Egalitarianism

[houndawg]

To me that's not my belief. But I do believe that there are differences in distributions of aptitudes between groups we classify as "races." I do believe that genetics is a factor in Asians just being better, on average, than others are iin math (for example).

You don't think it's difference culturally and not racially?

Asians emphasize studying your ass off, anything less than an A is a complete failure and they're shamed, etc. etc.

I don't think schooling is emphasized as much in black homes.

Take 20 asian kids and 20 black kids... switch their parents. Guarantee you the asian kids' math scores drop and the black kids' math scores increase.

I don't believe there is anything inherent about aptitude in any of the races. I don't believe math test scores are determined at birth. I also don't believe you've posted any decent evidence that there is an inherent difference in aptitude between black and asian kids from birth.

I'm sure there are similar statistics out there that would say a kid born in Louisiana scores lower, on average, than a kid from New Hampshire in math. Doesn't mean that Louisianans are genetically inferior or inherently worse at math than people from New Hampshire. I'm sure you would object to that.

I have seen an interesting bit in I can't remember which book, something like Freakonomics , that proposed that speakers of Chinese had an advantage in math because of their language which described numbers in such a way as to be a sort of verbal abacus that facilitated rapid calculation.

[93henfan]

For now I have to quit hogging the hotel lobby computer.

HA HAH! YOU CHEAP BASTARD!!!!

[JohnStOnge]

I have noticed that I was getting scores in the 100s the last time I queried the 2009 NAEP 8th grade math test and now I'm getting scores in the 200s. I'm going to have to try to figure out what's going on. The basic picture hasn't changed. But something weird is going on. For now I have to quit hogging the hotel lobby computer.

OK I figured it out. I was referring to the 12th grade NAEP Math test in the opening post rather than the 8th grade math test. I like using the 12th grade test when I can. But I can't use it to compare States because they didn't sample in all States for some reason like they did with the 8th grade test. You can get a legitimate estimate of national means without sampling in all States by doing something like first randomly sampling a subset of States then going from there. But, for instance, Louisiana wasn't sampled for the 12th grade test so I couldn't compare the 2 States.

BTW, I could find States, like Texas, that score consistently higher to a "significant" extent than Louisiana. But, as I said, I doubt that I could find a State in which poor children of a given race whose parents did not finish high school scored higher than "not poor" children of the same race whose parents were at the "college graduate" level.

In picking the comparison I used in the opening post I was picking a comparison in which it is VERY likely that the Asian group was at a disadvantage in terms of measurable environmental factors. It wouldn't be like that if I did something like compare "not poor" Black children whose parent(s) graduated college to the Asian children in the same category for reasons stated earlier. But when I made the comparison I did I ensured that the Asian children were definitely at an economic disadvantage and also were at a parental education level disadvantage. The economic disadvantage also made it unlikely that, on average, the Black children were served by poorer school districts. So on and so forth.

Some of the responsew I've gotten are exactly what I was talking about. People do not want to even entertain the possibility that genetics are a factor. We proceed under the assumption, for instance, that Black children would score about the same on the NAEP 12th grade math test as Asian children if they were exposed to exactly the same environments in all respects including culture. That assumption is not substantiated and there are indications consistent that it possibly not being true.

Yet we have all kinds of policies and approaches designed around that assumption and, as everyone knows, sometimes deny more objectively qualified people opportunities in favor of less objectively qualified members of "disadvantaged miniorities." And I hope nobody is going to argue that there isn't an effort to ensure that workforces and student bodies are "sufficiently diverse." Code for "there are enough people of color."

[JohnStOnge]

For now I have to quit hogging the hotel lobby computer.

HA HAH! YOU CHEAP BASTARD!!!!

Well, I AM cheap. But that's not the reason I'm using the hotel lobby computer for this. I have my work computer but I'm not going to use it to type on this message board because I express "unsanctioned" views such as this one. If I used my work computer to type on a subject like this it could cause me some grief.

Which is part of the social pressure to go along with the "acceptable" point of view in this area. It is not a "level playing field" when it comes to discussing this subject.

Also, I haven't seen anybody else express any interest in using this computer yet. I just figure at some point I ought to get off of it in case maybe somebody is peeking out of the elevator periodically or something thinking, "WHEN IS THAT $@^&*)! GOING TO GET THE $%*! OFF THE $%*!(#+ COMPUTER!!!

