I am fairly new to teaching psychology (my second semester) and to this list but hopefully someone can help me. Here is the scenario: A child is playing with a toy and throws it. The parent reacts by taking the toy away. I thought this would be a reasonable example for punishment since it is likely to decrease the throwing. However, as I was discussing it, I realized that it could also be explained as negative reinforcement since the negative condition being "removed" (as I explained it to my students) is the child's throwing, while the behavior of the parent taking the toy away is likely to be strengthened; this would fit the bill for the typical definition of negative reinforcement. Am I completely off-base here? I thought that reinforcement and punishment were mutually exclusive, so how can this be better explained?
Thanks in advance for the help, Deborah Deitcher ----- Original Message ----- From: "Teaching in the Psychological Sciences digest" <[EMAIL PROTECTED]> To: "tips digest recipients" <[EMAIL PROTECTED]> Sent: Wednesday, February 26, 2003 12:00 AM Subject: tips digest: February 25, 2003 > TIPS Digest for Tuesday, February 25, 2003. > > 1. new email: please change > 2. Re: z-score woes > 3. Re: psychology of crimal conduct mulitmedia resources > 4. Re: psychology of crimal conduct mulitmedia resources > 5. Re: z-score woes > 6. RE: z-score woes > 7. SD Woes > 8. student request > 9. Re: student request > 10. Re: student request > 11. Re: SD Woes > 12. Re: student request > 13. Re: student request > 14. RE: student request > 15. RE: student request > 16. Re: SD Woes > 17. RE: z-score woes > 18. FW: A Class Divided, (check local listings) on PBS > 19. Eating disorders - PBS special > 20. RE: SD Woes > 21. Re: z-score woes > 22. RE: z-score woes > 23. Re: parapsychology > 24. Question on a quote & need reference > 25. We've got it all wrong > 26. Re: SD Woes > 27. Re: We've got it all wrong > 28. Re: SD Woes > 29. Re: We've got it all wrong > 30. What is an experiment? > > ---------------------------------------------------------------------- > > Subject: new email: please change > From: Ferreira Alves <[EMAIL PROTECTED]> > Date: Tue, 25 Feb 2003 11:48:57 +0000 > X-Message-Number: 1 > > This is a multi-part message in MIME format. > > --Boundary_(ID_xJvggc4Z7hEuaeEecMyE/Q) > Content-type: text/plain; charset=iso-8859-1 > Content-transfer-encoding: quoted-printable > > Dear Colleagues > > I wish to subscribe to psychteach for a new email. My usual email = > changed . > Then > my new email is > > [EMAIL PROTECTED] > > My old email was > [EMAIL PROTECTED] > > many thanks for your understanding > > Jos=E9 Ferreira-Alves > Department of psychology > University of Minho > Campus de Gualtar > 4700 Braga > Portugal > email: [EMAIL PROTECTED] > Tel. +351253604247 > fax: +351253678987 > > --Boundary_(ID_xJvggc4Z7hEuaeEecMyE/Q) > Content-type: text/html; charset=iso-8859-1 > Content-transfer-encoding: quoted-printable > > <!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.0 Transitional//EN"> > <HTML><HEAD> > <META http-equiv=3DContent-Type content=3D"text/html; = > charset=3Diso-8859-1"> > <META content=3D"MSHTML 6.00.2800.1126" name=3DGENERATOR> > <STYLE></STYLE> > </HEAD> > <BODY bgColor=3D#ffffff> > <DIV>Dear Colleagues<BR><BR>I wish to subscribe to psychteach for a new = > email.=20 > My usual email changed .<BR>Then<BR>my new email is<BR><BR><A=20 > href=3D"mailto:[EMAIL PROTECTED]">[EMAIL PROTECTED]</A><BR><BR>My = > old email=20 > was<BR><A=20 > href=3D"mailto:[EMAIL PROTECTED]">[EMAIL PROTECTED]</A><BR><BR>= > many=20 > thanks for your understanding<BR><BR>Jos=E9 Ferreira-Alves<BR>Department = > of=20 > psychology<BR>University of Minho<BR>Campus de Gualtar<BR>4700=20 > Braga<BR>Portugal<BR>email: <A=20 > href=3D"mailto:[EMAIL PROTECTED]">[EMAIL PROTECTED]</A><BR>Tel.=20 > +351253604247<BR>fax: +351253678987<BR></DIV> ---<BR> You are currently subscribed to tips as: [EMAIL PROTECTED]<BR> To unsubscribe send a blank email to [EMAIL PROTECTED] </BODY></HTML> > > --Boundary_(ID_xJvggc4Z7hEuaeEecMyE/Q)-- > > ---------------------------------------------------------------------- > > Subject: Re: z-score woes > From: Robert Grossman <[EMAIL PROTECTED]> > Date: Tue, 25 Feb 2003 07:39:11 -0500 > X-Message-Number: 2 > > This is a multi-part message in MIME format. > --------------72EF412CDB8E63FE07544DF0 > Content-Type: text/plain; charset=us-ascii > Content-Transfer-Encoding: 7bit > > > > > Subject: z-score woes > > "I have a student who just does not understand z-scores. I have met with him for at least two hours outside of class and he still doesn't understand the concept. In particular, he doesn't seem to understand why you need to include standard deviation in the calculation of z-scores. "Why can't you just compare the raw > > scores?" is his frequent question." > > Rod, > > I would suggest you give him a real problem we face in our admissions process. Say you have two students and can only admit one. They should be equal in most respects but have very different test scores--one has a SAT scores V 500 + M 450 = 950 while the other has an ACT Composite of 32. Which has a better chance of doing well in college? This isn't raw score comparison but the numbers paint one picture while the z-scores give quite a different picture. > > bob grossman > [EMAIL PROTECTED] > Kalamazoo College > > > --------------72EF412CDB8E63FE07544DF0 > Content-Type: text/x-vcard; charset=us-ascii; > name="grossman.vcf" > Content-Transfer-Encoding: 7bit > Content-Description: Card for Robert Grossman > Content-Disposition: attachment; > filename="grossman.vcf" > > begin:vcard > n:Grossman;Robert > tel;fax:616-337-7030 > tel;work:616-337-7108 > x-mozilla-html:TRUE > url:http://www.kzoo.edu/psych/ndex.htm > org:Kalamazoo College;Psychology > adr:;;1200 Academy Street;Kalamazoo;Michigan;49006;USA > version:2.1 > email;internet:[EMAIL PROTECTED] > title:Professor > fn:Bob Grossman, Ph.D > end:vcard > > --------------72EF412CDB8E63FE07544DF0-- > > > ---------------------------------------------------------------------- > > Subject: Re: psychology of crimal conduct mulitmedia resources > From: Robert Grossman <[EMAIL PROTECTED]> > Date: Tue, 25 Feb 2003 07:50:17 -0500 > X-Message-Number: 3 > > This is a multi-part message in MIME format. > --------------5C290250737FD5BC4614FF4F > Content-Type: text/plain; charset=us-ascii > Content-Transfer-Encoding: 7bit > > > > Rachael Collie wrote: > > > Hi, I'm keen on anyone's knowledge of good video or CDRom resources > > relevant to the psychology of criminal conduct. Its for teaching at 3rd > > and 4th year levels of psychology. > > Rachael, > > My favorite video is the Frontline video on Kenneth Bianchi titled "Mind of a > Murder." It is available now in a two video set. It takes two hours to show > both tapes but it gives students a serious look at how clever a sociopath can > be. Since my main goal for my students is that they not be naive as to the > manipulative skill of criminals this two hour series is worth it. If you > want more information on where to get the tapes and the costs let me know. I > don't have the info at my desk right now but I can find it. This is the case > where a serial killer was able to convince some psychologists and > psychiatrists that he had a multiple personality while the judge and jury > were convinced he was faking by another set of psychiatrists and > psychologists. > > Bob Grossman > [EMAIL PROTECTED] > Kalamazoo College > > --------------5C290250737FD5BC4614FF4F > Content-Type: text/x-vcard; charset=us-ascii; > name="grossman.vcf" > Content-Transfer-Encoding: 7bit > Content-Description: Card for Robert Grossman > Content-Disposition: attachment; > filename="grossman.vcf" > > begin:vcard > n:Grossman;Robert > tel;fax:616-337-7030 > tel;work:616-337-7108 > x-mozilla-html:TRUE > url:http://www.kzoo.edu/psych/ndex.htm > org:Kalamazoo College;Psychology > adr:;;1200 Academy Street;Kalamazoo;Michigan;49006;USA > version:2.1 > email;internet:[EMAIL PROTECTED] > title:Professor > fn:Bob Grossman, Ph.D > end:vcard > > --------------5C290250737FD5BC4614FF4F-- > > > ---------------------------------------------------------------------- > > Subject: Re: psychology of crimal conduct mulitmedia resources > From: "Gene Walker" <[EMAIL PROTECTED]> > Date: Tue, 25 Feb 2003 08:42:45 -0600 > X-Message-Number: 4 > > Rachel: Try the following web sites: www.films.com; > www.cambridgeeducational.com; and, www.ncjrs.org. > Best Wishes. Gene Walker > ----- Original Message ----- > From: "Rachael Collie" <[EMAIL PROTECTED]> > To: "Teaching in the Psychological Sciences" <[EMAIL PROTECTED]> > Sent: Monday, February 24, 2003 9:06 PM > Subject: psychology of crimal conduct mulitmedia resources > > > > Hi, I'm keen on anyone's knowledge of good video or CDRom resources > > relevant to the psychology of criminal conduct. Its for teaching at 3rd > > and 4th year levels of psychology. > > > > Thanks > > Rachael Collie > > Victoria University, NZ > > > > --- > > You are currently subscribed to tips as: [EMAIL PROTECTED] > > To unsubscribe send a blank email to [EMAIL PROTECTED] > > > > > ---------------------------------------------------------------------- > > Subject: Re: z-score woes > From: Maxwell Gwynn <[EMAIL PROTECTED]> > Date: Tue, 25 Feb 2003 11:43:15 -0500 (EST) > X-Message-Number: 5 > > Rod: > > When introducing the class in the use of Z-scores (read "Zed Scores" in > the Great White North, eh?) I think that it's important to stress the idea > that we are talking about how an individual does _relative to the rest of > the distribution_. > > An example I use involves a bet between two roommates, Pat and Chris, who > are in two different statistics courses. They have midterms coming up, > and they want to make a bet as to who will "do better" on the exam. > > Pat suggests that whoever gets the higher score on their exam wins the bet > (no dishwashing for a week). Chris points out that the two exams may have > different numbers of questions, and/or a different maximum score. So, > looking at the raw scores may not be a way to compare their two > performances [e.g., 45 out of 55 versus 49 out of 60]. Instead, they > should each convert their grades to a percentage, and compare percentages. > [This introduces the concept of converting or transforming scores] > > That's an imporvement, says Pat. But what if your prof gives you an easy > exam with a high class average, while my prof gives a toughie with a lower > class average? That wouldn't be fair to me. [Must take distribution > average into account] Let's make it so that who ever does better relative > to their class average wins the bet. In other words, subtract the class > average from your score [X - Xbar], and whoever has the higher positive > difference wins. > > Chris replies with, I like the idea of comparing scores to the respective > class average rather than raw scores, but if your exam is out of 100 and > mine is out of 20, you're much more