Bungee Jumper Posted November 2, 2006 Share Posted November 2, 2006 You don't think he's angry?!?!?!? What on earth planet are you living on? Have you been abducted by space aliens or something--aliens that are using your fingers to transmit their own weird thoughts? This guy has "anger management issues" written all over him. In big neon letters. If you're too blind to see that . . . well, I guess it wouldn't be the first time you were too blind to see something obvious. 822443[/snapback] Uhhhhh...no, he doesn't. Link to comment Share on other sites More sharing options...
Orton's Arm Posted November 2, 2006 Author Share Posted November 2, 2006 1) That equation is bull sh--. The one in the article isn't, necessarily (it's incorrect for being incomplete - but not bull sh--). But naturally, you being you, you don't understand the math and !@#$ed it all up.2) Heritability and inheritability are two different things, you fool! How many times do you have to have it explained to you? 3) I'm mocking you for taking bits and pieces of things out of context, without understanding them, to suit your own bull sh-- eugenics beliefs. Hell, if you read the Wikipedia link you provided, you'd see that it contradicts everything you've said!!!! Particularly the equation which you took out of context, which demonstrates that your eugenics program will not work! 822594[/snapback] 1. You're wrong. 2. The article used the word "heritability" in the equation, as well as in the following sentence: The American Psychological Association's 1995 task force on "Intelligence: Knowns and Unknowns" concluded that within the white population the heritability of IQ is "around .75" (p. 85). We're talking apples to apples. 3. The article fits in nicely with what I've said--that intelligence is largely genetic, that parental intelligence drives the intelligence of children, etc. The formula which I cited is basically a mathematical definition of regression toward the mean. I've addressed the issue elsewhere. And at least for Weiss, regression toward the mean is simply an artifact of measurement error, rather than a genuinue phenomenon. Certainly it's not something that should be allowed to stand in the way of an otherwise welcome eugenics program. Link to comment Share on other sites More sharing options...
Bungee Jumper Posted November 2, 2006 Share Posted November 2, 2006 1. You're wrong.2. The article used the word "heritability" in the equation, as well as in the following sentence: The American Psychological Association's 1995 task force on "Intelligence: Knowns and Unknowns" concluded that within the white population the heritability of IQ is "around .75" (p. 85). We're talking apples to apples. No, I'm not, and the article uses "heritability" correctly. YOU use it wrong, because you don't know what it means. 3. The article fits in nicely with what I've said--that intelligence is largely genetic, that parental intelligence drives the intelligence of children, etc. The formula which I cited is basically a mathematical definition of regression toward the mean. I've addressed the issue elsewhere. And at least for Weiss, regression toward the mean is simply an artifact of measurement error, rather than a genuinue phenomenon. Certainly it's not something that should be allowed to stand in the way of an otherwise welcome eugenics program. 822661[/snapback] So the equation you're using to support your point of view doesn't actually support your point of view unless you assume it's wrong, in which case you arbitrarily attribute it to "measurement error" so you can pretend it still supports your point of view. And you actually believe this sh-- you're shoveling? Link to comment Share on other sites More sharing options...
Orton's Arm Posted November 2, 2006 Author Share Posted November 2, 2006 No, I'm not, and the article uses "heritability" correctly. YOU use it wrong, because you don't know what it means. There you go again. So the equation you're using to support your point of view doesn't actually support your point of view unless you assume it's wrong, in which case you arbitrarily attribute it to "measurement error" so you can pretend it still supports your point of view. The issue we were arguing about was whether intelligent adults are more likely than average to have intelligent children. You, apparently, weren't convinced that intelligent parents were any more likely to produce smart children than were any other type of parents. The formula demonstrates, with mathematical precision, that the confusion you've been trying to create about the word "heritability" is counterproductive. Intelligence is passed from one generation to the next. The formula is a mathematical description of regression toward the mean. Is regression toward the mean taking place? Assuming it is, successfully convincing smart people to have more children will result in a population that's smarter than it otherwise would have been. But suppose Weiss is right, and the appearance of regression toward the mean is due entirely to measurement error. In that case, the benefits of a eugenics program would be even greater. Link to comment Share on other sites More sharing options...