[JohnStOnge]

You don't think it's difference culturally and not racially?

It's not an "either/or" thing. It doesn't have to be environment or genetics. It could be both. Many thingss are. For instance, I don't think anybody would say that heredity plays no role in height. But environment plays a role too. 200 years ago people in the United States were shorter on average than they are now. And I think most believe it's because of environmental factors (nutrition, etc.). Today you could have a situation where at conception one individual could've ended up taller than another if both were exposed to exactly the same environment. But the other individual could end up taller instead if his or her environmental exposure was more favorable.

We all agree that math aptitude is tougher to get a handle on than something that can be directly measured like height. But I look at culture as an enviornmental factor that I'd expect could impact it. On the other hand I think that a point can be reached at which an objective person has to wonder if it can entirely account for an observed difference such as the one between economically disadvantaged Asian kids and relatively advantaged Black kids I cited.

I don't know if it's a slam dunk at all that if you had 20 randomly selected Black kids raised by poor Asian parents who both failed to finish high school and 20 randomly selected Asian kids raised by "not poor" Black children with at least one parent who graduated from college that the 20 Black kids would score higher on the NAEP 12 th grade math test. It'd be an interesting experiment...one of those "impossible to conduct" things as a practical matter...but I think it's a huge leap of faith to suggest a high level of confidence that the "culture" projected by the Asian parents would make that much of a difference.

I've seen the "culture of achievement" argument many times. But in my opinion it's at least partially kind of a "grasping at straws" action. People want to avoid contemplating genetics as a factor at all costs so they come up with whatever they can think of to avoid contemplating it.

[JohnStOnge]

BTW I do not advocate discriminating in things like hiring or school admissions based on race. If one Asian and one Black were applying for some job requiring math aptitude I would not assume the Asian had better math aptitude. I would test them and also look at other characteristics related to the job. I would favor a race blind process.

All I'm saying is that I think it's error to assume that there is something necessarily wrong with ending up with a situation in which the proportions of races in given groups are not consistent with proportions of those races in the society. I also think a view holding that equalizing all environments would make such inconsistencies go away is unsubstantiated. I think it's reasonble to think the magnitudes of inconsistencies would be reduced. But there is not anything close to sufficient evidence to assume they would go away. And I think that unsubstantiated assumption underlies an awful lot of social policy in this country.

[ASUMountaineer]

You don't think it's difference culturally and not racially?

Asians emphasize studying your ass off, anything less than an A is a complete failure and they're shamed, etc. etc.

I don't think schooling is emphasized as much in black homes.

Take 20 asian kids and 20 black kids... switch their parents. Guarantee you the asian kids' math scores drop and the black kids' math scores increase.

I don't believe there is anything inherent about aptitude in any of the races. I don't believe math test scores are determined at birth. I also don't believe you've posted any decent evidence that there is an inherent difference in aptitude between black and asian kids from birth.

I'm sure there are similar statistics out there that would say a kid born in Louisiana scores lower, on average, than a kid from New Hampshire in math. Doesn't mean that Louisianans are genetically inferior or inherently worse at math than people from New Hampshire. I'm sure you would object to that.

I have seen an interesting bit in I can't remember which book, something like Freakonomics , that proposed that speakers of Chinese had an advantage in math because of their language which described numbers in such a way as to be a sort of verbal abacus that facilitated rapid calculation.

Nice. Dubner is a fellow Mountaineer.

[kalm]

BTW I do not advocate discriminating in things like hiring or school admissions based on race. If one Asian and one Black were applying for some job requiring math aptitude I would not assume the Asian had better math aptitude. I would test them and also look at other characteristics related to the job. I would favor a race blind process.

All I'm saying is that I think it's error to assume that there is something necessarily wrong with ending up with a situation in which the proportions of races in given groups are not consistent with proportions of those races in the society. I also think a view holding that equalizing all environments would make such inconsistencies go away is unsubstantiated. I think it's reasonble to think the magnitudes of inconsistencies would be reduced. But there is not anything close to sufficient evidence to assume they would go away. And I think that unsubstantiated assumption underlies an awful lot of social policy in this country.

