[from Gary Cziko 930411.2210 GMT]

Here are the results on the my poll on whether the perceptual signal

contains useful information for a control system about the disturbance.

800 NO INFORMATION

300 YES INFORMATION

100 MAYBE INFORMATION

100 TOO EARLY INFORMATION

100 CAN'T ANSWER, DON'T KNOW WHAT 'INFORMATION ABOUT' IS

100 WHAT'S IT TO ME?

Although the results look decisive for NO INFORMATION, a chi-square test

using just the YES and NO categories yields a chi-square of 2.273 which is

not significant (at alpha = .05; df = 1). Therefore, the matter is still

unsettled. Further discussion may now proceed.

Note. The results of the poll are reported in hundredths of votes in order

to make the results initially appear more impressive than they actually

are.

P.S. I just realized something interesting in doing this chi-square test.

I did the test using the number of votes, not hundredths of votes. If I

had used the votes multiplied by 100, the results would have been

statistically significant with a whopping chi-square of 186.36. I never

realized before that the chi-square test was sensitive to how the results

are counted. So you can always get a statistically signficant chi-square

by reporting the results in fractions of frequencies. This is a decided

advantage over other inferential statistical tests for which in order to

get a statistically signficant finding you have to have a large enough

sample (which takes much more work than just multiplying your frequencies

by 10 or 100 or 1,000). In either case, however, it's nice to know that

you can always get statistically significant results (exciting findings

like rejecting the null hypothesis that some population correlation

coefficient is not zero) if you try hard enough (probably another reason

why "statistical" psychology and social science is better than PCT for

getting published and getting tenure).

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Greg Williams (930410) boldly flirts with the possibility of having to

fetch the CSGnet archive files on his own by stating:

You're beating a dead unicorn. I have always agreed that to study

mass phenomena, mass statistics are appropriate.No, I was beating (on?) a live Gary Cziko (to whom I sent the original

post, directly), whose commentI agree. It's called the STATISTICAL method, or the METHOD OF RELATIVE

FREQUENCIES. Pretty useless as real science goes (althought the

behavioral sciences seem to like it alot.implied to me that HE (NOT YOU, unless you're ghost-writing Gary's

direct posts to me!) thinks that mass statistics are inappropriate to

"real science." Maybe Gary actually agrees with you (and me, too) that

"to study mass phenomena, mass statistics are appropriate." I suppose he

does, even though he didn't answer my questions about his beliefs in this

regard. At any rate, if he does agree with us, it would appear that he

doesn't count studying mass phenomena as "real science."

Greg, my remarks on statistics were sent directly to you and not intended

for dissemination to CSGnet. They WERE intended to be somewhat facetious

and humorous in the spirit of other private exchanges we have had.

Yes, I most certainly agree that inferential statistics are useful for

doing research about populations, but only when one has a random sample

from that population (or can provide convincing evidence that the sample is

representative of the population of interest, even if not random)

But while I am happy to admit that inferential statistics can be usefully

employed by scientists interested in populations, I cannot recall ever

having come across a study in psychology or education psychology which has

used inferential statistics based on (a) random sample(s) of some

population(s) of theoretical or practical interest. All the studies I have

seen use SAMPLES OF CONVENIENCE (e.g., all nonabsent Boredom University

students enrolled in Psych 100 on a given day) and then generalize the

results to populations such as "fourth graders" or "people" or "men" or

"women"--just like the inane chi-square test I computed above for the poll

results!

Indeed, Joel Judd did his doctoral dissertation on reviewing several of the

most influential studies done on second language acquisition, and he

couldn't find a single useful study among them (if I remember correctly).

No random samples. Statements about how individuals learn languages when

not a single individual was investigated as a specimen.

Perhaps you can point out to me some psychological studies (ed psych would

even be better) which have used inferential statistics properly in this

respect--I would love to have some good examples to show to the students in

my intro statistics class to show how inferential statistics can be

properly used in ed. psych. Maybe such use of statistics can provide

answers to the types of questions I'm interested in (e.g., how learning in

school takes place) and I've been looking in the wrong journals.--Gary

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Gary Cziko Telephone: 217-333-8527

Educational Psychology FAX: 217-244-7620

University of Illinois E-mail: g-cziko@uiuc.edu

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