Chilly Posted November 2, 2006 Share Posted November 2, 2006 There you go again. So the equation you're using to support your point of view doesn't actually support your point of view unless you assume it's wrong, in which case you arbitrarily attribute it to "measurement error" so you can pretend it still supports your point of view. The issue we were arguing about was whether intelligent adults are more likely than average to have intelligent children. You, apparently, weren't convinced that intelligent parents were any more likely to produce smart children than were any other type of parents. The formula demonstrates, with mathematical precision, that the confusion you've been trying to create about the word "heritability" is counterproductive. Intelligence is passed from one generation to the next. The formula is a mathematical description of regression toward the mean. Is regression toward the mean taking place? Assuming it is, successfully convincing smart people to have more children will result in a population that's smarter than it otherwise would have been. But suppose Weiss is right, and the appearance of regression toward the mean is due entirely to measurement error. In that case, the benefits of a eugenics program would be even greater. 822744[/snapback] I love lamp Link to comment Share on other sites More sharing options...
Bungee Jumper Posted November 2, 2006 Share Posted November 2, 2006 There you go again. So the equation you're using to support your point of view doesn't actually support your point of view unless you assume it's wrong, in which case you arbitrarily attribute it to "measurement error" so you can pretend it still supports your point of view. The issue we were arguing about was whether intelligent adults are more likely than average to have intelligent children. You, apparently, weren't convinced that intelligent parents were any more likely to produce smart children than were any other type of parents. The formula demonstrates, with mathematical precision, that the confusion you've been trying to create about the word "heritability" is counterproductive. Intelligence is passed from one generation to the next. The formula is a mathematical description of regression toward the mean. Is regression toward the mean taking place? Assuming it is, successfully convincing smart people to have more children will result in a population that's smarter than it otherwise would have been. But suppose Weiss is right, and the appearance of regression toward the mean is due entirely to measurement error. In that case, the benefits of a eugenics program would be even greater. 822744[/snapback] This is asinine. Your post makes no sense. "Assuming regression towards the mean is occurring, it means it won't happen. But it's not because it's measurement error, so I can dismiss it." You've taken stupid to a whole new level... Why not, instead of dismissing the presumed "measurement error" (sic), analyze the equation at the bulk limit where any measurement error averages out? That's a very easy thing to do, if you know any sort of math whatsoever. Of course, it still doesn't address the simple fact that the equation's wrong...but it'll at least prove to you that you're a fool. Link to comment Share on other sites More sharing options...
Ramius Posted November 2, 2006 Share Posted November 2, 2006 1. You're wrong.2. The article used the word "heritability" in the equation, as well as in the following sentence: The American Psychological Association's 1995 task force on "Intelligence: Knowns and Unknowns" concluded that within the white population the heritability of IQ is "around .75" (p. 85). We're talking apples to apples. 3. The article fits in nicely with what I've said--that intelligence is largely genetic, that parental intelligence drives the intelligence of children, etc. The formula which I cited is basically a mathematical definition of regression toward the mean. I've addressed the issue elsewhere. And at least for Weiss, regression toward the mean is simply an artifact of measurement error, rather than a genuinue phenomenon. Certainly it's not something that should be allowed to stand in the way of an otherwise welcome eugenics program. 822661[/snapback] It takes a special brand of stupid to !@#$ things up beyond all recognition like you have done here. I probably wouldnt know tho, because i am so busy between work and anger management classes. Link to comment Share on other sites More sharing options...
Orton's Arm Posted November 2, 2006 Author Share Posted November 2, 2006 This is asinine. Your post makes no sense. "Assuming regression towards the mean is occurring, it means it won't happen. But it's not because it's measurement error, so I can dismiss it." You've taken stupid to a whole new level... Why not, instead of dismissing the presumed "measurement error" (sic), analyze the equation at the bulk limit where any measurement error averages out? That's a very easy thing to do, if you know any sort of math whatsoever. Of course, it still doesn't address the simple fact that the equation's wrong...but it'll at least prove to you that you're a fool. 822876[/snapback] "Analyze the equation at the bulk limit where any measurement error averages out?" Let me put this to you in simple terms: you have an equation that deals with children one by one. It deals with the individual parents of these children. There are several ways in which measurement error can occur: 1. The child's intelligence can be underestimated 2. The parents' intelligence can be underestimated 3. The child's intelligence can be overestimated 4. The parents' intelligence can be overestimated Let's do a thought experiment, and pretend these error terms are very strong. In fact, let's pretend they're so strong that no individual parent or child measurement has any validity whatsoever. In a world where measurement was as bad as this, whatever correlation might exist between parental and child I.Q. would be completely masked. It's masked on the individual level, and it's masked in the aggregate. But now measurement gets better; so there's now some relationship between a person's measured I.Q. and his or her real I.Q. This is the point where we can at least glimpse whatever correlation exists between parental and child I.Q. But only partially, because measurement error is still masking most of the relationship. If your measurement error was zero, you could truly see whether regression toward the mean was taking place. But due to the imperfect measurement systems we have, what appears to be regression toward the mean may actually be the result of measurement error partially occluding the true relationship between parental and child I.Q.s. So this is the argument against regression toward the mean. But there is also a chance regression toward the mean is real. Does this possibility mean a eugenics program wouldn't work? Not at all. Your earlier statements to the contrary notwithstanding, a heritability of 0.75 does in fact mean that, on average, 75% of a smart person's intelligence will be passed onto his or her children. So a couple with an average I.Q. of 200 will produce children with average I.Q.s of 175. Yes, there's a feeling of disappointment that the children probably won't be as smart as their parents, but at least they'll most likely be smarter than Ryan Leaf's kids. By encouraging the geniuses of the world to have more kids, the population will be smarter than it otherwise would have been. Link to comment Share on other sites More sharing options...