That's the point I was driving at - it's not egalitarianism that's the problem. It's how we approach and maintain the egalitarian society that folks like Locke, and Adam Smith, and many of the founders advocated for.

[Skjellyfetti]

I have seen an interesting bit in I can't remember which book, something like Freakonomics , that proposed that speakers of Chinese had an advantage in math because of their language which described numbers in such a way as to be a sort of verbal abacus that facilitated rapid calculation.

Not sure if you were disagreeing with me or adding to my argument...

But, language would be a product of culture. A black kid growing up speaking Chinese would have the same advantage.

[AZGrizFan]

Yay!

I had a really deep thought and then I saw these pics and it was gone.

[ASUG8]

So I think that so far we've determined that:

* educational achievement could be due to nature
* educational achievement could be due to nurture
* educational achievement could be due to both
* educational achievement could be due to neither

and that there are:
* lies
* damned lies, and
* statistics

[JohnStOnge]

and that there are:
* lies
* damned lies, and
* statistics

A change of subject but that Mark Twain quote is one of the most over-rated quotes ever. If provides a convenient, cute sounding cop out when the data contradict what one wishes to believe.

Misinformation is misinformation whether it's in the form of statistics or narrative language. Sure, you can try to deceive somebody with a deceptive statistical presentation just like you can attempt to deceive somebody by taking things out of context in a narrative way or out and out lying. Lies are lies, whether they involve statistics or not.

And there are no lies in the statistics I presented. I gave the source. I fully described what I did. I noted that the estimates are based on "scientific" sampling and that is true. You can hypothesize as you will about why it is so just as I can. But in 2009 when that 12th Grade NAEP math test was administered in the public school system nationally poor Asian children with parents that did not finish high school scored higher than middle to upper class Black kids who had at least one parent who graduated from college. And that happened in spite of the fact that in the overall population middle to upper class kids who had at least one parent that graduated from college scored 33 points higher on average than poor kids with parents who didn't finish high school did. 33 points is a huge difference for a test such that the overall national average is 154 and the overall national standard deviation is 34.

The post at the top of this thread is not "lying with statistics." It is telling the truth with statistics. And the truth is that the fact that Asian kids at the most "disadvantaged" extreme of the Socioeconomic Status/Parental Education grouping scored higher than Black kids at the most "advantaged" extreme to a "statistically significant" extent when the difference in averages between those extremes overall is so large in the overall sample SHOULD make any reasonable person at least BEGIN to question some of the "approved" assumptions of this irrationally egalitarian culture.

[ASUG8]

and that there are:
* lies
* damned lies, and
* statistics

A change of subject but that Mark Twain quote is one of the most over-rated quotes ever. If provides a convenient, cute sounding cop out when the data contradict what one wishes to believe.

Misinformation is misinformation whether it's in the form of statistics or narrative language. Sure, you can try to deceive somebody with a deceptive statistical presentation just like you can attempt to deceive somebody by taking things out of context in a narrative way or out and out lying. Lies are lies, whether they involve statistics or not.

And there are no lies in the statistics I presented. I gave the source. I fully described what I did. I noted that the estimates are based on "scientific" sampling and that is true. You can hypothesize as you will about why it is so just as I can. But in 2009 when that 12th Grade NAEP math test was administered in the public school system nationally poor Asian children with parents that did not finish high school scored higher than middle to upper class Black kids who had at least one parent who graduated from college. And that happened in spite of the fact that in the overall population middle to upper class kids who had at least one parent that graduated from college scored 33 points higher on average than poor kids with parents who didn't finish high school did. 33 points is a huge difference for a test such that the overall national average is 154 and the overall national standard deviation is 34.

The post at the top of this thread is not "lying with statistics." It is telling the truth with statistics. And the truth is that the fact that Asian kids at the most "disadvantaged" extreme of the Socioeconomic Status/Parental Education grouping scored higher than Black kids at the most "advantaged" extreme to a "statistically significant" extent when the difference in averages between those extremes overall is so large in the overall sample SHOULD make any reasonable person at least BEGIN to question some of the "approved" assumptions of this irrationally egalitarian culture.