likely to get a high positive > difference score. [The scores come from distributions with different > properties] And even if the two exams are out of the same total and have > the same average, maybe your class will have much more variability around > that average, giving you a better chance of scoring further above the mean > than I would have in my class of less variable scores. [Must take > variability into account] > > So how do we handle this, they ask. Let's figure the standard deviation (a > measure of variability) for each class distribution, and see who scores > more standard deviations [standard scores or Z-scores] above the mean. > That will give us a standardized measure of our scores relative to our > respective class distributions. [This is exactly what a Z score is: a > standardized score indicating relative position in a distribution, i.e., > where a score stands relative to all of the other scores in a > distribution, taking into account each distribution's mean and standard > devaition]. > > I then provide the two roommates' scores and their respective class > averages and standard deviations. Next, we calculate the percentage, > difference score (X - Xbar), and Z score for each raw score. > > I try to work it out such that the "Better" score goes back and forth > depending on which measure is used. For example, raw score: Pat wins; > percentage score: Chris wins; difference score: Pat wins; Z-score, which > I explain is the fairest way to compare scores from two distributions: > Chris wins the bet (Chris did better relative to the rest of the scores > in her class's distribution) and doesn't have to wash dishes for a week! > > For a pictorial representation, I demonstrate by drawing two normal > distributions (with differing variability) centred one under the other, > indicating the two means and where one standard deviation lies in each > distribution, i.e., under the point of inflection. Then I ask students to > estimate how far along the respective X axis each of the two raw scores > would be found. If we've talked about percentile scores, I'll expalin how > Z scores can be transformed into percentile scores. > > The same example can be used when comparing one person's scores from two > different tests (e.g., first and second midterm exams), to check on > improvement realtive to the rest of the class. Also takes into account the > difficulty (mean) and variability (standard deviation) of each of the two > midterms (distributions with different properties). > > As with many of the examples and demos I've collected over the years, I > can't recall where I found this demonstration (textbook, instructor's > manual, TIPS, or if I made it up). > > With a student such as Rod's who doesn't see the need to include standard > deviations in a calculation, I'd draw out two distributions one over the > other with the same mean but with different spreads, and show how it is > easier to get a higher raw score on the distribution with the greater > spread. > > Perhaps Rod's student is having difficulty understanding why it's not > "cheating" to convert to Z scores because the examples of running and > swimming speeds are too dissimilar (minutes versus seconds). Have you > tried an example of running speed when comparing say four-year olds > (slower speeds, less variability) to the same kids when they're 8 years > old (faster speeds and greater variability) to show that, even though he > runs faster now and is 5 seconds faster than the average at each age, > Person X might be a slower runner _relative to other kids_ as an 8 y.o. > compared to when he was a 4 y.o.? > > -Max > > On Mon, 24 Feb 2003, Hetzel, Rod wrote: > > > Hi everyone: > > > > I need your help with something. I have a student who just does not > > understand z-scores. I have met with him for at least two hours outside > > of class and he still doesn't understand the concept. In particular, he > > doesn't seem to understand why you need to include standard deviation in > > the calculation of z-scores. "Why can't you just compare the raw > > scores?" is his frequent question. I explained to him in various ways > > that the z-score is a transformed score that can take scores from two > > different distributions and put them on a common metric, that it gives > > you a summary statistic that tells you an individual's score in relation > > to the mean and standard deviation, that it provides a way to compare > > scores from two different distributions, etc. > > > > Here is the example that my student keeps coming back to: "Jack and > > Jill are intense competitors, but they never competed against each > > other. Jack specialized in long-distance running and Jill was an > > excellent sprint swimmer. As you can see from the distributions in each > > table, each was best in their event. Take the analysis one step farther > > and use z-scores to determine who is the more outstanding competitor." > > > > LONG-DISTANCE RUNNING > > Jack: 37 min > > Bob: 39 min > > Joe: 40 min > > Ron: 42 min > > > > SPRING SWIMMING > > Jill: 24 sec > > Sue: 26 sec > > Peg: 27 sec > > Ann: 28 sec > > > > Here are the relevant statistics: > > RUNNING MEAN: 39.5 > > RUNNING SD: 1.803 > > JACK'S ZSCORE: -1.39 > > > > SWIMMING MEAN: 26.25 > > SWIMMING SD: 1.479 > > JILL'S ZSCORE: -1.52 > > > > When I have met with the student, he has not understood how Jill is the > > more outstanding competitor. He makes the comment that Jack is > > obviously the better competitor because Jack scored an entire 3 minutes > > faster than the next finisher whereas Jill scored only 2 seconds faster > > than her runner-up. "Why do you have to even look at the other scores > > in the distribution to tell that Jack is the better competitor? He > > finished a full three minutes ahead of his competitors and Jill just > > barely finished ahead of her competitors." I have drawn some diagrams > > of normal distributions to show how Jill's score on the distribution is > > further away from the mean and closer to the tail, but my student thinks > > that I am somehow changing the scores and cheating the system when I > > transform the raw scores to z-scores. Even after I show him how the > > position of the score remains unchanged, he cannot grasp in this case > > how Jill is the more outstanding competitor. I've tried switching > > examples with him (e.g., distributions of test scores, changing C > > temperature to F temperature, etc.), but nothing seems to be sinking in. > > He has a fairly high level of anxiety about statistics but tends to > > cover it up with humor and sarcasm. He took statistics with another > > professor last semester and told me that all statistics is a bunch of > > bull**** that serves no useful purpose other than obscuring the > > painfully-obvious truth. > > > > So, I have two questions for all of you out there in TIPS land... > > > > 1. Given what I've told you about the student's struggles with > > z-scores, does anyone have any specific ideas on how to present this > > information to him? I think I'm in a rut with him and need a fresh way > > to explain this. > > > > 2. Would anyone be willing to share with me any z-score examples that > > you use for your own assignments and exams? I am running out of new > > examples to use with this student and was hoping that perhaps you would > > be willing to share some of your own examples. This would give my > > student some more opportunities to calculate z-scores > > > > 3. How do you work with students who just don't seem to get statistics? > > Everyone else in the class seems to understand z-scores well, but I'm > > struggling a bit in trying to reach this student. I find that I am > > hardly ever at a loss for words when teaching clinical courses, but I'm > > reaching my limit with this student. This is certainly not my area of > > expertise, so I'm hoping that some of you stats-people can help out with > > this! > > > > Thanks for your assistance with this problem! > > > > Rod > > > > --- > > You are currently subscribed to tips as: [EMAIL PROTECTED] > > To unsubscribe send a blank email to [EMAIL PROTECTED] > > > > Maxwell Gwynn, PhD [EMAIL PROTECTED] > Department of Psychology (519) 884-0710 ext 3854 > Wilfrid Laurier University > Waterloo, Ontario N2L 3C5 Canada > > > > ---------------------------------------------------------------------- > > Subject: RE: z-score woes > From: Mike Scoles <[EMAIL PROTECTED]> > Date: Tue, 25 Feb 2003 11:07:43 -0600 > X-Message-Number: 6 > > Many students have trouble with z-scores because they are introduced with a > formula. I have had success by starting with various standard scores (IQ, > GRE, T, z). After describing IQ scores, I give a few prompts like, "What is > another way of saying that someone has an IQ of 115? 70? Someone 2 standard > deviations above the mean would have what IQ score?" Then I do the same for > GRE, T, and z. Then I ask them to translate one type of score to > another--"An IQ of 115 would be the same as a T of what?" > > They can easily do all of this without z = (X - mean)/SD or X = mean + > z(SD). Those formulas help when you don't have nice round numbers, but a > lot of drill without the formulas pays off. It is much easier for students > to see how to use the formulas to translate from one scale to another once > they have done it without them. > > > ************************************************* > Michael T. Scoles, Ph.D. > Director, Arkansas Charter School Resource Center > Associate Professor of Psychology & Counseling > University of Central Arkansas > Conway, AR 72035 > voice: (501) 450-5418 > fax: (501) 450-5424 > ************************************************* > > > > >-----Original Message----- > >From: Robert Grossman [mailto:[EMAIL PROTECTED] > >Sent: Tuesday, February 25, 2003 6:39 AM > >To: Teaching in the Psychological Sciences > >Subject: Re: z-score woes > > > > > >> > >> Subject: z-score woes > >> "I have a student who just does not understand z-scores. I have > >met with him for at least two hours outside of class and he still > >doesn't understand the concept. In particular, he doesn't seem to > >understand why you need to include standard deviation in the > >calculation of z-scores. "Why can't you just compare the raw > >> scores?" is his frequent question." > > > >Rod, > > > >I would suggest you give him a real problem we face in our > >admissions process. Say you have two students and can only admit > >one. They should be equal in most respects but have very > >different test scores--one has a SAT scores V 500 + M 450 = 950 > >while the other has an ACT Composite of 32. Which has a better > >chance of doing well in college? This isn't raw score comparison > >but the numbers paint one picture while the z-scores give quite a > >different picture. > > > >bob grossman > >[EMAIL PROTECTED] > >Kalamazoo College > > > > > > > ---------------------------------------------------------------------- > > Subject: SD Woes > From: "Wallace E. Dixon, Jr." <[EMAIL PROTECTED]> > Date: Tue, 25 Feb 2003 12:40:13 -0500 > X-Message-Number: 7 > > Speaking of z-score woes, does anyone know how psychology ended up > with standard deviations rather than mean absolute differences from > the mean. Is it just because of ease of calculation? > > wedj > > -- > -------------------------------------------------------------------------- -- > Wallace E. Dixon, Jr. | > Chair and Associate Professor | Rocket science is child's play > of Psychology | compared to understanding > Department of Psychology | child's play > East Tennessee State University | -unknown > Johnson City, TN 36714 | > (423) 439-6656 | > -------------------------------------------------------------------------- -- > > ---------------------------------------------------------------------- > > Subject: student request > From: "Lenore Frigo" <[EMAIL PROTECTED]> > Date: Tue, 25 Feb 2003 09:43:51 -0800 > X-Message-Number: 8 > > A student just send me this email in regard to preparing vocabulary terms > for a test tomorrow. The odd thing is that all of these terms are listed in > the subject index at the end of the book. Do you think this student is lazy > or just does not know how to operate a textbook? Is it my obligation to look > up these page numbers for the student? I would appreciate any of your quick > replies. > > Thanks, > > Lenore Frigo > > [EMAIL PROTECTED] > > "Dr. Frigo: > > Here's the vocabulary words off the list that I couldn't find, or must have > > just skipped over in the book. For chapter four, contrast effects, opponent > > process theory, perceptual set. Chapter five, nominal fallacy, role playing > > of hypnosis, psychoactive. Chapter six, BF Skinner, primary/secondary > > reinforcers, behavior modification. If you could tell me the page they're > > on, or just the general definition, that would be great. Thank you so much." > > > > > ---------------------------------------------------------------------- > > Subject: Re: student request > From: Vincent Prohaska <[EMAIL PROTECTED]> > Date: Tue, 25 Feb 2003 12:57:51 -0500 (Eastern Standard Time) > X-Message-Number: 9 > > > Tell the student about the index in the textbook. > > Vinny > > > > Vincent Prohaska, Ph.D. > Associate Professor and Chair > Department of Psychology > Lehman College, City University of New York > Bronx, NY 10468-1589 > [EMAIL PROTECTED] > 718-960-8204 > 718-960-8092 fax > > > > ---------------------------------------------------------------------- > > Subject: Re: student request > From: David Wasieleski <[EMAIL PROTECTED]> > Date: Tue, 25 Feb 2003 12:56:21 -0500 > X-Message-Number: 10 > > I would tell the student that the terms are in the subject index. It is not > your place to look them up, and the student will learn how to use a subject > index to do so. > David W. > > > At 09:43 AM 2/25/2003 -0800, you wrote: > >A student just send me this email in regard to preparing vocabulary terms > >for a test tomorrow. The odd thing is that all of these terms are listed in > >the subject index at the end of the book. Do you think this student is lazy > >or just does not know how to operate a textbook? Is it my obligation to look > >up these page numbers for the student? I would appreciate any of your quick > >replies. > > > >Thanks, > > > >Lenore Frigo > > > >[EMAIL PROTECTED] > > > >"Dr. Frigo: > > > >Here's the vocabulary words off the list that I couldn't find, or must have > > > >just skipped over in the book. For chapter four, contrast effects, opponent > > > >process theory, perceptual set. Chapter five, nominal fallacy, role playing > > > >of hypnosis, psychoactive. Chapter six, BF Skinner, primary/secondary > > > >reinforcers, behavior modification. If you could tell me the page they're > > > >on, or just the general definition, that would be great. Thank you so much." > > > > > > > > > >--- > >You are currently subscribed to tips as: [EMAIL PROTECTED] > >To unsubscribe send a blank email to [EMAIL PROTECTED] > > David T. Wasieleski, Ph.D. > Associate Professor > Department of Psychology and Counseling > Valdosta State University > Valdosta, GA 31698 > 229-333-5620 > http://chiron.valdosta.edu/dtwasieleski > > "It's funny in this age of illusion > It's hard to tell what's fact or fiction..." > --Tom Cochrane > "Friendly Advice" > > > ---------------------------------------------------------------------- > > Subject: Re: SD Woes > From: jim clark <[EMAIL PROTECTED]> > Date: Tue, 25 Feb 2003 11:56:47 -0600 (CST) > X-Message-Number: 11 > > Hi > > On Tue, 25 Feb 2003, Wallace E. Dixon, Jr. wrote: > > > Speaking of z-score woes, does anyone know how psychology ended up > > with standard deviations rather than mean absolute differences from > > the mean. Is it just because of ease of calculation? > > It is because of the statistical properties associated with the > SD and the closely linked Mean, as determined by statisticians > rather than psychologists. For example, the M is the center of a > distribution in the sense that the sum of squared deviations > about the mean (SS) is a minimum. SS, of course, is the basis > for the variance and SD. The appropriate measure of central > tendency for absolute differences is the median not the mean. > Numerous other statistical properties hinge on the SD (or its > close relatives SS or variance), including the z-scores discussed > here of late. Just consider the t-test, the F-test, R^2, ... > > Best wishes > Jim > > ============================================================================ > James M. Clark (204) 786-9757 > Department of Psychology (204) 774-4134 Fax > University of Winnipeg 4L05D > Winnipeg, Manitoba R3B 2E9 [EMAIL PROTECTED] > CANADA http://www.uwinnipeg.ca/~clark > ============================================================================ > > > ---------------------------------------------------------------------- > > Subject: Re: student request > From: "=?iso-8859-1?Q?Jos=E9_F._Alves?=" <[EMAIL PROTECTED]> > Date: Tue, 25 Feb 2003 18:03:46 +0000 > X-Message-Number: 12 > > I think you should tell him how you feel strange his mail. And suggest him > to search those terms > > Jose > ----- Original Message ----- > From: "Lenore Frigo" <[EMAIL PROTECTED]> > Newsgroups: tips > To: "Teaching in the Psychological Sciences" <[EMAIL PROTECTED]> > Sent: Tuesday, February 25, 2003 5:43 PM > Subject: student request > > > > A student just send me this email in regard to preparing vocabulary terms > > for a test tomorrow. The odd thing is that all of these terms are listed > in > > the subject index at the end of the book. Do you think this student is > lazy > > or just does not know how to operate a textbook? Is it my obligation to > look > > up these page numbers for the student? I would appreciate any of your > quick > > replies. > > > > Thanks, > > > > Lenore Frigo > > > > [EMAIL PROTECTED] > > > > "Dr. Frigo: > > > > Here's the vocabulary words off the list that I couldn't find, or must > have > > > > just skipped over in the book. For chapter four, contrast effects, > opponent > > > > process theory, perceptual set. Chapter five, nominal fallacy, role > playing > > > > of hypnosis, psychoactive. Chapter six, BF Skinner, primary/secondary > > > > reinforcers, behavior modification. If you could tell me the page they're > > > > on, or just the general definition, that would be great. Thank you so > much." > > > > > > > > > > --- > > You are currently subscribed to tips as: [EMAIL PROTECTED] > > To unsubscribe send a blank email to [EMAIL PROTECTED] > > > > > > ---------------------------------------------------------------------- > > Subject: Re: student request > From: John Serafin <[EMAIL PROTECTED]> > Date: Tue, 25 Feb 2003 13:04:50 -0500 > X-Message-Number: 13 > > on 2/25/03 12:43 PM, Lenore Frigo at [EMAIL PROTECTED] wrote: > > > A student just send me this email in regard to preparing vocabulary terms > > for a test tomorrow. The odd thing is that all of these terms are listed in > > the subject index at the end of the book. Do you think this student is lazy > > or just does not know how to operate a textbook? Is it my obligation to look > > up these page numbers for the student? I would appreciate any of your quick > > replies. > > > > Thanks, > > > > Lenore Frigo > > > > [EMAIL PROTECTED] > > > > "Dr. Frigo: > > > > Here's the vocabulary words off the list that I couldn't find, or must have > > > > just skipped over in the book. For chapter four, contrast effects, opponent > > > > process theory, perceptual set. Chapter five, nominal fallacy, role playing > > > > of hypnosis, psychoactive. Chapter six, BF Skinner, primary/secondary > > > > reinforcers, behavior modification. If you could tell me the page they're > > > > on, or just the general definition, that would be great. Thank you so much." > > > Heh, the student can't find B. F. Skinner in the text? He (B. F., that is) > must have fallen farther from grace than we had thought, if he receives such > minor attention. > > Lenore, I would simply email the student back and point out that all of the > terms can be found in the index (including page numbers!). I certainly would > not look up the page numbers myself. > > John > > -- > John Serafin > Psychology Department > Saint Vincent College > Latrobe, PA 15650 > [EMAIL PROTECTED] > > > > ---------------------------------------------------------------------- > > Subject: RE: student request > From: "Shearon, Tim" <[EMAIL PROTECTED]> > Date: Tue, 25 Feb 2003 11:22:43 -0700 > X-Message-Number: 14 > > Lenore- Perhaps you should send them a list of the things you have been = > assigned to do for tomorrow and thank them for doing it. :) YES the = > student is being lazy. But also inappropriately familiar, expressing = > entitlement, immaturity, yada, yada. Gently but firmly state to them = > that they do not learn from work you do for them and that the terms are = > indeed in the text. Wish them luck but under no circumstances would I do = > this for them. Tim > > ********************************************** > Timothy O. Shearon, Ph.D. > Department of Psychology (Chairperson) > Albertson College of Idaho > Caldwell, Idaho > > ph- 208-459-5840=20 > > teaching interests: neuropsychology, history of psychology, = > developmental (topical), intro > > -----Original Message----- > From: Lenore Frigo [mailto:[EMAIL PROTECTED] > Sent: Tuesday, February 25, 2003 10:44 AM > To: Teaching in the Psychological Sciences > Subject: student request > > > A student just send me this email in regard to preparing vocabulary = > terms > for a test tomorrow. The odd thing is that all of these terms are listed = > in > the subject index at the end of the book. Do you think this student is = > lazy > or just does not know how to operate a textbook? Is it my obligation to = > look > up these page numbers for the student? I would appreciate any of your = > quick > replies. > > Thanks, > > Lenore Frigo > > [EMAIL PROTECTED] > > "Dr. Frigo: > > Here's the vocabulary words off the list that I couldn't find, or must = > have > > just skipped over