Bungee Jumper Posted November 10, 2006 Share Posted November 10, 2006 Care to donate to the kill a thread fund. 831291[/snapback] We'll just start a new one. He has a pathological need to look like an idiot, and I have a pathological need to egg him on. Link to comment Share on other sites More sharing options...
meazza Posted November 10, 2006 Share Posted November 10, 2006 We'll just start a new one. He has a pathological need to look like an idiot, and I have a pathological need to egg him on. 831292[/snapback] HA knows less about statistics than I do. You should seriously donate some of your time to saving the world or something Link to comment Share on other sites More sharing options...
Bungee Jumper Posted November 10, 2006 Share Posted November 10, 2006 HA knows less about statistics than I do. You should seriously donate some of your time to saving the world or something 831298[/snapback] But I hate people. Why the !@#$ would I do that? Hear that, KurtGoebbels? I hate people. Put that in your sig. Link to comment Share on other sites More sharing options...
meazza Posted November 10, 2006 Share Posted November 10, 2006 But I hate people. Why the !@#$ would I do that? Hear that, KurtGoebbels? I hate people. Put that in your sig. 831305[/snapback] This might be something else going on your war crimes trial. Link to comment Share on other sites More sharing options...
Orton's Arm Posted November 10, 2006 Share Posted November 10, 2006 And you don't understand the article, because it's not error causing the effect. Error has nothing to do with it; it's a feature of a normally distributed sample. The regression is not because of "error", the regression is because it's a statistical function, not a deterministic one. Which is your main hang-up in this entire discussion. You can't define "statistics". It's not deterministic, it's probabilistic...which is what causes regression, and it's not error either. So we'll just add that to the list of words you can't define: "deterministic", "statistical", and "probability". Hell, let's just say you can't define "math". 831286[/snapback] You are wrong. And not merely wrong, but wrong in a way which shows zero comprehension of, oh, I don't know, the last five pages, the Monte Carlo simulation, two or three links, and probably some other stuff I'm forgetting. This has gone far beyond ridiculous. The conclusion that the expected score on the second test is below 750 depends on the assumption that scores on the test are, at least in some small part, due to chance or luck. . . . Define the mean of these 1,000 scores as the person's "true" score. On some tests, the person will have scored below the "true" score; on these tests the person was less lucky than average. On some tests the person will have scored above the true score; on these tests the person was more lucky than average. Consider the ways in which someone could score 750. There are three possibilities: (1) their "true" score is 750 and they had exactly average luck, (2) their "true" score is below 750 and they had better than average luck, and (3) their "true" score is above 750 and they had worse than average luck. Consider which is more likely, possibility #2 or possibility #3. There are very few people with "true" scores above 750 (roughly 6 in 1,000); there are many more people with true scores between 700 and 750 (roughly 17 in 1,000). Since there are so many more people with true scores between 700 and 750 than between 750 and 800, it is more likely that someone scoring 750 is from the former group and was lucky than from the latter group and was unlucky. Do you finally understand now? You are trying to measure someone's true score. But due to random chance, or luck, there may well have been a little incorrectness in measuring that person's true score. It's this inaccuracy or error in the measurement system which allows people to get "lucky" or "unlucky" on tests instead of being measured correctly. If measurement was always 100% accurate, there would be no regression toward the mean. Someone who got a 750 on the math section of the SAT the first time he took the test would get a 750 again the second time, and the third, etc. Regression toward the mean happens because someone who scored a 750 just might be a person with a true score of 725 who got lucky when taking the test. Granted, he might also be a true 775 who got unlucky, but the odds of this are less likely; because there are fewer true 775s than true 725s. Link to comment Share on other sites More sharing options...
