IQ Score Chart Explained: Mean, Standard Deviation, Percentiles, and Ranges
An IQ score chart summarizes a standardized distribution. It does not convert any online quiz total into IQ. Before reading a band or percentile, verify the test edition, mean, standard deviation, norm group and confidence interval.
01
The familiar 100 and 15 convention
Many, but not all, IQ scales are reported with mean 100 and standard deviation 15. Roughly speaking, 85 and 115 are one standard deviation below and above the mean on such a scale.
This convention describes transformed norm scores. It is not a universal raw-score ruler and does not authorize conversion from an unrelated test.
02
Percentiles and standard scores answer different questions
A standard score describes distance from the norm mean on the chosen scale. A percentile rank describes the proportion of the norm distribution at or below a score under that test's rules.
Percentile intervals are uneven: equal standard-score differences do not produce equal percentile-point differences near the center and tails.
03
Why range labels vary
Labels such as average, high average or superior are publisher-specific interpretive conventions. Cut points and wording differ, and some terms carry historical baggage.
Use the manual for the administered test. A generic web chart can illustrate a distribution, but it should not overwrite the test's official score definitions.
04
Confidence intervals belong beside the score
No observed score is perfectly precise. A confidence interval communicates a plausible range for the underlying score under a stated model and confidence level.
Small differences between two numbers may not support a meaningful rank order, especially across different domains or instruments.
05
A worked reading example
Suppose a manual reports a standard score of 112 on a scale with mean 100 and standard deviation 15, together with a confidence interval of 106–118. The observed value is 12 scale points above the norm mean, but the interval shows that plausible values cover a wider band. The correct interpretation comes from that manual's norms and precision study—not from treating 112 as 112 questions, 112 percent or a universal ranking.
If another website reports 16 of 20 correct, that result is 80 percent correct on its form. It does not become IQ 112 by matching the numbers to a generic chart. A norm conversion must be estimated for that exact form and eligible population, and it should carry its own uncertainty.
06
Why the tails require extra caution
Very high and very low scores are supported by fewer observations in most norm samples. Short forms may also have too few appropriately targeted items to distinguish people near the ends of a distribution. Ceiling and floor effects can compress different performances into the same reported result.
Percentiles amplify this issue because small standard-score changes in the tails can look like large differences in rarity. Claims about giftedness, impairment or membership thresholds should use the required approved instrument and administration, not a rounded online chart.
07
A safe chart-reading checklist
Before interpreting a chart, identify the exact test, edition, age or comparison group, standard deviation, norm date, confidence level and intended use.
- Never convert a raw total with an unrelated chart
- Do not compare scores from different scales without documentation
- Treat labels as summaries, not identities
- Keep high-stakes interpretation with qualified professionals
Questions
Common questions
Is 100 always the average IQ?
It is a common reporting convention, but interpretation still depends on the specific test, edition and norm group.
Can two different tests give different IQ scores?
Yes. They may sample different domains, use different norms, contain measurement error and be administered under different conditions.
Is percentile the same as percent correct?
No. Percent correct is a raw test proportion. Percentile is a norm-referenced rank based on a comparison distribution.
Sources and standards used for this guide
These references support the general testing principles discussed here. They do not validate Ikigain's independently written item set or create population norms for it.