in the book. For chapter four, contrast effects, = > opponent > > process theory, perceptual set. Chapter five, nominal fallacy, role = > playing > > of hypnosis, psychoactive. Chapter six, BF Skinner, primary/secondary > > reinforcers, behavior modification. If you could tell me the page = > they're > > on, or just the general definition, that would be great. Thank you so = > much." > > > > > --- > You are currently subscribed to tips as: [EMAIL PROTECTED] > To unsubscribe send a blank email to = > [EMAIL PROTECTED] > > ---------------------------------------------------------------------- > > Subject: RE: student request > From: "Hetzel, Rod" <[EMAIL PROTECTED]> > Date: Tue, 25 Feb 2003 13:08:46 -0600 > X-Message-Number: 15 > > I have found that many students--particularly > first-year-students--aren't aware that college requires more independent > work. I would guess that many students have had high school teachers > that would do this sort of work for them and don't know that more is > expected of them in college. The specific situation you mentioned is > really just one variation on a theme. I have had students asked me to > prepare very detailed study guides, takes notes on chapters for them, > give them copies of my lecture/discussion notes so they don't have to > take notes in class, etc. When I have to educate students about these > kinds of things, I try to do it with no personal agenda--no heat or > parental-like anger--but just a calm explanation as to what is > acceptable and why it is acceptable. I try to adopt an "Oh, they must > not get it. I'll need to explain it" attitude, assuming their behavior > is based on naivete rather than illwill. =20 > > This is sometimes difficult to do, though. I had a student last week > who was drawing unflattering pictures of me in class on the paperwork > that he was supposed to turn in at the end of the class session. When I > asked for the class to submit this paperwork, he bust out laughing and > showed his drawing to the rest of the students at the table, who also > then started laughing. He then took his paper back and began furiously > erasing his artwork. I made an appointment to meet with him later that > afternoon and explained how his behavior came across as disruptive and > disrespectful. He understood the disruptive part, but he didn't think > he was being disrespectful. I asked him what he had been erasing and he > told me he was erasing a picture of the class sleeping. I asked him, > "Don't you consider it disrespectful to be drawing a picture of your > professor lecturing while the rest of the class is sleeping?" but he > told me that I should be grateful because his sketching during class > allowed him to stay awake in the first place. Sigh...Part of me thinks > that this is the sort of thing that she be taken care of in high school > and shouldn't be seen among juniors and seniors. At any rate, in > handling these types of situations, I have found that the more punitive > I come across, the less likely my students are to internalize the > message and the less likely they will be to grow from the experience. > > Just my 2 cents. > > ______________________________________________ > Roderick D. Hetzel, Ph.D. > Department of Psychology > LeTourneau University > Post Office Box 7001 > 2100 South Mobberly Avenue > Longview, Texas 75607-7001 > =20 > Office: Education Center 218 > Phone: 903-233-3893 > Fax: 903-233-3851 > Email: [EMAIL PROTECTED] > Homepage: http://www.letu.edu/people/rodhetzel > > > > -----Original Message----- > > From: Lenore Frigo [mailto:[EMAIL PROTECTED] > > Sent: Tuesday, February 25, 2003 11:44 AM > > To: Teaching in the Psychological Sciences > > Subject: student request > >=20 > >=20 > > A student just send me this email in regard to preparing=20 > > vocabulary terms for a test tomorrow. The odd thing is that=20 > > all of these terms are listed in the subject index at the end=20 > > of the book. Do you think this student is lazy or just does=20 > > not know how to operate a textbook? Is it my obligation to=20 > > look up these page numbers for the student? I would=20 > > appreciate any of your quick replies. > >=20 > > Thanks, > >=20 > > Lenore Frigo > >=20 > > [EMAIL PROTECTED] > >=20 > > "Dr. Frigo: > >=20 > > Here's the vocabulary words off the list that I couldn't=20 > > find, or must have > >=20 > > just skipped over in the book. For chapter four, contrast=20 > > effects, opponent > >=20 > > process theory, perceptual set. Chapter five, nominal=20 > > fallacy, role playing > >=20 > > of hypnosis, psychoactive. Chapter six, BF Skinner, primary/secondary > >=20 > > reinforcers, behavior modification. If you could tell me the=20 > > page they're > >=20 > > on, or just the general definition, that would be great.=20 > > Thank you so much." > >=20 > >=20 > >=20 > >=20 > > --- > > You are currently subscribed to tips as: [EMAIL PROTECTED] > > To unsubscribe send a blank email to=20 > > [EMAIL PROTECTED] > >=20 > > ---------------------------------------------------------------------- > > Subject: Re: SD Woes > From: "Patrick O. Dolan" <[EMAIL PROTECTED]> > Date: Tue, 25 Feb 2003 14:11:29 -0500 > X-Message-Number: 16 > > Interesting question. Glancing through a couple stats books it is > occasionally mentioned as a method but quickly dismissed. > > Welkowitz, Ewen & Cohen (1992; 4th ed.) notes that averaging the > absolute values is a useful descriptive measure termed Average > Deviation. They go on to say "it is usually rejected because absolute > values are unsuitable for further statistical analysis." > > A stats for engineers book by Kennedy & Neville (1976; 2nd ed.) states > "the usefulness of the mean deviation in statistical calculations is > small, and practically no statistical methods of analysis involve its > use." > > Another text (Howell1992; 3rd ed.) called it the M.A.D. (mean absolute > deviation) and goes on to say "for all its simplicity and intuitive > appeal, the mean absolute deviation has not played an important role > in statistics. Instead, much more useful measures, the variance and > the standard deviation, are normally used." > > Spence, Underwood, Duncan & Cotton (1968; 2nd ed.) "Yet, for various > reasons, the average deviation is rarely used as a measure of > variability." > > Levine's (1981) text offers the closest to a justification why it is > not used. It states that it is useful but "... it is not useable in > conjunction with most statistical techniques, which require > consistence with the laws of algebra. Ignoring the signs of numbers > violates the laws of algebra." > > Patrick > (any excuse to not grade this afternoon...) > > ********************* > Patrick O. Dolan > Assistant Professor > Department of Psychology > Drew University > Madison, NJ 07940 > 973-408-3558 > [EMAIL PROTECTED] > ********************* > ----- Original Message ----- > From: "Wallace E. Dixon, Jr." <[EMAIL PROTECTED]> > To: "Teaching in the Psychological Sciences" > <[EMAIL PROTECTED]> > Sent: Tuesday, February 25, 2003 12:40 PM > Subject: SD Woes > > > > Speaking of z-score woes, does anyone know how psychology ended up > > with standard deviations rather than mean absolute differences from > > the mean. Is it just because of ease of calculation? > > > > wedj > > > > -- > > -------------------------------------------------------------------- > -------- > > Wallace E. Dixon, Jr. | > > Chair and Associate Professor | Rocket science is child's > play > > of Psychology | compared to understanding > > Department of Psychology | child's play > > East Tennessee State University | -unknown > > Johnson City, TN 36714 | > > (423) 439-6656 | > > -------------------------------------------------------------------- > -------- > > > > --- > > You are currently subscribed to tips as: [EMAIL PROTECTED] > > To unsubscribe send a blank email to > [EMAIL PROTECTED] > > > > > > > ---------------------------------------------------------------------- > > Subject: RE: z-score woes > From: "John Kulig" <[EMAIL PROTECTED]> > Date: Tue, 25 Feb 2003 14:23:24 -0500 > X-Message-Number: 17 > > > > I agree with the "hold the formula" approach. I introduce Z from the % > angle, and I use the "68% - 95% - 99.7%" rules of thumb, and > occasionally substitute "most people" "nearly everybody" and "virtually > everybody" for the %. You can get a lot of mileage from this approach. > The formulas can be introduced later, when dead reckoning fails. > > Say, anybody else notice that students are showing up to their first > stats class with overly-expensive calculators? I had a student with a > graphing TI, she lost the manual, and couldn't get a mean! Being a "HP" > person, I couldn't get the mean either! > > > ============================================ > John W. Kulig > Professor of Psychology > Plymouth State College > Plymouth NH 03264 > ============================================ > "Eat bread and salt and speak the truth" > Russian saying. > > -----Original Message----- > From: Mike Scoles [mailto:[EMAIL PROTECTED] > Sent: Tuesday, February 25, 2003 12:08 PM > To: Teaching in the Psychological Sciences > Subject: RE: z-score woes > > Many students have trouble with z-scores because they are introduced > with a > formula. I have had success by starting with various standard scores > (IQ, > GRE, T, z). After describing IQ scores, I give a few prompts like, > "What is > another way of saying that someone has an IQ of 115? 