Orton's Arm Posted November 10, 2006 Share Posted November 10, 2006 HA knows less about statistics than I do. You lack self-confidence, which is why you're trying to ingratiate yourself with Bungee Jumper. Too bad the leader you picked doesn't know beans about regression toward the mean. Link to comment Share on other sites More sharing options...
meazza Posted November 10, 2006 Share Posted November 10, 2006 You lack self-confidence, which is why you're trying to ingratiate yourself with Bungee Jumper. Too bad the leader you picked doesn't know beans about regression toward the mean. 831324[/snapback] I lack self-confidence Yeah that must be it. You don't know anything about normal distribution, regression and you're telling me I lack self-confidence. Seriously, get a hobby and if this is your hobby, well you suck at it. Link to comment Share on other sites More sharing options...
Orton's Arm Posted November 10, 2006 Share Posted November 10, 2006 Yeah that must be it. You don't know anything about normal distribution, regression And you think this because Bungee Jumper and Ramius said so. As I said, you lack self-confidence. Link to comment Share on other sites More sharing options...
meazza Posted November 10, 2006 Share Posted November 10, 2006 And you think this because Bungee Jumper and Ramius said so. As I said, you lack self-confidence. 831331[/snapback] Actually no. I didn't even read their posts, I read yours. I know what these things are because i was stuck studying them for 2 years while getting my BA in economics. And plus, after every sh------- exam, someone would say "i hope he bell curves it" Now stop calling me a follower, and give this crusade up. Link to comment Share on other sites More sharing options...
Orton's Arm Posted November 10, 2006 Share Posted November 10, 2006 Actually no. I didn't even read their posts, I read yours. I know what these things are because i was stuck studying them for 2 years while getting my BA in economics. And plus, after every sh------- exam, someone would say "i hope he bell curves it" Now stop calling me a follower, and give this crusade up. 831332[/snapback] If you want me to stop calling you a follower, I suggest you stop acting like one. As for your claim that you've gone through this thread reading my posts but not any of theirs . . . um . . . yeah. Whatever dude. You actually quoted one of Bungee Jumper's posts on this very page. Link to comment Share on other sites More sharing options...
meazza Posted November 10, 2006 Share Posted November 10, 2006 If you want me to stop calling you a follower, I suggest you stop acting like one. As for your claim that you've gone through this thread reading my posts but not any of theirs . . . um . . . yeah. Whatever dude. You actually quoted one of Bungee Jumper's posts on this very page. 831338[/snapback] Ya, the posts that are about 1 sentence long. I'm too lazy to read the long ones but I actually read yours. Now stop trying to prove a point that isn't there. Link to comment Share on other sites More sharing options...
Bungee Jumper Posted November 10, 2006 Share Posted November 10, 2006 You are wrong. And not merely wrong, but wrong in a way which shows zero comprehension of, oh, I don't know, the last five pages, the Monte Carlo simulation, two or three links, and probably some other stuff I'm forgetting. This has gone far beyond ridiculous.Do you finally understand now? You are trying to measure someone's true score. But due to random chance, or luck, there may well have been a little incorrectness in measuring that person's true score. It's this inaccuracy or error in the measurement system which allows people to get "lucky" or "unlucky" on tests instead of being measured correctly. If measurement was always 100% accurate, there would be no regression toward the mean. Someone who got a 750 on the math section of the SAT the first time he took the test would get a 750 again the second time, and the third, etc. Regression toward the mean happens because someone who scored a 750 just might be a person with a true score of 725 who got lucky when taking the test. Granted, he might also be a true 775 who got unlucky, but the odds of this are less likely; because there are fewer true 775s than true 725s. 831320[/snapback] CHANCE AND LUCK ARE A FUNCTION OF PROBABILITY AS A FEATURE OF A STATISTICAL DISTRIBUTION! THAT IS NOT THE SAME THING AS ERROR! What part of "probability is not error" are you not understanding? Your "Monte Carlo" (sic) simulation shows regression toward the mean of your normally distributed error because of the defined probabilistic nature of the error: the guy with a "real IQ" of 160 who scores 170 does so because he experiences extremely unlikely error in his favor, not because he's scoring an extremely unlikely IQ score. He is more likely to score closer to 160 next time not because the measured IQ is regressing toward a mean of 100, but because the error is regressing toward the mean error of 0!!!!! Your simulation is measuring the wrong !@#$ing thing!!!!! Is there anyone else out there who isn't understanding me? Am I being unclear, or is Holcomb's Arm really this much of a blockhead? Link to comment Share on other sites More sharing options...
