The Bell Curve

[_Analytics]

The problem is what people do with those variables. Do they assume that because x correlates with a, any person who is x is also a? Should a person be denied education beyond high school if their IQ is below 100? This is not a life insurance question about whether a person should pay $90 dollars a month instead of $70 because they smoke. The stakes are different.

Excellent questions. But it's two different things to say, "you did poorly on the standardized tests so we aren't going to accept you into our college," and say, "because of the color of your skin you'd probably do poorly on the standardized test, so let's save some time, energy, and embarrassment and just skip the test, shall we?"

The first statement is the reality of our world. The second is abhorrent.

[_Analytics]

Otherwise, if you already did and think it checks out, I find this to be a weird moment for you to fall in with the alt-righters. I suppose you and ldsfaqs could now enjoy the same videos, though, which is fun. :p

The video I linked is Gottfredson discussing the evolutionary and biological basis for the profound intellectual inferiority of blacks in a mental race hierarchy with ldsfaqs favorite Stefan Molyneux. It's long. I initially just queued it up to a particularly ugly point that corresponded to a claim I made about her. But I had the thing on in the background as I did work and ended up listening to it all. This video probably functions as a better introduction of who she in terms of racial science is than a Southern Poverty Law Center article is going to capture.

I'll have to take your word for it. I don't think I have the time or stomach to watch it.

[_Analytics]

Rather than continuing to read The Bell Curve, we can pivot over and read, Coming Apart: The State of White America, 1960-2010. This will give us three advantages--first, we'll get some glimpses of his arguments based on more recent research. Second, we'll avoid the whole race issue by only looking at what is happening within the white population. Third, maybe we'll have an easier discussion because their won't be so many strong opinions about it.

Or is the whole point of Coming Apart a way to dis on blacks without even mentioning them?

[Guest]

Who is it that you think is asking for help? That's twice now. Just weird. I'm not asking for help, I am registering some serious reservations regarding your the assessment of the statistical work you are reviewing.

Sorry for offering "help." I really wasn't trying to be patronizing.

And once again, you pick out a minor part of my post and don't address the statistical issues I was questioning.

In terms of this kind of model, saying it "fails for some" doesn't make any sense.

You have got to be kidding! I was paraphrasing YOU!!! You don't even remember you said that? And you are absolutely right, when you said it, it didn't make any sense.

Why do some people do better than the prediction and others do worse? Presumably there is a reason. Or maybe it's just luck. Or both?

You equate a model "failing" with a model not explaining everything.

You think I said that? Not even close, pal, not even close.

The model doesn't claim that there are no outliers.

Who said it did? Did you even read my comment??? Did you even read YOURS? Or the quotes you took out of the book?

You could look that up in a statistics text book.

If that's what you are basing your assessment on, it explains a lot.

Maybe I'm misunderstanding what you are saying. If you think I'm being patronizing in what I'm saying and that you are qualified to judge this in terms of statistics and what the book actually says, we can roll up our sleeves and rigorously perform an Analysis of Variance and engage it that way.

Right. You did not comment on a single issue from my post, and apparently you have no intention of actually addressing the statistical situation, beyond quoting definitions from high school textbooks, and flexing your muscles in some weird challenge.

Too bad, there are some interesting statistical questions that could have been discussed, but the surface approach you are taking is apparently ruling that out. Let me re-state then:

What I'm seeing from your summary and excerpts is that the authors have engaged in some extremely weak and unreliable statistical analysis, which they are then using to unjustifiably support their conclusions. I don't have the confidence you do that they are accurately portraying the situation; in my opinion you are taking their work at face value without adequately considering and understanding the statistical issues.

[_Gadianton]

I vote you continue with the chapter summaries because I want to see what the book is about and I am really interested in how it either comes together or falls apart for you in the end. Most of us are taking issue in anticipation of part two and with some bias ourselves.

I think you have a legit issue in part 1 to settle with Lemmie, and I hope you can multitask and address that at the same time as reading, while ignoring most of the rest until you finish the book.

[_Morley]

I vote you continue with the chapter summaries because I want to see what the book is about and I am really interested in how it either comes together or falls apart for you in the end. Most of us are taking issue in anticipation of part two and with some bias ourselves.

I think you have a legit issue in part 1 to settle with Lemmie, and I hope you can multitask and address that at the same time as reading, while ignoring most of the rest until you finish the book.

Agreed. We need to get to the good part.

[_Analytics]

Too bad, there are some interesting statistical questions that could have been discussed, but the surface approach you are taking is apparently ruling that out. Let me re-state then:

What I'm seeing from your summary and excerpts is that the authors have engaged in some extremely weak and unreliable statistical analysis, which they are then using to unjustifiably support their conclusions. I don't have the confidence you do that they are accurately portraying the situation; in my opinion you are taking their work at face value without adequately considering and understanding the statistical issues.

Obviously, I have done a terrible job of explaining what the book actually says. That is on me. As you know, I've been bombarded with questions on this thread.