70? Someone 2 > standard > deviations above the mean would have what IQ score?" Then I do the same > for > GRE, T, and z. Then I ask them to translate one type of score to > another--"An IQ of 115 would be the same as a T of what?" > > They can easily do all of this without z = (X - mean)/SD or X = mean + > z(SD). Those formulas help when you don't have nice round numbers, but > a > lot of drill without the formulas pays off. It is much easier for > students > to see how to use the formulas to translate from one scale to another > once > they have done it without them. > > > ************************************************* > Michael T. Scoles, Ph.D. > Director, Arkansas Charter School Resource Center > Associate Professor of Psychology & Counseling > University of Central Arkansas > Conway, AR 72035 > voice: (501) 450-5418 > fax: (501) 450-5424 > ************************************************* > > > > >-----Original Message----- > >From: Robert Grossman [mailto:[EMAIL PROTECTED] > >Sent: Tuesday, February 25, 2003 6:39 AM > >To: Teaching in the Psychological Sciences > >Subject: Re: z-score woes > > > > > >> > >> Subject: z-score woes > >> "I have a student who just does not understand z-scores. I have > >met with him for at least two hours outside of class and he still > >doesn't understand the concept. In particular, he doesn't seem to > >understand why you need to include standard deviation in the > >calculation of z-scores. "Why can't you just compare the raw > >> scores?" is his frequent question." > > > >Rod, > > > >I would suggest you give him a real problem we face in our > >admissions process. Say you have two students and can only admit > >one. They should be equal in most respects but have very > >different test scores--one has a SAT scores V 500 + M 450 = 950 > >while the other has an ACT Composite of 32. Which has a better > >chance of doing well in college? This isn't raw score comparison > >but the numbers paint one picture while the z-scores give quite a > >different picture. > > > >bob grossman > >[EMAIL PROTECTED] > >Kalamazoo College > > > > > > > --- > You are currently subscribed to tips as: [EMAIL PROTECTED] > To unsubscribe send a blank email to > [EMAIL PROTECTED] > > > ---------------------------------------------------------------------- > > Subject: FW: A Class Divided, (check local listings) on PBS > From: Beth Benoit <[EMAIL PROTECTED]> > Date: Tue, 25 Feb 2003 14:50:22 -0500 > X-Message-Number: 18 > > > ---------- > From: FRONTLINE bulletin <[EMAIL PROTECTED]> > Reply-To: [EMAIL PROTECTED] > Date: Tue, 25 Feb 2003 02:13:10 GMT > To: [EMAIL PROTECTED] > Subject: A Class Divided, (check local listings) on PBS > > > FRONTLINE > http://www.pbs.org/frontline/ > > - This Week: "A Class Divided," > (check local listings) on PBS > - Wanted: A Few Good Words ... > > > + This Week ... > > One Friday morning in April 1968, the day after Martin Luther King Jr. > was shot and killed, a third-grade teacher in Iowa named Jane Elliott > decided to change her lesson plan. > > "I knew the night before that it was time to deal with this in a > concrete way, not just talking about it," Elliott explained to FRONTLINE > 14 years later. "We had talked about racism since the first day of > school, but the shooting of Martin Luther King ... could not just be > talked about and explained away." > > So she did something she'd been considering for a long time but had > never found the courage to try. She divided her all-white third-grade > class into two groups -- one brown-eyed and one blue-eyed -- and taught > them a hard lesson about discrimination that is still powerful after > more than 30 years. > > "A Class Divided," originally broadcast in 1985 and re-airing this > (check local listings) on PBS, is one of the > most requested programs in FRONTLINE's history. Producer William Peters, > who had made a documentary about Elliott's exercise in 1970 for ABC > News, returned in 1984 to interview Elliott and film a reunion of her > students, who by that time were young adults, as they watched themselves > in the original documentary and talked about how the experience changed > their lives. Peters then filmed Elliott conducting the exercise with > employees of Iowa's correctional system, documenting the lesson's impact > on adults. The results are strangely, unexpectedly riveting. > > In the years since, Elliott's lesson has been adopted around the world > and has been the inspiration for a best-selling book, four more > documentaries, and a made-for-TV movie (starring Susan Sarandon as Jane > Elliott) that's now in development. > > On our website you'll find an interview with Elliott conducted this past > December, in which she talks about her experiences in the years since > the FRONTLINE film was made. The interview and more, including an > opportunity to join the discussion, can all be found at: > http://www.pbs.org/frontline/shows/divided/ > > Whether you've seen the film before, or whether it's your first time, we > hope you'll join us this (check local listings). And if you miss the > broadcast, > don't forget that you can watch "A Class Divided" in its entirety on our > website in streaming video. > > Wen Stephenson > Website Managing Editor > FRONTLINE > > > > ---------------------------- > > + Wanted: A Few Good Words ... > > PBS Advertising is planning to produce an on-air image spot for > FRONTLINE in early March that includes comments from "ordinary viewers" > who watch FRONTLINE somewhat regularly (once or more per month) and who > are familiar with the series' website. The PBS creative team is looking > for 15 viewers who have positive impressions of FRONTLINE and who can > articulate why they watch. They're particularly interested in hearing > about actions viewers may have taken after viewing FRONTLINE, like > writing a letter to a government representative, sharing their > impressions of the program with friends, etc. > > PBS producers will be in the Boston area in the coming weeks to conduct > interviews and are looking for participants living within a reasonable > proximity to Boston. (No travel compensation will be offered.) > Participants will be pre-interviewed by phone, and if selected, will > need to give the producers two hours of their time on a weekday. > > If you have any interest in being considered for this on-air campaign, > kindly reply by email to [EMAIL PROTECTED] (with the subject heading > "Campaign") by this Friday, February 28. > > ---------------------------- > > Funding for FRONTLINE is provided through the support of PBS viewers. > > ---------------------------- > > We're always happy to hear from our viewers. If you have a question or > comment about a FRONTLINE program, about our website, or about this > bulletin, you can write to us directly by going to: > http://www.pbs.org/frontline/contact/ > > ---------------------------- > > You're subscribed to the FRONTLINE Bulletin as: [EMAIL PROTECTED] > If you feel you've received this email in error or you wish to > unsubscribe for any reason, please go to > http://www.pbs.org/frontline/join/ and fill out the "unsubscribe" > section. We cannot process requests to unsubscribe via email. > > > > ---------------------------------------------------------------------- > > Subject: Eating disorders - PBS special > From: Beth Benoit <[EMAIL PROTECTED]> > Date: Tue, 25 Feb 2003 14:52:11 -0500 > X-Message-Number: 19 > > This already premiered yesterday, but is still on its repeat schedule. I > saw a bit of it, so have my VCR set for 3 a.m. tomorrow. Check local > listings: > > http://www.pbs.org/perfectillusions/ > > > ---------------------------------------------------------------------- > > Subject: RE: SD Woes > From: "John Kulig" <[EMAIL PROTECTED]> > Date: Tue, 25 Feb 2003 15:00:00 -0500 > X-Message-Number: 20 > > Wallace: > The rest of our statistical procedures (correlations, > regression, anova) build on a foundation of "squared deviation" scores, > not average deviation scores. They all hang together as related > procedures. The average deviation is not related to these other > procedures. > Squaring the deviation scores does more than get rid of negative > signs; scores farther away from the mean get added weight. In the simple > series 1,2,3,4,5 (m=3), the absolute deviations scores are 2,1,0,1,2 > (average = 1.2). The squared deviations are 4,1,0,1,4, which, when > summed (=10) averaged (=2) and squared rooted back to the original > units, equals 1.414 (larger than 1.2). That's about the extent of what I > teach about AD - I use it as a set-up to introduce squared deviation > scores en-route to the variance and SD. But, we can probably have > legitimate uses for the AD. Knowing that the average deviation score in > Intro Psych equals 10 can be a useful statistic in its own right. > > ============================================ > John W. Kulig > Professor of Psychology > Plymouth State College > Plymouth NH 03264 > ============================================ > "Eat bread and salt and speak the truth" > Russian saying. > > -----Original Message----- > From: Wallace E. Dixon, Jr. [mailto:[EMAIL PROTECTED] > Sent: Tuesday, February 25, 2003 12:40 PM > To: Teaching in the Psychological Sciences > Subject: SD Woes > > Speaking of z-score woes, does anyone know how psychology ended up > with standard deviations rather than mean absolute differences from > the mean. Is it just because of ease of calculation? > > wedj > > -- > ------------------------------------------------------------------------ > ---- > Wallace E. Dixon, Jr. | > Chair and Associate Professor | Rocket science is child's play > of Psychology | compared to understanding > Department of Psychology | child's play > East Tennessee State University | -unknown > Johnson City, TN 36714 | > (423) 439-6656 | > ------------------------------------------------------------------------ > ---- > > --- > You are currently subscribed to tips as: [EMAIL PROTECTED] > To unsubscribe send a blank email to > [EMAIL PROTECTED] > > > ---------------------------------------------------------------------- > > Subject: Re: z-score woes > From: "David L. Carpenter" <[EMAIL PROTECTED]> > Date: Tue, 25 Feb 2003 17:02:23 -0500 > X-Message-Number: 21 > > Rod, > > Maybe an example closer to home would help. Give him as an example his > score on two hypothetical exams in the same class. Set it up so his > numerical score on the first exam is lower than his numerical score on the > second exam, but on the first exam is above the mean of the class and > below it on the second exam. Ask him which exam he did better on. > Obviously he did higher on the second, but relatively (and on the grading > curve) he did poorer on the second exam. Maybe that will get him thinking > a little outside his box. > > Dave Carpenter > Dept. of Psychology > St. Bonaventure University > St. Bonaventure, NY 14778 > > [EMAIL PROTECTED] > > > > Rod: > > > > When introducing the class in the use of Z-scores (read "Zed Scores" in > > the Great White North, eh?) I think that it's important to stress the idea > > that we are talking about how an individual does _relative to the rest of > > the distribution_. > > > > An example I use involves a bet between two roommates, Pat and Chris, who > > are in two different statistics courses. They have midterms coming up, > > and they want to make a bet as to who will "do better" on the exam. > > > > Pat suggests that whoever gets the higher score on their exam wins the bet > > (no dishwashing for a week). Chris points out that the two exams may have > > different numbers of questions, and/or a different maximum score. So, > > looking at the raw scores may not be a way to compare their two > > performances [e.g., 45 out of 55 versus 49 out of 60]. Instead, they > > should each convert their grades to a percentage, and compare percentages. > > [This introduces the concept of converting or transforming scores] > > > > That's an imporvement, says Pat. But what if your prof gives you an easy > > exam with a high class average, while my prof gives a toughie with a lower > > class average? That wouldn't be fair to me. [Must take distribution > > average into account] Let's make it so that who ever does better relative > > to their class average wins the bet. In other words, subtract the class > > average from your score [X - Xbar], and whoever has the higher positive > > difference wins. > > > > Chris replies with, I like the idea of comparing scores to the respective > > class average rather than raw scores, but if your exam is out of 100 and > > mine is out