LIghten up, John. I wasn't calling you a liar. Just saying that you can generally paint many pictures with the same data set depending on which variables you choose to include/exclude. Pay attention to the first part of my post - that was more serious. By your own admission there could be multiple other variables that play into this difference. IMHO, you took an end result (testing inequities) and used convenient stereotypes to build a model to explain it. Maybe you're right, maybe not.

[93henfan]

Yay!

I had a really deep thought and then I saw these pics and it was gone.

I know what you were about to say. You were going to mention how egalitarianism is...

..um...

CAMEL TOE!!!!

[houndawg]

and that there are:
* lies
* damned lies, and
* statistics

A change of subject but that Mark Twain quote is one of the most over-rated quotes ever. If provides a convenient, cute sounding cop out when the data contradict what one wishes to believe.

Misinformation is misinformation whether it's in the form of statistics or narrative language. Sure, you can try to deceive somebody with a deceptive statistical presentation just like you can attempt to deceive somebody by taking things out of context in a narrative way or out and out lying. Lies are lies, whether they involve statistics or not.

And there are no lies in the statistics I presented. I gave the source. I fully described what I did. I noted that the estimates are based on "scientific" sampling and that is true. You can hypothesize as you will about why it is so just as I can. But in 2009 when that 12th Grade NAEP math test was administered in the public school system nationally poor Asian children with parents that did not finish high school scored higher than middle to upper class Black kids who had at least one parent who graduated from college. And that happened in spite of the fact that in the overall population middle to upper class kids who had at least one parent that graduated from college scored 33 points higher on average than poor kids with parents who didn't finish high school did. 33 points is a huge difference for a test such that the overall national average is 154 and the overall national standard deviation is 34.

The post at the top of this thread is not "lying with statistics." It is telling the truth with statistics. And the truth is that the fact that Asian kids at the most "disadvantaged" extreme of the Socioeconomic Status/Parental Education grouping scored higher than Black kids at the most "advantaged" extreme to a "statistically significant" extent when the difference in averages between those extremes overall is so large in the overall sample SHOULD make any reasonable person at least BEGIN to question some of the "approved" assumptions of this irrationally egalitarian culture.

Here's one that is one of the most underrated quotes ever: Statistics are like bikinis, what they reveal is very interesting, what they don't reveal is vital. Don't recall if it was Juran or Deming that gets the credit.

[houndawg]

I have seen an interesting bit in I can't remember which book, something like Freakonomics , that proposed that speakers of Chinese had an advantage in math because of their language which described numbers in such a way as to be a sort of verbal abacus that facilitated rapid calculation.

Not sure if you were disagreeing with me or adding to my argument...

But, language would be a product of culture. A black kid growing up speaking Chinese would have the same advantage.

[JohnStOnge]

Here's one that is one of the most underrated quotes ever: Statistics are like bikinis, what they reveal is very interesting, what they don't reveal is vital. Don't recall if it was Juran or Deming that gets the credit.

I think that quote dramatically understates the power of statisticsal estimation and analysis when those things are properly applied. A "statistic" is just an estimate of a "parameter." A parameter is a true value. For instance, if investigators had been able to test every single poor Asian national public school student of parents who didn't finish high school there would have been some average score. That average is the parameter. Since they could not do that or because doing that would've been too much they took a probability sample of that population and got a sample average. That sample average is a statistic; an estimate of the parameter. And statistical estimation techniques allow for establishing given levels of "confidence" that the parameter is somewhere within some interval.

That estimate can be compared to the one for middle and upper class Black children who had at least one parent who graduated college. Then the parameter is the true difference between what the averages would've been if they'd tested all students in each group and the statistic is the difference between the sample averages. And a statistical hypothesis test can be applied to establish a level of confidence that the parameter is not zero, that it is within some interval, or that it is greater or less than some value.

Another statistic is the 33 point difference between the "poor children of parents who didn't finish high school" and "middle to upper class children with at least one parent who graduated college" groups. A confidence interval estimate could be constructed for the underlying parameter and it would indicate that a very large true difference existed.

What statistics can't reveal in this instance is cause and effect because the data are observational. There has been no controlled experiment, for example, to infer that the difference in socioeconomic status and parental education level caused the referenced 33 point difference. Of course saying those differences in environment were at least a substantial factor in the difference is a reasonable hyphothesis. And it's one nobody is going to have any particular resistance to.