Taking a step back, here is the original question:

And they repeatedly say that while IQ has the most predictive power of all of the variables in the dataset, individual factors that don't come through in the statistics are collectively the driving determinants of success.

So if individual factors, NOT captured by the statistics, are the "driving determinants" of success, then the only way that IQ could still have "the most predictive power" would be if those individual factors WERE correlated with IQ. But the main argument of these outliers, if I am reading you correctly, was that these individual factors were NOT correlated with IQ. So, which is it? IQ predicts? Or individual factors predict? Or is it that the authors are carefully asserting no individual is being talked about here, but their analysis still holds for groups and averages, hence EA's "exaggerated relationship" comment?

Let me answer this way.

Of all the variables studied, IQ is the best predictor of success. The higher your IQ, the higher the chances are you'll be successful. In statistical terms, this beta has high predictive power. There are plenty of "cognitively elite" people who underperform their IQ-based expectations. There are plenty of people in the middle of the bell curve that over perform their IQ-based expectations. Whether you under perform or over perform is your own epsilon.

The IQ predicts. Other individual factors (i.e. your epsilon) are huge on an individual level, so if you want to be successful in life, don't let your IQ discourage you, and don't let it make you overconfident. These other factors are statistically independent of your IQ. The researcher can't predict somebody's success based on them because the researcher doesn't know what those factors are.

Despite that, the power of IQ to predict success is, according to them, a powerful predictor compared to most statistically significant predictors in Social Science. It doesn't tell you very much about individuals, but it does tell you a lot about the averages of groups.

Regarding the accusation that they exaggerate the relationship, I'm at a loss. The accusation is made in a general way and I don't know how to address it.

Does that make any sense?

[_Always Changing]

Regarding the accusation that they exaggerate the relationship, I'm at a loss. The accusation is made in a general way and I don't know how to address it.

Does that make any sense?

The cream has already risen to the top, and that poor generally means unintelligent and criminal. I have to shut down because of lightning and thunder. want to wrote more, but not advisable.

[Guest]

Does that make any sense?

Before I respond, I would like to point out that this sentence is as patronizing as "Does that help?"

Is there a reason I am the only responder in this thread to which, in every single response to me, you have included this kind of condescending ending? You are not teaching me anything, nor are you explaining the academic basics of statistical analysis to me. We are two people, discussing an issue, expressing our opinions, and I would appreciate a response appropriate to that setting.

I am assuming you have an education that includes some statistics and I certainly know I do, so I would appreciate a stop to this. I don't mind if things get heated, but have the respect to not address me in a way that is different and less respectful than how you've responded to every other poster on this thread.

[_Lemmie]

Too bad, there are some interesting statistical questions that could have been discussed, but the surface approach you are taking is apparently ruling that out. Let me re-state then:

What I'm seeing from your summary and excerpts is that the authors have engaged in some extremely weak and unreliable statistical analysis, which they are then using to unjustifiably support their conclusions. I don't have the confidence you do that they are accurately portraying the situation; in my opinion you are taking their work at face value without adequately considering and understanding the statistical issues.

Obviously, I have done a terrible job of explaining what the book actually says. That is on me. As you know, I've been bombarded with questions on this thread.

Taking a step back, here is the original question:

And they repeatedly say that while IQ has the most predictive power of all of the variables in the dataset, individual factors that don't come through in the statistics are collectively the driving determinants of success.

So if individual factors, NOT captured by the statistics, are the "driving determinants" of success, then the only way that IQ could still have "the most predictive power" would be if those individual factors WERE correlated with IQ. But the main argument of these outliers, if I am reading you correctly, was that these individual factors were NOT correlated with IQ. So, which is it? IQ predicts? Or individual factors predict? Or is it that the authors are carefully asserting no individual is being talked about here, but their analysis still holds for groups and averages, hence EA's "exaggerated relationship" comment?

Let me answer this way.

Of all the variables studied, IQ is the best predictor of success. The higher your IQ, the higher the chances are you'll be successful. In statistical terms, this beta has high predictive power. There are plenty of "cognitively elite" people who underperform their IQ-based expectations. There are plenty of people in the middle of the bell curve that over perform their IQ-based expectations. Whether you under perform or over perform is your own epsilon.

The IQ predicts. Other individual factors (i.e. your epsilon) are huge on an individual level, so if you want to be successful in life, don't let your IQ discourage you, and don't let it make you overconfident. These other factors are statistically independent of your IQ. The researcher can't predict somebody's success based on them because the researcher doesn't know what those factors are.

Despite that, the power of IQ to predict success is, according to them, a powerful predictor compared to most statistically significant predictors in Social Science. It doesn't tell you very much about individuals, but it does tell you a lot about the averages of groups.

Regarding the accusation that they exaggerate the relationship, I'm at a loss. The accusation is made in a general way and I don't know how to address it.

Re-stating the book's conclusion over and over in no way addresses the statistical issues brought up. Are you saying the book fails to address any statistical issues, or fails to adequately support their statistical conclusions? If the above summarizes the book as you see it, there is even less reason to take their conclusions at face value.