of 20, you're much more likely to get a high positive > > difference score. [The scores come from distributions with different > > properties] And even if the two exams are out of the same total and have > > the same average, maybe your class will have much more variability around > > that average, giving you a better chance of scoring further above the mean > > than I would have in my class of less variable scores. [Must take > > variability into account] > > > > So how do we handle this, they ask. Let's figure the standard deviation (a > > measure of variability) for each class distribution, and see who scores > > more standard deviations [standard scores or Z-scores] above the mean. > > That will give us a standardized measure of our scores relative to our > > respective class distributions. [This is exactly what a Z score is: a > > standardized score indicating relative position in a distribution, i.e., > > where a score stands relative to all of the other scores in a > > distribution, taking into account each distribution's mean and standard > > devaition]. > > > > I then provide the two roommates' scores and their respective class > > averages and standard deviations. Next, we calculate the percentage, > > difference score (X - Xbar), and Z score for each raw score. > > > > I try to work it out such that the "Better" score goes back and forth > > depending on which measure is used. For example, raw score: Pat wins; > > percentage score: Chris wins; difference score: Pat wins; Z-score, which > > I explain is the fairest way to compare scores from two distributions: > > Chris wins the bet (Chris did better relative to the rest of the scores > > in her class's distribution) and doesn't have to wash dishes for a week! > > > > For a pictorial representation, I demonstrate by drawing two normal > > distributions (with differing variability) centred one under the other, > > indicating the two means and where one standard deviation lies in each > > distribution, i.e., under the point of inflection. Then I ask students to > > estimate how far along the respective X axis each of the two raw scores > > would be found. If we've talked about percentile scores, I'll expalin how > > Z scores can be transformed into percentile scores. > > > > The same example can be used when comparing one person's scores from two > > different tests (e.g., first and second midterm exams), to check on > > improvement realtive to the rest of the class. Also takes into account the > > difficulty (mean) and variability (standard deviation) of each of the two > > midterms (distributions with different properties). > > > > As with many of the examples and demos I've collected over the years, I > > can't recall where I found this demonstration (textbook, instructor's > > manual, TIPS, or if I made it up). > > > > With a student such as Rod's who doesn't see the need to include standard > > deviations in a calculation, I'd draw out two distributions one over the > > other with the same mean but with different spreads, and show how it is > > easier to get a higher raw score on the distribution with the greater > > spread. > > > > Perhaps Rod's student is having difficulty understanding why it's not > > "cheating" to convert to Z scores because the examples of running and > > swimming speeds are too dissimilar (minutes versus seconds). Have you > > tried an example of running speed when comparing say four-year olds > > (slower speeds, less variability) to the same kids when they're 8 years > > old (faster speeds and greater variability) to show that, even though he > > runs faster now and is 5 seconds faster than the average at each age, > > Person X might be a slower runner _relative to other kids_ as an 8 y.o. > > compared to when he was a 4 y.o.? > > > > -Max > > > > On Mon, 24 Feb 2003, Hetzel, Rod wrote: > > > > > Hi everyone: > > > > > > I need your help with something. I have a student who just does not > > > understand z-scores. I have met with him for at least two hours outside > > > of class and he still doesn't understand the concept. In particular, he > > > doesn't seem to understand why you need to include standard deviation in > > > the calculation of z-scores. "Why can't you just compare the raw > > > scores?" is his frequent question. I explained to him in various ways > > > that the z-score is a transformed score that can take scores from two > > > different distributions and put them on a common metric, that it gives > > > you a summary statistic that tells you an individual's score in relation > > > to the mean and standard deviation, that it provides a way to compare > > > scores from two different distributions, etc. > > > > > > Here is the example that my student keeps coming back to: "Jack and > > > Jill are intense competitors, but they never competed against each > > > other. Jack specialized in long-distance running and Jill was an > > > excellent sprint swimmer. As you can see from the distributions in each > > > table, each was best in their event. Take the analysis one step farther > > > and use z-scores to determine who is the more outstanding competitor." > > > > > > LONG-DISTANCE RUNNING > > > Jack: 37 min > > > Bob: 39 min > > > Joe: 40 min > > > Ron: 42 min > > > > > > SPRING SWIMMING > > > Jill: 24 sec > > > Sue: 26 sec > > > Peg: 27 sec > > > Ann: 28 sec > > > > > > Here are the relevant statistics: > > > RUNNING MEAN: 39.5 > > > RUNNING SD: 1.803 > > > JACK'S ZSCORE: -1.39 > > > > > > SWIMMING MEAN: 26.25 > > > SWIMMING SD: 1.479 > > > JILL'S ZSCORE: -1.52 > > > > > > When I have met with the student, he has not understood how Jill is the > > > more outstanding competitor. He makes the comment that Jack is > > > obviously the better competitor because Jack scored an entire 3 minutes > > > faster than the next finisher whereas Jill scored only 2 seconds faster > > > than her runner-up. "Why do you have to even look at the other scores > > > in the distribution to tell that Jack is the better competitor? He > > > finished a full three minutes ahead of his competitors and Jill just > > > barely finished ahead of her competitors." I have drawn some diagrams > > > of normal distributions to show how Jill's score on the distribution is > > > further away from the mean and closer to the tail, but my student thinks > > > that I am somehow changing the scores and cheating the system when I > > > transform the raw scores to z-scores. Even after I show him how the > > > position of the score remains unchanged, he cannot grasp in this case > > > how Jill is the more outstanding competitor. I've tried switching > > > examples with him (e.g., distributions of test scores, changing C > > > temperature to F temperature, etc.), but nothing seems to be sinking in. > > > He has a fairly high level of anxiety about statistics but tends to > > > cover it up with humor and sarcasm. He took statistics with another > > > professor last semester and told me that all statistics is a bunch of > > > bull**** that serves no useful purpose other than obscuring the > > > painfully-obvious truth. > > > > > > So, I have two questions for all of you out there in TIPS land... > > > > > > 1. Given what I've told you about the student's struggles with > > > z-scores, does anyone have any specific ideas on how to present this > > > information to him? I think I'm in a rut with him and need a fresh way > > > to explain this. > > > > > > 2. Would anyone be willing to share with me any z-score examples that > > > you use for your own assignments and exams? I am running out of new > > > examples to use with this student and was hoping that perhaps you would > > > be willing to share some of your own examples. This would give my > > > student some more opportunities to calculate z-scores > > > > > > 3. How do you work with students who just don't seem to get statistics? > > > Everyone else in the class seems to understand z-scores well, but I'm > > > struggling a bit in trying to reach this student. I find that I am > > > hardly ever at a loss for words when teaching clinical courses, but I'm > > > reaching my limit with this student. This is certainly not my area of > > > expertise, so I'm hoping that some of you stats-people can help out with > > > this! > > > > > > Thanks for your assistance with this problem! > > > > > > Rod > > > > > > --- > > > You are currently subscribed to tips as: [EMAIL PROTECTED] > > > To unsubscribe send a blank email to [EMAIL PROTECTED] > > > > > > > Maxwell Gwynn, PhD [EMAIL PROTECTED] > > Department of Psychology (519) 884-0710 ext 3854 > > Wilfrid Laurier University > > Waterloo, Ontario N2L 3C5 Canada > > ---------------------------------------------------------------------- > > Subject: RE: z-score woes > From: "Hetzel, Rod" <[EMAIL PROTECTED]> > Date: Tue, 25 Feb 2003 16:17:42 -0600 > X-Message-Number: 22 > > Hi everyone: > > Thanks to everyone for their helpful guidance on the z-score situation. > Actually, I ended using an combination of all of your suggestions. I > used David's examples of focusing on two particular distributions of > tests scores (see below for the specifics). I framed this situation in > the context of Max's example of a wager between two roommates. I also > took Mike's approach to discussing the differences between various > standard scores and then discussing the formula. This was the third > hour outside of the classroom that I have devoted to helping this > student understand z-scores, but I think that he is finally beginning to > understand the concept. Now, on to T-scores.... :) > > Thanks again for all of your help! > > Rod > > ______________________________________________ > Roderick D. Hetzel, Ph.D. > Department of Psychology > LeTourneau University > Post Office Box 7001 > 2100 South Mobberly Avenue > Longview, Texas 75607-7001 > =20 > Office: Education Center 218 > Phone: 903-233-3893 > Fax: 903-233-3851 > Email: [EMAIL PROTECTED] > Homepage: http://www.letu.edu/people/rodhetzel > > > > -----Original Message----- > > From: David L. Carpenter [mailto:[EMAIL PROTECTED] > > Sent: Tuesday, February 25, 2003 4:02 PM > > To: Teaching in the Psychological Sciences > > Subject: Re: z-score woes > >=20 > >=20 > > Rod, > > =20 > > Maybe an example closer to home would help. Give him as an=20 > > example his score on two hypothetical exams in the same=20 > > class. Set it up so his numerical score on the first exam is=20 > > lower than his numerical score on the second exam, but on the=20 > > first exam is above the mean of the class and below it on the=20 > > second exam. Ask him which exam he did better on.