Orton's Arm Posted November 2, 2006 Author Share Posted November 2, 2006 It takes a special brand of stupid to !@#$ things up beyond all recognition like you have done here. I probably wouldnt know tho, because i am so busy between work and anger management classes. Thanks for once again seeming to say something without having said anything. Beyond the fact that you disagree, of course. But we knew that already, because you've repeated it a few hundred times. Link to comment Share on other sites More sharing options...
Bungee Jumper Posted November 2, 2006 Share Posted November 2, 2006 "Analyze the equation at the bulk limit where any measurement error averages out?" Let me put this to you in simple terms: you have an equation that deals with children one by one. It deals with the individual parents of these children. 823023[/snapback] No, it doesn't. It deals with the statistical variance of intelligence through generations. It is a feature of the equation itself that, when taken in the bulk limit (any bulk limit you care to analyze it in - I just did it for an extreme example of your eugenics program, where the general population has a specific mean and standard deviation, but the breeding population has a different one, with higher mean and smaller deviation) there is a regression to the mean. That's not "measurement error". That's math. It's Statistics 101; it's something you should have learned in your "statistics classes". The rest of your post is horseshit, because it stems from the above incorrect assumption that you know what you're talking about. If you weren't too stupid and lazy to do the math yourself, you could easily prove to yourself that you're wrong. And you're still defining heritability wrong. You can find the correct definition in this article, you !@#$ing bozo. Link to comment Share on other sites More sharing options...
bills_fan Posted November 2, 2006 Share Posted November 2, 2006 mechanic and teacher. i guess society would have been better off had my mom gotten her tubes tied, instead of working her ass off and going to night school while she was raising me by herself. I'm not even sure why my mom even bothered getting her Masters degree. she should have just accepted her place in society and done nothing. Maybe she would have made some money by winning "America's Stupidest Woman ©". ROTF...LMAO!! Post of the week!!! Link to comment Share on other sites More sharing options...
Orton's Arm Posted November 2, 2006 Author Share Posted November 2, 2006 No, it doesn't. It deals with the statistical variance of intelligence through generations. It is a feature of the equation itself that, when taken in the bulk limit (any bulk limit you care to analyze it in - I just did it for an extreme example of your eugenics program, where the general population has a specific mean and standard deviation, but the breeding population has a different one, with higher mean and smaller deviation) there is a regression to the mean. That's not "measurement error". That's math. It's Statistics 101; it's something you should have learned in your "statistics classes". The rest of your post is horseshit, because it stems from the above incorrect assumption that you know what you're talking about. If you weren't too stupid and lazy to do the math yourself, you could easily prove to yourself that you're wrong. And you're still defining heritability wrong. You can find the correct definition in this article, you !@#$ing bozo. 823037[/snapback] In practical terms, the bulk limit theorem states the following: suppose the true population is normally distributed. You begin sampling. At first, your sample will be a t-distribution, but as you add to your sample size the t-distribution will get taller and skinnier to look more and more like the normal distribution of the true population. In other words, the bigger your sample, the more closely it will resemble the true population. You appear to be confusing this with another statistical phenomenon: regression toward the mean: In statistics regression toward the mean, sometimes called the regression effect in other disciplines, is a principle stating a relationship between a measurement that is used to split a population into groups, and a second measurement of the groups thereby created. It states that given one measurement, another measurement — made only on a selection of those having a first measurement which is either higher or lower than the overall average — is expected to produce a result that is closer to the overall average than the observed value of the first measurement. The degree of regression toward the mean becomes more extreme, other things being equal, as the distance of the first measurement from the average becomes larger. The less reproducable the measurement, the more randomness there is in the quantity measured, the more there is expectation that regression toward the mean will be seen in the second measurement. Consider, for example, students who take a midterm and a final exam. Students who got an extremely high score on the midterm will probably get a good score on the final exam as well, but we expect their score to generally be closer to the average than their midterm score was. This is because there are more students with less than exceptional skill than there are students with exceptional skill. Because there are more un-exceptional students than exceptional students it is not very likely that a student with an un-exceptional score had exceptional abilitities but was unlucky. It is more likely that a student with an exceptional score was a less-skilled student that got lucky. There are simply more un-exceptional students that have a chance at getting lucky than there are exceptional students who might be unlucky. Link to comment Share on other sites More sharing options...
