Orton's Arm

This is your second attempt this page to start an argument with me.

Upstate New York's problems are clear. Wasteful and harmful social programs have resulted in far too high a tax rate. Misguided government involvement has resulted in too many regulations. Moreover, the state is very lawyer-friendly and labor union-friendly. These problems have served to drive out businesses; which have driven out jobs. That's why Upstate New York has been on a decline since before most residents were born. How many of these problems could a liberal talk show reasonably be expected to combat? Liberal people, driven by a liberal point of view, created each of the problems described above. Addressing New York State's problems with a liberal point of view is like using cyanide to treat food poisoning.

Your post doesn't ring true. Probably the most widely agreed-upon thing on these boards is that the Bills' line has generally been a problem. I certainly don't remember anyone saying that the sole problem with the Bills' offense was at quarterback.

Oddly, when I wrote about people setting up barriers of aggressive ignorance, you were one of those I had in mind.

I don't feel smug. I feel disgruntled at the fact that so many people out there are aggressively ignorant.

The aggressive ignorance I encountered over on the PPP board was mind-boggling. It seemed like the only people who understood what I was saying were Wraith (who works with stats for a living), and maybe Dave B. Few if any of the other participants were able to understand this article. Unfortunately, that lack of understanding wasn't accompanied by anything even remotely resembling humility or an ability to listen.

You might want to go here.

I appreciate the advice, but I'm not sure how well even you could do with this particular crowd. You're welcome to take a crack at it though. The underlying phenomenon is described here. If you're able to get that particular message through the barriers of extremely aggressive ignorance people have set up, I'll think of you as the teacher of the year.

If I had a dime for each time I encountered the behaviors you described, I'd be Bill Gates.

I suppose that's one way of putting it. If someone doesn't understand me the first time I say something, I have a tendency to explain it again. I happened to come across a relatively counter-intuitive statistical phenomenon, which I mentioned in passing over on the PPP boards. I thought--wrongly--that others would quickly and clearly grasp what this phenomenon was all about. Most people didn't, so I had to explain it again. It was rather annoying to have been ridiculed for making objectively true statements. To remove any doubt, I provided links to a number of independent, credible websites which supported what I'd been saying. These links were generally misunderstood or ignored. I tried so hard to teach people about that phenomenon, and most still don't understand it. I've never been a teacher, but I feel I now have a better understanding of some of the frustrations they must endure.

What's interesting about the playoff scenario you've outlined is that if the Dolphins lose to the Jets, the Bills stay home for the playoffs. Period, end of story. I don't often say this, but, um, go Fish!

Talk about the pot calling the kettle black!

You're a sore loser. I've pretty much won that statistics debate over in PPP--both the binomial portion (a small win) and the appearance of regression toward the mean portion (a 50+ page win). You've embarrassed yourself enough by losing, don't make it worse by having it said you lost to an idiot. That said, I voted for Fins fans being dumber than JSP. For one thing, JSP has had enough grief lately by winning that tard of the week award. In addition, we're talking about Fins fans!

Your second distribution would look more like this 2,3: 0, 0, 0 4 - 12: 1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1 Is the above a reasonable approximation for the normal distribution? I think not. Bungee Jumper clearly had your first chart in mind when he talked about his so-called "binomial distribution," and did not intend it to be converted into the single real binomial distribution I've described above, nor the series of binomial distributions Wraith described.

You've surely heard the saying, "My country. Right or wrong, but my country." Sometimes I get the feeling that there are people on this thead saying, "Bungee Jumper. Right or wrong, but Bungee Jumper." In the quotes I posted above, Bungee Jumper announced he was using "the binomial distribution of possible values [for rolling a pair of dice] as a reasonable approximation of a normal distribution." You can't do that unless you're dividing up those dice rolling results into eleven categories. Which means his conception of a binomial distribution was mistaken.

Where's the rest? here, at the bottom of the page: And you can go here, first post of the page, to see this quote: Again, Bungee Jumper didn't know that one of the requirements for a binomial distribution is that you group all your observations into only two categories. I had to tell him otherwise. Which would be fine, if he didn't incessantly (and falsely) accuse me of not understanding basic statistical terminology.

Too bad you didn't understand the links which you posted. A binomial distribution must have only two categories--"success" and "failure" if you will. Bungee Jumper was using eleven categories in his dice rolling example. Even you should have the mental capacity to see the difference between two categories and eleven categories.

Too bad for you guys that saying things doesn't make them so. Like it or not, a binomial distribution has a very specific definition; which Bungee Jumper was unaware of until I provided the Hyperstats link and the textbook quote. You are required to classify your results into only two categories to use a binomial distribution; instead of using eleven categories as Bungee Jumper was doing in his so-called "binomial distribution."

The example is correct, as applied by the authors of the website. They were interested in the probability of a single event (in this case, rolling a 3). They categorized each observation into one of two categories: 3 and not-3. This is consistent with the definition of a binomial distribution. Bungee Jumper, on the other hand, was using the rolling of a pair of dice as an approximation for the normal distribution. He categorized his possible results into eleven categories; and that's not the binomial distribution he said it was.

Why I continue to debate someone who enjoys throwing around childish insults far more than he enjoys talking about stats is far beyond me. I'll put this to you again. You take a thin slice of the population, based on people's test scores the first time they took the imperfect test. Assuming the test scores you're looking for are above the population mean, the thin slice should contain a greater number of people who got lucky than people who got unlucky. Given that fact, the average I.Q. for the people in the thin slice is somewhat lower than the average test score for the people in the slice. Do you agree or disagree?

If you click on the "binomial distribution" link in that website, you'll see the following text: Two possible outcomes for each trial--think flipping a coin. Not rolling a pair of dice.

This from someone who until recently thought that rolling a pair of dice would produce a binomial distribution. In case you're wondering, yes you'll have to hear about that every time you question my understanding of terminology or vocabulary. In my earlier post, the word "average" referred to the average member of the thin slice, and not the average member of the population. I think you understood that when you posted, but couldn't resist the temptation to turn this away from a statistics debate, and into a "you're an idiot because you don't understand term X" debate.

Losman's been playing better lately, but let's not get the annointing oil out just yet.

Which is another way of saying that if the offensive line gets dominated in some upcoming game, we should expect Losman to go back to his old ways. Is this really the point you're trying to make?

My example makes it perfectly obvious that even in a thin slice, the average person is closer to the population mean than his or her test score would indicate. (Assuming an imperfect test, of course.) Retest the people in the thin slice, and their test scores will, on average, be somewhat closer to the population's mean. Is there anything in this paragraph with which you disagree?