Regression toward the mean

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AND THUS YOU PROVED THAT ERROR REGRESSES TOWARD THE MEAN OF THE ERROR, AS I'VE BEEN SAYING.

 

The problem YOU have is that you think that represents regression to the mean of the population.  Because you're too !@#$ing stupid to know the difference. 

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The process of error regressing toward the mean of the error causes those who obtain extreme scores the first time around to, on average, obtain somewhat less extreme scores upon being retested. This is because those with very high scores on the first test are disproportionately lucky, and those with very low scores are disproportionately unlucky.

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If I make my font bigger, bolder, and redder than yours that makes me righter

[Orton's Arm]

If I make my font bigger, bolder, and redder than yours that makes me righter

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Make your face redder too, just to have all the bases covered.

[Ramius]

The process of error regressing toward the mean of the error causes those who obtain extreme scores the first time around to, on average, obtain somewhat less extreme scores upon being retested. This is because those with very high scores on the first test are disproportionately lucky, and those with very low scores are disproportionately unlucky.

 

If I make my font bigger, bolder, and redder than yours that makes me righter

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No, first you have to tell everyone how you post on mensa message boards, and claim that you are in the triple 9 club (which to me, says that theres a 99.9% chance you havent been laid)

 

then you are righter.

 

oh wait, you need ot link to hyperstats and wikipedia to be righter.

[Ramius]

See a psychiatrist.  Please.  You've gone beyond simple stupidity into the realm of mental disorder.

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wait, so me and you have been arguing this point all along, about regressing to the mean of the error, NOT the population. Holcombs tard has been arguing against it.

 

Now he flip-flops yet AGAIN, and claims he's right?

 

You are correct bungee. This man is definitely a candidate for a serious mental disorder.

[erynthered]

Your ability to distinguish between statistical fact and mental disorders makes you entirely qualified to continue in this discussion, and shoot me.

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Fixed......

 

 

Fer Christ sake, try Yoga for the brain. .45 calibers seem to work just fine from what I hear.

[Orton's Arm]

Fixed......

Fer Christ sake, try Yoga for the brain. .45 calibers seem to work just fine from what I hear.

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Have you ever tried shooting yourself in the head with a .45? Didn't think so. Get back to me when you have some firsthand experience in that area, and then we'll talk.

[Orton's Arm]

wait, so me and you have been arguing this point all along, about regressing to the mean of the error, NOT the population. Holcombs tard has been arguing against it.

 

Now he flip-flops yet AGAIN, and claims he's right?

 

You are correct bungee. This man is definitely a candidate for a serious mental disorder.

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My statement that I'm right isn't a claim. It's an observation of fact.

 

The fact that you're accusing me of flip-flopping shows a complete absence of even a rudimentary understanding of my post. What a surprise.

 

I'll spell things out more clearly, in terms hopefully even you can understand. Suppose you take a group of people who scored a 140 on an I.Q. test, and ask them to retake the test. That group will have a greater number of lucky 130s than unlucky 150s. You'd expect a lucky 130 to have his or her error term regress to zero on the retest. In other words, if your real I.Q. is 130, and if you got lucky and scored a 140 on the first test, your expected score on the retest is 130. The unlucky 150 is expected to score a 150 on the retest. Because individual people's error terms are expected to regress to a mean error of zero upon being retested, and because there are more lucky 130s than unlucky 150s, those who got a 140 on an I.Q. test will tend (on average) to score lower than 140 upon retaking the test.

[Bungee Jumper]

My statement that I'm right isn't a claim. It's an observation of fact.

 

The fact that you're accusing me of flip-flopping shows a complete absence of even a rudimentary understanding of my post. What a surprise.

 

I'll spell things out more clearly, in terms hopefully even you can understand. Suppose you take a group of people who scored a 140 on an I.Q. test, and ask them to retake the test. That group will have a greater number of lucky 130s than unlucky 150s. You'd expect a lucky 130 to have his or her error term regress to zero on the retest. In other words, if your real I.Q. is 130, and if you got lucky and scored a 140 on the first test, your expected score on the retest is 130. The unlucky 150 is expected to score a 150 on the retest. Because individual people's error terms are expected to regress to a mean error of zero upon being retested, and because there are more lucky 130s than unlucky 150s, those who got a 140 on an I.Q. test will tend (on average) to score lower than 140 upon retaking the test.

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And that's not regression toward the population mean.

 

What part don't you understand? It doesn't cause regression toward the mean. It doesn't even appear to cause regression toward the mean...unless your a hydrocephalic moron like yourself who arbitrarily discards meaningful data that doesn't agree with you.

[Orton's Arm]

And that's not regression toward the population mean. 

 

What part don't you understand?  It doesn't cause regression toward the mean.  It doesn't even appear to cause regression toward the mean...unless your a hydrocephalic moron like yourself who arbitrarily discards meaningful data that doesn't agree with you.

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Unfortunately for your argument, you've yet to present a single meaningful datum for me to discard.

 

True 130s outnumber true 150s. Therefore, in a group of people who scored 140 on an I.Q. test, lucky 130s will outnumber unlucky 150s. Have the group retake the test, and the group's average score will be closer to the mean than that original 140. What part of this don't you understand?

[Bungee Jumper]

Unfortunately for your argument, you've yet to present a single meaningful datum for me to discard.

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How about EVERYONE WHO SCORES BELOW YOUR ARBITRARY THRESHHOLD, DUMBASS?????