=20 > > Obviously he did higher on the second, but relatively (and on=20 > > the grading > > curve) he did poorer on the second exam. Maybe that will get=20 > > him thinking a little outside his box. > > =20 > > Dave Carpenter > > Dept. of Psychology > > St. Bonaventure University > > St. Bonaventure, NY 14778 > >=20 > > [EMAIL PROTECTED] > >=20 > >=20 > > > Rod: > > >=20 > > > When introducing the class in the use of Z-scores (read=20 > > "Zed Scores"=20 > > > in the Great White North, eh?) I think that it's important=20 > > to stress=20 > > > the idea that we are talking about how an individual does=20 > > _relative to=20 > > > the rest of the distribution_. > > >=20 > > > An example I use involves a bet between two roommates, Pat=20 > > and Chris,=20 > > > who are in two different statistics courses. They have=20 > > midterms coming=20 > > > up, and they want to make a bet as to who will "do better" on the=20 > > > exam. > > >=20 > > > Pat suggests that whoever gets the higher score on their=20 > > exam wins the=20 > > > bet (no dishwashing for a week). Chris points out that the=20 > > two exams=20 > > > may have different numbers of questions, and/or a different maximum=20 > > > score. So, looking at the raw scores may not be a way to=20 > > compare their=20 > > > two performances [e.g., 45 out of 55 versus 49 out of 60]. Instead,=20 > > > they should each convert their grades to a percentage, and compare=20 > > > percentages. [This introduces the concept of converting or=20 > > > transforming scores] > > >=20 > > > That's an imporvement, says Pat. But what if your prof gives you an=20 > > > easy exam with a high class average, while my prof gives a toughie=20 > > > with a lower class average? That wouldn't be fair to me. [Must take=20 > > > distribution average into account] Let's make it so that=20 > > who ever does=20 > > > better relative to their class average wins the bet. In=20 > > other words,=20 > > > subtract the class average from your score [X - Xbar], and=20 > > whoever has=20 > > > the higher positive difference wins. > > >=20 > > > Chris replies with, I like the idea of comparing scores to the=20 > > > respective class average rather than raw scores, but if=20 > > your exam is=20 > > > out of 100 and mine is out of 20, you're much more likely to get a=20 > > > high positive difference score. [The scores come from distributions=20 > > > with different properties] And even if the two exams are out of the=20 > > > same total and have the same average, maybe your class will=20 > > have much=20 > > > more variability around that average, giving you a better chance of=20 > > > scoring further above the mean than I would have in my=20 > > class of less=20 > > > variable scores. [Must take variability into account] > > >=20 > > > So how do we handle this, they ask. Let's figure the standard=20 > > > deviation (a measure of variability) for each class=20 > > distribution, and=20 > > > see who scores more standard deviations [standard scores or=20 > > Z-scores]=20 > > > above the mean. That will give us a standardized measure of=20 > > our scores=20 > > > relative to our respective class distributions. [This is=20 > > exactly what=20 > > > a Z score is: a standardized score indicating relative=20 > > position in a=20 > > > distribution, i.e., where a score stands relative to all of=20 > > the other=20 > > > scores in a distribution, taking into account each=20 > > distribution's mean=20 > > > and standard devaition]. > > >=20 > > > I then provide the two roommates' scores and their respective class=20 > > > averages and standard deviations. Next, we calculate the=20 > > percentage,=20 > > > difference score (X - Xbar), and Z score for each raw score. > > >=20 > > > I try to work it out such that the "Better" score goes back=20 > > and forth=20 > > > depending on which measure is used. For example, raw score:=20 > > Pat wins;=20 > > > percentage score: Chris wins; difference score: Pat wins; Z-score,=20 > > > which I explain is the fairest way to compare scores from two=20 > > > distributions: Chris wins the bet (Chris did better relative to the=20 > > > rest of the scores in her class's distribution) and doesn't have to=20 > > > wash dishes for a week! > > >=20 > > > For a pictorial representation, I demonstrate by drawing two normal=20 > > > distributions (with differing variability) centred one under the=20 > > > other, indicating the two means and where one standard=20 > > deviation lies=20 > > > in each distribution, i.e., under the point of inflection.=20 > > Then I ask=20 > > > students to estimate how far along the respective X axis=20 > > each of the=20 > > > two raw scores would be found. If we've talked about percentile=20 > > > scores, I'll expalin how Z scores can be transformed into=20 > > percentile=20 > > > scores. > > >=20 > > > The same example can be used when comparing one person's=20 > > scores from=20 > > > two different tests (e.g., first and second midterm exams),=20 > > to check=20 > > > on improvement realtive to the rest of the class. Also takes into=20 > > > account the difficulty (mean) and variability (standard=20 > > deviation) of=20 > > > each of the two midterms (distributions with different properties). > > >=20 > > > As with many of the examples and demos I've collected over=20 > > the years,=20 > > > I can't recall where I found this demonstration (textbook,=20 > > > instructor's manual, TIPS, or if I made it up). > > > =20 > > > With a student such as Rod's who doesn't see the need to include=20 > > > standard deviations in a calculation, I'd draw out two=20 > > distributions=20 > > > one over the other with the same mean but with different=20 > > spreads, and=20 > > > show how it is easier to get a higher raw score on the distribution=20 > > > with the greater spread. > > >=20 > > > Perhaps Rod's student is having difficulty understanding=20 > > why it's not=20 > > > "cheating" to convert to Z scores because the examples of=20 > > running and=20 > > > swimming speeds are too dissimilar (minutes versus=20 > > seconds). Have you=20 > > > tried an example of running speed when comparing say four-year olds=20 > > > (slower speeds, less variability) to the same kids when they're 8=20 > > > years old (faster speeds and greater variability) to show=20 > > that, even=20 > > > though he runs faster now and is 5 seconds faster than the=20 > > average at=20 > > > each age, Person X might be a slower runner _relative to=20 > > other kids_=20 > > > as an 8 y.o. compared to when he was a 4 y.o.? > > >=20 > > > -Max > > >=20 > > > On Mon, 24 Feb 2003, Hetzel, Rod wrote: > > >=20 > > > > Hi everyone: > > > >=20 > > > > I need your help with something. I have a student who=20 > > just does not=20 > > > > understand z-scores. I have met with him for at least two hours=20 > > > > outside of class and he still doesn't understand the concept. In=20 > > > > particular, he doesn't seem to understand why you need to include=20 > > > > standard deviation in the calculation of z-scores. "Why=20 > > can't you=20 > > > > just compare the raw scores?" is his frequent question. =20 > > I explained=20 > > > > to him in various ways that the z-score is a transformed=20 > > score that=20 > > > > can take scores from two different distributions and put=20 > > them on a=20 > > > > common metric, that it gives you a summary statistic that=20 > > tells you=20 > > > > an individual's score in relation to the mean and=20 > > standard deviation, that it provides a way to compare > > > > scores from two different distributions, etc. =20 > > > >=20 > > > > Here is the example that my student keeps coming back to:=20 > > "Jack and=20 > > > > Jill are intense competitors, but they never competed=20 > > against each=20 > > > > other. Jack specialized in long-distance running and Jill was an=20 > > > > excellent sprint swimmer. As you can see from the=20 > > distributions in=20 > > > > each table, each was best in their event. Take the analysis one=20 > > > > step farther and use z-scores to determine who is the more=20 > > > > outstanding competitor." > > > >=20 > > > > LONG-DISTANCE RUNNING > > > > Jack: 37 min > > > > Bob: 39 min > > > > Joe: 40 min > > > > Ron: 42 min > > > >=20 > > > > SPRING SWIMMING > > > > Jill: 24 sec > > > > Sue: 26 sec > > > > Peg: 27 sec > > > > Ann: 28 sec > > > >=20 > > > > Here are the relevant statistics: > > > > RUNNING MEAN: 39.5 > > > > RUNNING SD: 1.803 > > > > JACK'S ZSCORE: -1.39 > > > >=20 > > > > SWIMMING MEAN: 26.25 > > > > SWIMMING SD: 1.479 > > > > JILL'S ZSCORE: -1.52 > > > >=20 > > > > When I have met with the student, he has not understood=20 > > how Jill is=20 > > > > the more outstanding competitor. He makes the comment=20 > > that Jack is=20 > > > > obviously the better competitor because Jack scored an entire 3=20 > > > > minutes faster than the next finisher whereas Jill scored only 2=20 > > > > seconds faster than her runner-up. "Why do you have to=20 > > even look at=20 > > > > the other scores in the distribution to tell that Jack is=20 > > the better=20 > > > > competitor? He finished a full three minutes ahead of his=20 > > > > competitors and Jill just barely finished ahead of her=20 > > competitors." =20 > > > > I have drawn some diagrams of normal distributions to show how=20 > > > > Jill's score on the distribution is further away from the=20 > > mean and=20 > > > > closer to the tail, but my student thinks that I am=20 > > somehow changing=20 > > > > the scores and cheating the system when I transform the=20 > > raw scores=20 > > > > to z-scores. Even after I show him how the position of the score=20 > > > > remains unchanged, he cannot grasp in this case how Jill=20 > > is the more=20 > > > > outstanding competitor. I've tried switching examples with him=20 > > > > (e.g., distributions of test scores, changing C temperature to F=20 > > > > temperature, etc.), but nothing seems to be sinking in. He has a=20 > > > > fairly high level of anxiety about statistics but tends=20 > > to cover it=20 > > > > up with humor and sarcasm. He took statistics with another=20 > > > > professor last semester and told me that all statistics=20 > > is a bunch of > > > > bull**** that serves no useful purpose other than obscuring the > > > > painfully-obvious truth. > > > >=20 > > > > So, I have two questions for all of you out there in TIPS land... > > > >=20 > > > > 1. Given what I've told you about the student's struggles with=20 > > > > z-scores, does anyone have any specific ideas on how to=20 > > present this=20 > > > > information to him? I think I'm in a rut with him and=20 > > need a fresh=20 > > > > way to explain this. > > > >=20 > > > > 2. Would anyone be willing to share with me any z-score examples=20 > > > > that you use for your own assignments and exams? I am=20 > > running out=20 > > > > of new examples to use with this student and was hoping=20 > > that perhaps=20 > > > > you would be willing to share some of your own examples. =20 > > This would=20 > > > > give my student some more opportunities to calculate z-scores > > > >=20 > > > > 3. How do you work with students who just don't seem to get=20 > > > > statistics? Everyone else in the class seems to=20 > > understand z-scores=20 > > > > well, but I'm struggling a bit in trying to reach this=20 > > student. I=20 > > > > find that I am hardly ever at a loss for words when teaching=20 > > > > clinical courses, but I'm reaching my limit