The easiest interpretation to measure would be a regression toward the mean effect. Putting a lower bound on the IQ scores in your sample means that you have a relevant fraction of people who tested higher than their average test score. I suspect that at the high end, IQ tests have few enough questions scored incorrectly that noise can let some < 1 in 5000 IQ test takers into your 1 in 10000 cutoff.
I also didn’t note the other problem: 1 in 10,000 is around IQ=155; the ceiling of most standardized (validated and normed) intelligence tests is around 1 in 1000 (IQ~=149). Tests above this tend to be constructed by people who consider themselves in this range, to see who can join their high IQ society and not substantially for any other purpose.
The easiest interpretation to measure would be a regression toward the mean effect. Putting a lower bound on the IQ scores in your sample means that you have a relevant fraction of people who tested higher than their average test score. I suspect that at the high end, IQ tests have few enough questions scored incorrectly that noise can let some < 1 in 5000 IQ test takers into your 1 in 10000 cutoff.
I also didn’t note the other problem: 1 in 10,000 is around IQ=155; the ceiling of most standardized (validated and normed) intelligence tests is around 1 in 1000 (IQ~=149). Tests above this tend to be constructed by people who consider themselves in this range, to see who can join their high IQ society and not substantially for any other purpose.