But we routinely view the world in terms of what are essentially statistics. If I say "men are taller on average than women" that is based basically on a statistic; whether it is formally derived or not. No one has ever measured the height of every man on earth and every woman on earth and reported the true parameter at any given time. Also, an awful lot of what we might consider vital knowledge is based on statistics. Maybe even most of it. "Cigarettes cause cancer," for example. And that one, technically, hasn't even been fully established because there have understandably been no controlled experiments to directly infer it.

Again, I think quotes like Twain's and the one above sound clever but they're really not all that clever. I think they are cute sounding quotes people sometimes invoke when they are confronated with legitimate statistics they'd rather not be confronted with. Sure, there can be unreliable and/or deceptive statistics and/or people can use statistics in an attempt to deceive just like they can use any other kind of information. But you can usually identify the problems by asking a few questions about how the statistics were derived, etc.

[houndawg]

Here's one that is one of the most underrated quotes ever: Statistics are like bikinis, what they reveal is very interesting, what they don't reveal is vital. Don't recall if it was Juran or Deming that gets the credit.

I think that quote dramatically understates the power of statisticsal estimation and analysis when those things are properly applied. A "statistic" is just an estimate of a "parameter." A parameter is a true value. For instance, if investigators had been able to test every single poor Asian national public school student of parents who didn't finish high school there would have been some average score. That average is the parameter. Since they could not do that or because doing that would've been too much they took a probability sample of that population and got a sample average. That sample average is a statistic; an estimate of the parameter. And statistical estimation techniques allow for establishing given levels of "confidence" that the parameter is somewhere within some interval.

That estimate can be compared to the one for middle and upper class Black children who had at least one parent who graduated college. Then the parameter is the true difference between what the averages would've been if they'd tested all students in each group and the statistic is the difference between the sample averages. And a statistical hypothesis test can be applied to establish a level of confidence that the parameter is not zero, that it is within some interval, or that it is greater or less than some value.

Another statistic is the 33 point difference between the "poor children of parents who didn't finish high school" and "middle to upper class children with at least one parent who graduated college" groups. A confidence interval estimate could be constructed for the underlying parameter and it would indicate that a very large true difference existed.

What statistics can't reveal in this instance is cause and effect because the data are observational. There has been no controlled experiment, for example, to infer that the difference in socioeconomic status and parental education level caused the referenced 33 point difference. Of course saying those differences in environment were at least a substantial factor in the difference is a reasonable hyphothesis. And it's one nobody is going to have any particular resistance to.

But we routinely view the world in terms of what are essentially statistics. If I say "men are taller on average than women" that is based basically on a statistic; whether it is formally derived or not. No one has ever measured the height of every man on earth and every woman on earth and reported the true parameter at any given time. Also, an awful lot of what we might consider vital knowledge is based on statistics. Maybe even most of it. "Cigarettes cause cancer," for example. And that one, technically, hasn't even been fully established because there have understandably been no controlled experiments to directly infer it.

Again, I think quotes like Twain's and the one above sound clever but they're really not all that clever. I think they are cute sounding quotes people sometimes invoke when they are confronated with legitimate statistics they'd rather not be confronted with. Sure, there can be unreliable and/or deceptive statistics and/or people can use statistics in an attempt to deceive just like they can use any other kind of information. But you can usually identify the problems by asking a few questions about how the statistics were derived, etc.

The Japanese rode the above quote all the way to world class manufacturing capability, I think it's not as unclever as you think.

[∞∞∞]

..."Cigarettes cause cancer," for example. And that one, technically, hasn't even been fully established because there have understandably been no controlled experiments to directly infer it.

WTF?

[ASUG8]

..."Cigarettes cause cancer," for example. And that one, technically, hasn't even been fully established because there have understandably been no controlled experiments to directly infer it.

WTF?

Missed that one - easy to miss in these mini books. I would venture that the CV, R-squared, p and t values for that correlation are strong enough to make a solid argument against smoking....more so than the argument being posed here.

[ASUMountaineer]

WTF?

Missed that one - easy to miss in these mini books. I would venture that the CV, R-squared, p and t values for that correlation are strong enough to make a solid argument against smoking....more so than the argument being posed here.