 

Jesus Christ...the effect you see, you only see because you're arbitrarily discarding that which cancels out the effect!!!! That's why it's not a real effect...because it's entirely in your head, invented when you decided that people who score less than your threshhold don't count...which causes the "error" to "regress toward the mean" the people you chose.

 

That doesn't make it regression toward the mean. That makes it stupid.

[Ramius]

How about EVERYONE WHO SCORES BELOW YOUR ARBITRARY THRESHHOLD, DUMBASS????? 

 

Jesus Christ...the effect you see, you only see because you're arbitrarily discarding that which cancels out the effect!!!!  That's why it's not a real effect...because it's entirely in your head, invented when you decided that people who score less than your threshhold don't count...which causes the "error" to "regress toward the mean" the people you chose. 

 

That doesn't make it regression toward the mean.  That makes it stupid. 

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Sounds strangely like his QB analysis. Discard all data that disproves your point. Your case is therefore much stronger.

[GG]

How about EVERYONE WHO SCORES BELOW YOUR ARBITRARY THRESHHOLD, DUMBASS????? 

 

 

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Maybe I'm asking him the wrong questions?

[Orton's Arm]

How about EVERYONE WHO SCORES BELOW YOUR ARBITRARY THRESHHOLD, DUMBASS????? 

 

Jesus Christ...the effect you see, you only see because you're arbitrarily discarding that which cancels out the effect!!!!  That's why it's not a real effect...because it's entirely in your head, invented when you decided that people who score less than your threshhold don't count...which causes the "error" to "regress toward the mean" the people you chose. 

 

That doesn't make it regression toward the mean.  That makes it stupid. 

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The fact that you're still questioning the arbitrary threshold this late in the game is absolutely absurd. Of course you need an arbitrarily defined threshold. The point--which I've been trying to drive into your skull for quite some time now, is that people who do exceptionally well on their first I.Q. test tend to do somewhat less well on the second test. The arbitrary threshold is necessary to give a mathematical definition for "people who did exceptionally well on the first test." Or exceptionally badly.

 

If 100 people got a 140 on an I.Q. test, and if those people are sitting down to retake it, the average score of that group will be less than 140. Yes, you need an arbitrarily-defined threshold (in this case, 140) to prove that. Why on earth you think the presence of such a threshold make this phenomenon not "real" is completely beyond me.

[/dev/null]

Discard all data that disproves your point. Your case is therefore much stronger.

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omg, it just occured to me. Holcombs Arm is really Tony Snow

[Orton's Arm]

Sounds strangely like his QB analysis. Discard all data that disproves your point. Your case is therefore much stronger.

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This from someone who:

a. Has not supplied any data with which to support his points.

b. Has not supplied any links with which to support his points.

c. Has not supplied any logical thought with which to support his points.

d. Has not supplied any statistical insight with which to support his points.

e. Has not supplied any statistical knowledge with which to support his points.

 

You have, however, supplied plenty of insults with which to support your points, so I guess that cancels out the above.

[Orton's Arm]

omg, it just occured to me.  Holcombs Arm is really Tony Snow 

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If I'm the White House press secretary, Ramius is the White House janitor.

[Bungee Jumper]

The fact that you're still questioning the arbitrary threshold this late in the game is absolutely absurd. Of course you need an arbitrarily defined threshold. The point--which I've been trying to drive into your skull for quite some time now, is that people who do exceptionally well on their first I.Q. test tend to do somewhat less well on the second test. The arbitrary threshold is necessary to give a mathematical definition for "people who did exceptionally well on the first test." Or exceptionally badly.

 

If 100 people got a 140 on an I.Q. test, and if those people are sitting down to retake it, the average score of that group will be less than 140. Yes, you need an arbitrarily-defined threshold (in this case, 140) to prove that. Why on earth you think the presence of such a threshold make this phenomenon not "real" is completely beyond me.

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Fine. Let's assume you're right (you're not...but let's assume you are). What is it supposed to mean?

[Orton's Arm]

Fine.  Let's assume you're right (you're not...but let's assume you are).  What is it supposed to mean?

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Suppose you have a man and a woman who each scored a 140 on an I.Q. test. Those two people are more likely to be lucky 130s than unlucky 150s. Let's say their expected score on a retest is 133.

 

They decide to have kids, and the kids score an average of 133 on their I.Q. tests. On the surface, it seems like the kids are closer to the population mean than their parents. But that's not necessarily the case. In searching for the most intelligent parents, you selected those with the highest I.Q. scores--and hence, a group of people that was disproportionately lucky on the test. This test taking luck won't be passed onto the next generation, so the kids will score somewhat lower on their I.Q. tests; even if they're just as smart as their parents.

[bartshan-83]

Can't...look...away

[Bungee Jumper]

Suppose you have a man and a woman who each scored a 140 on an I.Q. test. Those two people are more likely to be lucky 130s than unlucky 150s. Let's say their expected score on a retest is 133.

 

They decide to have kids, and the kids score an average of 133 on their I.Q. tests. On the surface, it seems like the kids are closer to the population mean than their parents. But that's not necessarily the case. In searching for the most intelligent parents, you selected those with the highest I.Q. scores--and hence, a group of people that was disproportionately lucky on the test. This test taking luck won't be passed onto the next generation, so the kids will score somewhat lower on their I.Q. tests; even if they're just as smart as their parents.

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So we're all the way back to "error causes regression toward the mean"...but with a twist, that the parent's error causes the children's regression toward the mean.

 

Which once again demonstrates: you can't tell the difference between error and normal population variance.