the top few percent, depending on the scale.

IQ percentile FAQ

No. Percent correct describes raw test accuracy. Percentile describes rank compared with a norm group after scores are standardized.

IQ 100 is the average on many IQ scales. The 50th percentile is the middle of the norm group, so the two values usually align closely.

Percentiles above the 75th are often above average, and percentiles above the 95th are uncommon. The interpretation still depends on the test and norms.

Percentiles are usually estimates. Rounding, test reliability, norm tables, and confidence intervals can all make exact-looking values less precise than they appear.

Tables can differ when they use different standard deviations, norm groups, rounding rules, or score conversion methods.
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