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Even humans are able to tell races apart by observing phenotypes, most of the time. The reason why genetic analysis failed is simply associated with bad experimental design, bad samples, and bad analysis.
For example, the genes that determine skin color can certainly separate white (and maybe East Asians) from other races. We are talking about statistics, not case by case.
Once more.
Humans are genetically homogenous, that means there is greater variation WITHIN the arbitrary groupings of "race" than between them. That is fact. Seriously, they have sequenced huge sections of genome, in numerous people of different races.
Races, need to be genetically divergent its the basic biological definition. There is nothing that suggests human are genetically divergent. Hell, if anything they have become more and more genetically convergent.
Come on be honest already, there is nothing in science that could convince you that races are a meaningless designation. And since that has become abundantly clear, there is no point in talking to you as if you were a rational human being.
Humans are genetically homogenous, that means there is greater variation WITHIN the arbitrary groupings of "race" than between them. That is fact. Seriously, they have sequenced huge sections of genome, in numerous people of different races.
Races, need to be genetically divergent its the basic biological definition. There is nothing that suggests human are genetically divergent. Hell, if anything they have become more and more genetically convergent.
Come on be honest already, there is nothing in science that could convince you that races are a meaningless designation. And since that has become abundantly clear, there is no point in talking to you as if you were a rational human being.
You biologists have abused math/statistics enough. As a data scientist I wonder why you guys can't stop pretending you understand it.
Who told you the within/between group variances are necessarily crucial for data classification? You imagine every distribution is Gaussian or what?
Think about this: In a 2D feature space, there is a circle. Members of Group A fall in the circle, and members of Group B out of the circle. You know what? The variance in Group A or B respectively can be larger than the variance between the two groups, but they are classifiable! The circle is a perfect boundary between two groups. Why? Because we are not talking about some simple, normal distributions here! Genetic analysis always involves high dimensional data, and thus your way of thinking does not work at all.
Secondly, in order to do good classification, we can do feature selection (heard of the term?). As far as genes are concerned, we can select genes that determine skin color, hair color, muscle structure...(just examples here). It may or may not be irrelevant to analyze genes that are correlated with height, weight, cancer etc.
You can create classifications, but those classifications are not races.
A race must be a genetically divergent population with small genetic and morphological differences that are either ecologically or geographically isolated from each other and, as a result, diverging towards subspecies, but not of sufficient divergence or geographic isolation to be a subspecies.
Very interesting data, and it appears to be closely aligned the results of decades worth of IQ testing and income levels. Granted, it is old data and the GRE format and scoring has changed since then, but I'd be willing to bet there would be little to no change in the actual rankings since that time.
As to the question regarding why this was posted: I personally like to see data that addresses the claims we frequently see in society that are rarely, if ever substantiated with data. We are told constantly that every group is inherently equal in intellectual capability when virtually every study suggests otherwise. While I agree that data like this will most often be used negatively, I don't appreciate being told supposed truths that originate in feelings, hopes and wishes rather than facts.
Last edited by War Beagle; 02-14-2013 at 02:24 PM..
I think you missed the part about how the GRE badly underpredicts the success of women and underrepresented minorities in grad school; and how graduate departments largely ignore the GRE except as a strict cutoff (even though ETS states that a strict cutoff is an inappropriate use of the GRE).
In other words, what does the GRE actually predict other than test taking ability? (which is particularly bad when you consider that ETS is one of the worst companies at correcting cultural testing bias)
What is the point of these racial threads about who scores better and who is over or under represented? It this a political rant or what?
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