101–110 of 116 posts
Note that this is not some sort of unexpected effect due to humans not behaving mathematically ideally; this is what happens when your intuitions about 1, 2 and 3 dimensions are applied to higher dimensional spaces. Consider the goal of being in the middle 50% of a random value on one dimension; you have a 50% chance. But if you have two dimensions, and you want to be in the middle 50% for both of them, it's a 25% ch…
Note that this is not some sort of unexpected effect due to humans not behaving mathematically ideally; this is what happens when your intuitions about 1, 2 and 3 dimensions are applied to higher dimensional spaces. Consider the goal of being in the middle 50% of a random value on one dimension; you have a 50% chance. But if you have two dimensions, and you want to be in the middle 50% for both of them, it's a 25% ch…
how did you derive 38%?
Note that this is not some sort of unexpected effect due to humans not behaving mathematically ideally; this is what happens when your intuitions about 1, 2 and 3 dimensions are applied to higher dimensional spaces. Consider the goal of being in the middle 50% of a random value on one dimension; you have a 50% chance. But if you have two dimensions, and you want to be in the middle 50% for both of them, it's a 25% ch…
This comment was what made this article make sense to me. Just to add to add to the mathematical intuition here (please correct me if I'm wrong): if you're thinking of it as a unit line/square/cube then total n-dim area is 1^n, and the portion in the 50% range is (1/2)^n, where n = number of dimensions. So that should simplify to 2^(-n). Note this works out to 10th dimension as 0.09765% or 0.1 person per 1000. ETA: A…
But interestingly, every relevant comment here either got something wrong about the final frequency or percentage, or corrected the wrong thing. (Parent comment, grandparent, 2 aunts and 1 cousin.)
0.5^10 = 2^-10 = 1/(2^10) = 1/1024 [i.e. exactly 1 person per 1024] ~= 0.00097656 ~= 0.09766 %.
Earlier quoted context omitted.
Since intelligence must be a one-sided distribution it's probably right-tailed, which means the mean is higher than the median. So I expect (slightly) more than half of the population to be dumber than average.
>Since intelligence must be a one-sided distribution it's probably right-tailed, which means the mean is higher than the median. There are a lot of people with physical injuries or disabilities that skew things to the left.
Earlier quoted context omitted.
> Human dimensions are closer to a normal distribution Human height is (it's the textbook example of a real, intuitive_that is, using the normal linear scale—physical measure that is a good fit for a normal distribution) plenty of other human dimensions are not.
Human height should be a negative binomial distribution, since human height can't be negative.
That's a sensible analytical speculation, but it empirically fits very well with a normal distribution.
The fact that zero is, for adult male height (the typical cited example for fitting a nor Al distribution, though adult female height also works), around 17 standard deviations below the mean helps: I won't bother to calculate how little should be below that, since below 7σ in a normal distribution is 1/780 billion.
How many software engineers fit the mold of the bearded male craft beer connoisseur vs how many are trying to shoehorn themselves into it?
Not to pick on a single stereotype but it seems we've become memes and it's led to an attack of the clones on the ideas of diversity and inclusion flipping everything on its head Think about how 'fitting in' is also a term for 'averaging out' and ask yourself how much we value mediocrity? You can only join our group if you fit within one of these narrow guidelines and wear one size fits all clothing For crying out lo…
For that same reason though, I'm not sure I'd say that other groups differ so much. "Fake" realtors, "the typical hiker," or whatever it may be. The in-groups can often tell you about it first.
Groups do seek their own identity over time, and sometimes groups can have identity crises, in which they arrive at a consensus on a new set of values after some other set of values has run its course.
Even more importantly, individuals encountering this perspective--before the group does--have the opportunity to run early experiments and find new ways of being or communicating from the heart that may also be attractive to the social organism (of tech, or whatever).
Someone with your outlook may be able to help with this...and that could really add up to a lot.
Earlier quoted context omitted.
They are neither fully independent nor fully dependent. It falls somewhere in the middle. The same will apply, just in a slightly less dramatic effect.
But surely the engineers were who were inventing jets and rocket guidance systems and radar understood probabilities of independent events. The point, which the author almost misses completely, is that they dramatically overestimated how correlated the measurements were. Beyond that, while there's no accounting for taste, I find it to be an appallingly bad article. It's poor man's Malcolm Gladwell.
It is very common for engineering projects to encounter problems caused by an issue which was understood but was not identified. Most engineering failures fall into this category. Humans simply make mistakes.
Earlier quoted context omitted.
Not to pick on a single stereotype but it seems we've become memes and it's led to an attack of the clones on the ideas of diversity and inclusion flipping everything on its head Think about how 'fitting in' is also a term for 'averaging out' and ask yourself how much we value mediocrity? You can only join our group if you fit within one of these narrow guidelines and wear one size fits all clothing For crying out lo…
There's something more impersonal and less about authenticity, when you look at the factors involved in joining a group and becoming part of its identity, that's for sure. For that same reason though, I'm not sure I'd say that other groups differ so much. "Fake" realtors, "the typical hiker," or whatever it may be. The in-groups can often tell you about it first. Groups do seek their own identity over time, and somet…
Earlier quoted context omitted.
That last bit seems to be the Crux of why this is so surprising -- being in the middle 50% on some dimension correlates positively with being in the middle 50% on the other dimensions, rather than each dimension being independent as in your calculation. It's difficult for me to reconcile that, for the 400 in the study within 5% of average height, each was a standard deviation away from the mean in some other measurem…
It’s two different effects. First being within a range is not the same as being at the center of the range. Someone 4% above average height should have ~50% of their dimensions larger than that. Similarly someone at 4% below average should have around 50% of their dimensions below that. At best someone in the exact middle of the range only has so much buffer to work with. Second the correlation is less significant th…
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.
Earlier quoted context omitted.
It’s two different effects. First being within a range is not the same as being at the center of the range. Someone 4% above average height should have ~50% of their dimensions larger than that. Similarly someone at 4% below average should have around 50% of their dimensions below that. At best someone in the exact middle of the range only has so much buffer to work with. Second the correlation is less significant th…
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 an…
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.