Orton's Arm Posted November 10, 2006 Share Posted November 10, 2006 Ya, the posts that are about 1 sentence long. I'm too lazy to read the long ones but I actually read yours. Now stop trying to prove a point that isn't there. 831339[/snapback] Did you also read the HyperStat article to which I linked? Its length is quite reasonable, and it's an easy read as far as stats go. I suggest you read it, and then go back through the last five pages or so of Bungee Jumper's and Ramius's posts. I want someone other than me to see how very badly those two have embarrassed themselves. Link to comment Share on other sites More sharing options...
meazza Posted November 10, 2006 Share Posted November 10, 2006 Did you also read the HyperStat article to which I linked? Its length is quite reasonable, and it's an easy read as far as stats go. I suggest you read it, and then go back through the last five pages or so of Bungee Jumper's and Ramius's posts. I want someone other than me to see how very badly those two have embarrassed themselves. 831349[/snapback] Don't feel like it. I did read a few of yours and even if your article makes sense, you seem to have a hard time understanding it. Now back to studying. Link to comment Share on other sites More sharing options...
Orton's Arm Posted November 10, 2006 Share Posted November 10, 2006 CHANCE AND LUCK ARE A FUNCTION OF PROBABILITY AS A FEATURE OF A STATISTICAL DISTRIBUTION! THAT IS NOT THE SAME THING AS ERROR! What part of "probability is not error" are you not understanding? Your "Monte Carlo" (sic) simulation shows regression toward the mean of your normally distributed error because of the defined probabilistic nature of the error: the guy with a "real IQ" of 160 who scores 170 does so because he experiences extremely unlikely error in his favor, not because he's scoring an extremely unlikely IQ score. He is more likely to score closer to 160 next time not because the measured IQ is regressing toward a mean of 100, but because the error is regressing toward the mean error of 0!!!!! Your simulation is measuring the wrong !@#$ing thing!!!!! Is there anyone else out there who isn't understanding me? Am I being unclear, or is Holcomb's Arm really this much of a blockhead? 831345[/snapback] Your post is of course incorrect, but less so than usual. If the lightbulb in your head had previously been turned off, it's now on its lowest setting. In a few more pages it will perhaps be at its brightest; and then you'll see exactly how wrong you've been. You probably won't admit it, but you'll know it. And that will be enough. My Monte Carlo simulation shows that someone who scores well on a test involving mostly intelligence, but also a little luck, will tend to do a little worse the second time around. If you want me to put this in the language you've apparently developed, the mean error for the Threshold group is positive the first time around (on average, they got lucky) and regresses toward a mean error term of zero the second time around (on average they are neither lucky nor unlucky the second time they take the test). Why was the Threshold group, on average, luckier than the non-Threshold group on that first test? Because the Threshold group was selected based on its high scores on the first test, which in part are a function of luck. Link to comment Share on other sites More sharing options...