Bungee Jumper Posted November 2, 2006 Share Posted November 2, 2006 In practical terms, the bulk limit theorem states the following: suppose the true population is normally distributed. You begin sampling. At first, your sample will be a t-distribution, but as you add to your sample size the t-distribution will get taller and skinnier to look more and more like the normal distribution of the true population. You appear to be confusing this with another statistical phenomenon: regression toward the mean: 823091[/snapback] No, I'm not confused. I've published peer-reviewed papers on this sh--. Take your equation, and instead of pretending it applies to discrete individuals, calculate it with an x-bar of exp((x-10)^2)/1800), and (m+f)/2 of whatever gaussian distribution you care to use (I used exp((x^2-110)/200) - a breeding population with an IQ of 110, with a standard deviation of 10). That is the bulk limit of the system, you dimwit. Do the calculation - do it yourself, like I did, don't come back with "someone else says your wrong" if you won't do the math yourself - and tell me what happens. Link to comment Share on other sites More sharing options...
Orton's Arm Posted November 2, 2006 Author Share Posted November 2, 2006 I wrote: The formula which I cited is basically a mathematical definition of regression toward the mean. Later on, you wrote: No, it doesn't. It deals with the statistical variance of intelligence through generations. It is a feature of the equation itself that, when taken in the bulk limit (any bulk limit you care to analyze it in - I just did it for an extreme example of your eugenics program, where the general population has a specific mean and standard deviation, but the breeding population has a different one, with higher mean and smaller deviation) there is a regression to the mean. You followed it up with Take your equation, and instead of pretending it applies to discrete individuals, calculate it with an x-bar of exp((x-10)^2)/1800), and (m+f)/2 of whatever gaussian distribution you care to use (I used exp((x^2-110)/200) - a breeding population with an IQ of 110, with a standard deviation of 10). That is the bulk limit of the system, you dimwit. Do the calculation - do it yourself, like I did, don't come back with "someone else says your wrong" if you won't do the math yourself - and tell me what happens. I'm glad you've done the math to prove what I was already saying: the equation I mentioned is a mathematical definition of regression toward the mean. If you think I didn't know that already, go back and reread my above posts. The question is what's causing the observed regression toward the mean that the equation describes? As the article I found points out, measurement error produces the appearance of regression toward the mean. Link to comment Share on other sites More sharing options...
Bungee Jumper Posted November 2, 2006 Share Posted November 2, 2006 I wrote: Later on, you wrote: You followed it up with I'm glad you've done the math to prove what I was already saying: the equation I mentioned is a mathematical definition of regression toward the mean. If you think I didn't know that already, go back and reread my above posts. The question is what's causing the observed regression toward the mean that the equation describes? As the article I found points out, measurement error produces the appearance of regression toward the mean. 823145[/snapback] "Regression toward the mean" and "error" are TWO COMPLETELY DIFFERENT THINGS, YOU MORON!!! Where the hell is the "error" in that equation? Point to it. You can't. Because it's not there. Because in the bulk limit, as the sample size goes to infinity, the cumulative error averages to precisely zero. Which is why I did the math in the bulk limit (i.e. a gaussian distribution.) In fact, I even explicitly added an error term to it just now, just for kicks. Want to know what happened? Not regression toward the mean...the results diverge wildly from the mean, as the overall error rapidly overwhelms the other terms in the equation. Like I said: Do the math. Don't tell me what the math means, until you do the math. Link to comment Share on other sites More sharing options...
