Sure, but being in the middle 10 percentile in height(or some other dimension) would serve to "normalize" the sample; so 400 people are close to the center of the larger range. Despite being close to the middle of the range, some dimension is far from the center of it's range.
Yes, the correlation is not as strong as I would assuming -- that was really the point of my comment. You are a sample size of one, so your anecdote doesn't mean much. However, based on this work, apparently almost everyone has a similar anecdote: after normalizing for height, there is another common dimension which is "unusually" large or small.
The slope of a bell curve near it’s center is almost flat. This means you end up with a fairly uniform distribution when looking at values near the median. Which makes outliers within that range more common than intuition suggests.
Yes, the correlation is not as strong as I would assuming -- that was really the point of my comment. You are a sample size of one, so your anecdote doesn't mean much. However, based on this work, apparently almost everyone has a similar anecdote: after normalizing for height, there is another common dimension which is "unusually" large or small.