Right. I can't see how it would be possible that putting a lighted piece of paper in your mouth and inhaling smoke into your lungs could ever be considered harmful. It's just a ridiculous notion, tar--nothing to see here, completely safe.

[Ivytalk]

A change of subject but that Mark Twain quote is one of the most over-rated quotes ever. If provides a convenient, cute sounding cop out when the data contradict what one wishes to believe.

Misinformation is misinformation whether it's in the form of statistics or narrative language. Sure, you can try to deceive somebody with a deceptive statistical presentation just like you can attempt to deceive somebody by taking things out of context in a narrative way or out and out lying. Lies are lies, whether they involve statistics or not.

And there are no lies in the statistics I presented. I gave the source. I fully described what I did. I noted that the estimates are based on "scientific" sampling and that is true. You can hypothesize as you will about why it is so just as I can. But in 2009 when that 12th Grade NAEP math test was administered in the public school system nationally poor Asian children with parents that did not finish high school scored higher than middle to upper class Black kids who had at least one parent who graduated from college. And that happened in spite of the fact that in the overall population middle to upper class kids who had at least one parent that graduated from college scored 33 points higher on average than poor kids with parents who didn't finish high school did. 33 points is a huge difference for a test such that the overall national average is 154 and the overall national standard deviation is 34.

The post at the top of this thread is not "lying with statistics." It is telling the truth with statistics. And the truth is that the fact that Asian kids at the most "disadvantaged" extreme of the Socioeconomic Status/Parental Education grouping scored higher than Black kids at the most "advantaged" extreme to a "statistically significant" extent when the difference in averages between those extremes overall is so large in the overall sample SHOULD make any reasonable person at least BEGIN to question some of the "approved" assumptions of this irrationally egalitarian culture.

Here's one that is one of the most underrated quotes ever: Statistics are like bikinis, what they reveal is very interesting, what they don't reveal is vital. Don't recall if it was Juran or Deming that gets the credit.

I like that one! God help me, I can't even finish JSO's posts.

[Rob Iola]

I had a really deep thought and then I saw these pics and it was gone.

I know what you were about to say. You were going to mention how egalitarianism is...

..um...

CAMEL TOE!!!!

Just leave out the moose knuckle pics please - I'd prefer not having to break out the mind bleach...

[Ibanez]

John, I think you should research Mark Twains thoughts on brevity.

[JohnStOnge]

Missed that one - easy to miss in these mini books. I would venture that the CV, R-squared, p and t values for that correlation are strong enough to make a solid argument against smoking....more so than the argument being posed here.

There is plenty of evidence of association between smoking and cancer. But you can't infer cause and effect without a controlled experiment. I've posted an excerpt from a graduate level experimental statistics textbook on this forum as well as on the "other" one before in which the author specifically used associations between cigarette smoking and cancer as well as heart disease as examples of the principle that one can't infer cause and effect from observational studies. I can't post it again now because I've got it saved on my hard drive at home and I'm on a hotel lobby computer. Besides people are already complaining about my long posts and it's a long excerpt.

Perhaps smoking has been shown to cause cancer in other ways. Don't know. But, if the rules are followed, it can never be shown to "cause" cancer with statistical data unless and until a controlled experiment is conducted to infer that. By "controlled experiment" I mean you'd have to get a group of experimental subjects. You'd have to randomly assign some to smoke and others not to smoke. And the subjects would have to do what they're assigned to do. Then you'd have to follow them over the years and watched lung cancer rates in the two groups.

You can never, ever legitimately infer cause and effect from just looking at people who chose to smoke vs. people who chose not to. You can identify an association. But association is not necessarily causation.

Believe it or not, a drug manufacturer would NEVER be allowed to claim a positive effect of a drug based on the kind evidence used to say that cigarette smoking causes cancer. If they tried it they'd be prosecuted for making unsubstantiated claims.

And if you're wondering: I do believe that cigarette smoking increases cancer risk. That's not the point. The point is that all the reams of statistical data showing association between cigarette smoking and cancer cannot legitimately be used to infer that cigarette smoking causes cancer because they are all observational rather than experimental data.

The shame of it is that people have been so bombarded with conclusions based on observational data that when someone tells them the truth about the limitations of such data they may be ridiculed when they are absolutely correct.