Ramius Posted November 2, 2006 Share Posted November 2, 2006 I wrote: Later on, you wrote: You followed it up with I'm glad you've done the math to prove what I was already saying: the equation I mentioned is a mathematical definition of regression toward the mean. If you think I didn't know that already, go back and reread my above posts. The question is what's causing the observed regression toward the mean that the equation describes? As the article I found points out, measurement error produces the appearance of regression toward the mean. 823145[/snapback] please tell me you are not saying that regression towards the mean is due to error. please. my gut cant bear the thought of that anymore. i have been brought to tears of laughter from reading that statement. Link to comment Share on other sites More sharing options...
Bungee Jumper Posted November 2, 2006 Share Posted November 2, 2006 please tell me you are not saying that regression towards the mean is due to error. please. my gut cant bear the thought of that anymore. i have been brought to tears of laughter from reading that statement. 823218[/snapback] You're only laughing because you have anger issues. Link to comment Share on other sites More sharing options...
Ramius Posted November 2, 2006 Share Posted November 2, 2006 You're only laughing because you have anger issues. 823222[/snapback] in my 8+ years now of data analysis using statistics, dating back to high school, 4 years of undergrad, and 4+ years of grad school, never once have i seen or heard of error causing data to regress toward the mean. Error will do a lot of things. it can shift your data, or in most cases, just make it a complete cluster!@#$. but it has never caused data to regress toward the mean. I'm just wondering. if intelligence is passed on from parents to child, judging by HA's claims in some of these threads, on that fateful night with mrs HA, how did his dad ever figure out where to put it? Link to comment Share on other sites More sharing options...
Bungee Jumper Posted November 2, 2006 Share Posted November 2, 2006 in my 8+ years now of data analysis using statistics, dating back to high school, 4 years of undergrad, and 4+ years of grad school, never once have i seen or heard of error causing data to regress toward the mean. Error will do a lot of things. it can shift your data, or in most cases, just make it a complete cluster!@#$. but it has never caused data to regress toward the mean. I'm just wondering. if intelligence is passed on from parents to child, judging by HA's claims in some of these threads, on that fateful night with mrs HA, how did his dad ever figure out where to put it? 823232[/snapback] Maybe he was adopted by smart parents. Because the correlation between the intelligence of parents and their adopted kids is zero, so that must mean that adopted kids with smart parents are really really dumb, since the intelligence isn't "heritable" (sic) with a correlation factor of zero... You know, it's actually a lot harder to string that gibberish together when you know you're abusing the terminology... Link to comment Share on other sites More sharing options...
Orton's Arm Posted November 3, 2006 Author Share Posted November 3, 2006 Given that some people appear to have had difficulty understanding the point I was making, I'll express my thoughts on regression toward the mean in simpler, easier to understand terms. Consider an I.Q. test. 60% of the people who take the test get the correct score. 20% get lucky, and score 10 points higher than they should. 20% get unlucky, and score 10 points lower than they should. Now imagine a room filled with people who scored a 140 on the test. Most of those people will indeed have I.Q.s of 140. But some of the people will have I.Q.s of 150, but who due to bad luck scored 10 points lower than they should have. There will be people in this room with I.Q.s of 130, but who through good luck scored a 140 on the test. Because there are a lot more people with I.Q.s of 130 than there are with I.Q.s of 150, the lucky 130s in the room will significantly outnumber the unlucky 150s. Therefore, the average intelligence of the people in the room will be lower than the 140 you measured. Suppose you were to ask everyone in the room to take a second I.Q. test. You'd expect the number of lucky people to balance out the number of unlucky people. Once you'd finished averaging the results of the second test, you'd know the true average I.Q. for the people in the room. That true average will be lower than 140. This is what the Wikipedia article meant when it described regression toward the mean. What did I mean when I wrote that regression toward the mean could be caused by error in measurement? Suppose that the expected value of a child's intelligence is the average of the two parents' I.Q.s. Now suppose that the people in the I.Q. 140 room had been kept there so long they started having kids with each other. Based on the I.Q. tests those people took, you'd expect their kids to have I.Q.s of 140. That was the measured I.Q. But the true average I.Q. in that room is lower--perhaps 135. Once those people's children start taking I.Q. tests, those children will get an average score of 135. This is what Weiss meant when he pointed out that measurement error could explain regression toward the mean. Link to comment Share on other sites More sharing options...
Recommended Posts