Bungee Jumper Posted November 10, 2006 Share Posted November 10, 2006 Your post is of course incorrect, but less so than usual. If the lightbulb in your head had previously been turned off, it's now on its lowest setting. In a few more pages it will perhaps be at its brightest; and then you'll see exactly how wrong you've been. You probably won't admit it, but you'll know it. And that will be enough. My Monte Carlo simulation shows that someone who scores well on a test involving mostly intelligence, but also a little luck, will tend to do a little worse the second time around. If you want me to put this in the language you've apparently developed, the mean error for the Threshold group is positive the first time around (on average, they got lucky) and regresses toward a mean error term of zero the second time around (on average they are neither lucky nor unlucky the second time they take the test). Why was the Threshold group, on average, luckier than the non-Threshold group on that first test? Because the Threshold group was selected based on its high scores on the first test, which in part are a function of luck. 831376[/snapback] Exactly. The problem is that that doesn't mean what you think it means. You're not measuring the regression of the IQ, you're mesauring the regression of the error. You think you're measuring the regression of the IQ because you specifically and arbitrarily chose a subset of data where the regression of the error is toward the mean of the IQ. That does not make it regression of the IQ score. Like I keep saying: YOU ARE MEASURING THE WRONG !@#$ING THING, DUMBASS!!!! Link to comment Share on other sites More sharing options...
Orton's Arm Posted November 10, 2006 Share Posted November 10, 2006 Don't feel like it. I did read a few of yours and even if your article makes sense, you seem to have a hard time understanding it. I seem to have a hard time understanding it? I've only been trying to communicate that exact same message for the last five or ten pages! What's next? Are you going to tell us that Ronald Reagan had a hard time understanding that communism might not always be a good thing? Or that Al Gore had a hard time understanding that he nearly won the presidency back in 2000? Please, do share. Link to comment Share on other sites More sharing options...
meazza Posted November 10, 2006 Share Posted November 10, 2006 I seem to have a hard time understanding it? I've only been trying to communicate that exact same message for the last five or ten pages! What's next? Are you going to tell us that Ronald Reagan had a hard time understanding that communism might not always be a good thing? Or that Al Gore had a hard time understanding that he nearly won the presidency back in 2000? Please, do share. 831386[/snapback] Forget it. Good luck with the bungee jumper and windex supplier. Link to comment Share on other sites More sharing options...
Orton's Arm Posted November 10, 2006 Share Posted November 10, 2006 Exactly. The problem is that that doesn't mean what you think it means. You're not measuring the regression of the IQ, you're mesauring the regression of the error. You think you're measuring the regression of the IQ because you specifically and arbitrarily chose a subset of data where the regression of the error is toward the mean of the IQ. That does not make it regression of the IQ score. Like I keep saying: YOU ARE MEASURING THE WRONG !@#$ING THING, DUMBASS!!!! 831384[/snapback] I am measuring the regression of I.Q. scores. Someone who obtains a score that's far from the mean on the first test, more often than not, will get a score that's closer to the mean upon taking a second test. This is what the article meant when it said that someone who scored a 750 on the math section the first time around will, on average, get a 725 upon taking the retest. Link to comment Share on other sites More sharing options...
Bungee Jumper Posted November 10, 2006 Share Posted November 10, 2006 I seem to have a hard time understanding it? I've only been trying to communicate that exact same message for the last five or ten pages! What's next? Are you going to tell us that Ronald Reagan had a hard time understanding that communism might not always be a good thing? Or that Al Gore had a hard time understanding that he nearly won the presidency back in 2000? Please, do share. 831386[/snapback] That's what he means by "you seem to have a hard time understanding it". You're communicating a completely different message, because you can't differentiate "probability" from "error". And it's really not that hard: You roll a pair of dice, it's probabilistic. When they stop moving, it's deterministic. The system has an expectation value (a "mean") of 7. Rolls subsequent to very low or very high rolls (2 or 3, or 11 or 12) will tend to regress toward the mean not because dice are error-prone or inaccurate - they're not, they're very accurate and not the least bit subject to error. It's because there's only 3 ways to roll a 2 or 3, and 33 other possibilities the next time you roll. Regression toward the mean happens because your current measure is deterministic, but your future measure is probabilistic. That's probability, not error. It's really !@#$ing simple. Like I said, I can teach that to a three year old. Why the !@#$ do you have so much trouble with it? Link to comment Share on other sites More sharing options...
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