with this=20 > > student. This=20 > > > > is certainly not my area of expertise, so I'm hoping that some of=20 > > > > you stats-people can help out with this! > > > >=20 > > > > Thanks for your assistance with this problem! > > > >=20 > > > > Rod > > > >=20 > > > > --- > > > > You are currently subscribed to tips as: [EMAIL PROTECTED] > > > > To unsubscribe send a blank email to=20 > > > > [EMAIL PROTECTED] > > > >=20 > > >=20 > > > Maxwell Gwynn, PhD [EMAIL PROTECTED] > > > Department of Psychology (519) 884-0710 ext 3854 > > > Wilfrid Laurier University > > > Waterloo, Ontario N2L 3C5 Canada > >=20 > > --- > > You are currently subscribed to tips as: [EMAIL PROTECTED] > > To unsubscribe send a blank email to=20 > > [EMAIL PROTECTED] > >=20 > > ---------------------------------------------------------------------- > > Subject: Re: parapsychology > From: "alexia elliott" <[EMAIL PROTECTED]> > Date: Tue, 25 Feb 2003 08:18:43 -0000 > X-Message-Number: 23 > > hello everyone > I have agreed to teach a short paranormal psychology course any ideas for > lesson plans!!! > or recommended books...... > all ideas appreciated > alexia > ----- Original Message ----- > From: "James Guinee" <[EMAIL PROTECTED]> > To: "Teaching in the Psychological Sciences" <[EMAIL PROTECTED]> > Sent: Monday, February 24, 2003 10:13 PM > Subject: Re: Classroom bully pulpits > > > > > This is a very good topic for discussion, because we all operate from > > > our biases whether we like it or not. > > > > Guess that's why we're called professors > > > > We profess...;) > > > > > > ******************************************************************* > > Jim Guinee, Ph.D. > > Director of Training & Adjunct Professor > > University of Central Arkansas Counseling Center > > 313 Bernard Hall Conway, AR 72035 USA > > > > "But in your hearts set apart Christ as Lord. > > Always be prepared to give an answer to everyone who > > asks you to give the reason for the hope that you have. > > But do this with GENTLENESS and RESPECT" > > [emphasis mine] [1 Peter 3:15] > > > > E-mail is not a secure means to transmit confidential > > information. The UCA Counseling Center staff does not > > use e-mail to discuss personal issues. The staff does > > not maintain 24-hour access to their e-mail accounts. > > ********************************************************************* > > > > --- > > You are currently subscribed to tips as: [EMAIL PROTECTED] > > To unsubscribe send a blank email to [EMAIL PROTECTED] > > > ---------------------------------------------------------------------- > > Subject: Question on a quote & need reference > From: [EMAIL PROTECTED] > Date: Tue, 25 Feb 2003 18:20:35 -0500 > X-Message-Number: 24 > > Hi Tipsters, > I am trying to find two pieces of information, and I can't seem to locate either. I am looking for a reference for a quote and a citation for a study. > > The quote goes something like this: > "Students will not care about your discipline unless they know you care about them." > > Second question: Does anyone know where the study can be found that identified a positive correlation between amount of smiling an instructor does and the ratings on student evaluations? > > I thought these items were in McKeachie's book, but I can't find either of the above there. > > Thanks in advance to anyone who can help! > > Kathleen Kleissler > Dept. of Psychology > Kutztown University > Kutztown PA 19530 > [EMAIL PROTECTED] > [EMAIL PROTECTED] > > > > > ---------------------------------------------------------------------- > > Subject: We've got it all wrong > From: "Bill Scott" <[EMAIL PROTECTED]> > Date: Tue, 25 Feb 2003 18:49:07 -0500 > X-Message-Number: 25 > > I just today asked a student to change the word "experiment" in her paper to > the word "study" because she simply asked different groups to respond to > questionnaires. Around here, I reserve the label "experiment" to mean a > study that randomly assigns participants to conditions. However I wonder if > I am not with it in the way we scientists think these days. I was looking at > NASA research and found that they seem to call any scientific activity an > experiment. > > Here's an example: > http://lsda.jsc.nasa.gov/scripts/cf/exper.cfm?exp_index=848 > > I have a problem with students who show me published studies that are very > poorly designed but they want to believe them because the studies are in > print. When NASA calls non-experiments "experiments" I find myself losing > credibility. Am I behind the times? > > Bill Scott > > > > ---------------------------------------------------------------------- > > Subject: Re: SD Woes > From: "Dr. Bob Wildblood" <[EMAIL PROTECTED]> > Date: Tue, 25 Feb 2003 20:30:08 -0500 > X-Message-Number: 26 > > In a little book that a colleague and I wrote nearly 30 years ago (and > for some completely unknown reason was not picked up by a publisher) we > said: > > "As a means of comparing dispersion among distributions, the > average deviation has some value since, simply stated, the greater the > average3 deviation, the greater the dispersion; however, when using the > average deviation to interpret scores within a distribution, it is less > useful since there is not precise mathematical relationship between the > average deviation and the actual locationof values within the deviation. > Since the average deviation is of such limited value, why is it > discussed in this text at all? The primary reason is because of the > historical relationship the average deviataion has with the variiance > and standard deviation, and second, and understanding of the concept of > deviation as espressed by the average deviation allows us to begin to > understand errors in prediction. That is, if you were to try to predict > the score of a given individual on a test, what is the single best > guess? Well, assuming that the data come from a normally distributed > population and that you are given no other information that the mean (or > some other measure of central tendency, it turns out that the mean is > the best predictor. > When we use the mean as the predicted score, the largest error you > can make is equal to the most expteme score minus the mean. Using any > other score, the maximum possible error is larger." > > I think that the text written by Runyon, Haber, (and I don't remember > who the third author is) has a reasonably good description of what we > used to call back in the early 70's the Average Deviation. > > ********************* > > ----- Original Message ----- > > From: "Wallace E. Dixon, Jr." <[EMAIL PROTECTED]> > > To: "Teaching in the Psychological Sciences" > > <[EMAIL PROTECTED]> > > Sent: Tuesday, February 25, 2003 12:40 PM > > Subject: SD Woes > > > > > > > >>Speaking of z-score woes, does anyone know how psychology ended up > >>with standard deviations rather than mean absolute differences from > >>the mean. Is it just because of ease of calculation? > >> > > > > ---------------------------------------------------------------------- > > Subject: Re: We've got it all wrong > From: "Christopher D. Green" <[EMAIL PROTECTED]> > Date: Tue, 25 Feb 2003 20:42:29 -0500 > X-Message-Number: 27 > > It's not so much a matter of "wrong" as it is "historically and disciplinarily > limited." See: > > Winston, Andrew S. and Blais, Daniel J. (1996) What counts as an experiment?: A > transdisciplinary analysis of textbooks, 1930-1970. American Journal of > Psychology 109(4):599-616. > > which can be found on-line at HTP Prints: > http://htpprints.yorku.ca/documents/docs/00/00/00/34/index.html > > Regards, > -- > Christopher D. Green > Department of Psychology > York University > Toronto, Ontario, Canada > M3J 1P3 > > e-mail: [EMAIL PROTECTED] > phone: 416-736-5115 ext. 66164 > fax: 416-736-5814 > http://www.yorku.ca/christo/ > =============================== > > > Bill Scott wrote: > > > I just today asked a student to change the word "experiment" in her paper to > > the word "study" because she simply asked different groups to respond to > > questionnaires. Around here, I reserve the label "experiment" to mean a > > study that randomly assigns participants to conditions. However I wonder if > > I am not with it in the way we scientists think these days. I was looking at > > NASA research and found that they seem to call any scientific activity an > > experiment. > > > > Here's an example: > > http://lsda.jsc.nasa.gov/scripts/cf/exper.cfm?exp_index=848 > > > > I have a problem with students who show me published studies that are very > > poorly designed but they want to believe them because the studies are in > > print. When NASA calls non-experiments "experiments" I find myself losing > > credibility. Am I behind the times? > > > > Bill Scott > > > > --- > > You are currently subscribed to tips as: [EMAIL PROTECTED] > > To unsubscribe send a blank email to [EMAIL PROTECTED] > > > > > > ---------------------------------------------------------------------- > > Subject: Re: SD Woes > From: "Karl L. Wuensch" <[EMAIL PROTECTED]> > Date: Tue, 25 Feb 2003 21:18:57 -0500 > X-Message-Number: 28 > > After you have taught bivariate linear regression (a two parameter model, > intercept and slope) to your students, stressing the least squares > criterion, you may want to point out that the mean is simply the intercept > in a single parameter linear model, that is, predicted Y = mean Y. The > variance is then just the MSE (residual variance) for that model and the > standard deviation is just the standard error. > > Once your students have grasped the idea that the mean is a single point in > one dimensional space that minimizes the SS about it, and that a regression > is defined in the same way in two dimensional space, you have them primed > for the leap to multiple regression and all of its special cases (like > ANOVA) and elaborations. > > Karl W. > ----- Original Message ----- > From: "jim clark" <[EMAIL PROTECTED]> > To: "Teaching in the Psychological Sciences" <[EMAIL PROTECTED]> > Sent: Tuesday, February 25, 2003 12:56 PM > Subject: Re: SD Woes > > > For example, the M is the center of a > distribution in the sense that the sum of squared deviations > about the mean (SS) is a minimum. > Jim > > > > ---------------------------------------------------------------------- > > Subject: Re: We've got it all wrong > From: "Annette Taylor, Ph. D." <[EMAIL PROTECTED]> > Date: Tue, 25 Feb 2003 18:42:35 -0800 > X-Message-Number: 29 > > Hi Bill: > > I teach research methods and spend quite some time repeatedly over the semester > talking about research versus experiment and why in science it is so important > to use the denotative meaning of words, and not connotative. thus, what NASA is > doing flies in the face of that, and is a disservice IMHO. > > Annette > > Quoting Bill Scott <[EMAIL PROTECTED]>: > > > I just today asked a student to change the word "experiment" in her paper to > > the word "study" because she simply asked different groups to respond to > > questionnaires. Around here, I reserve the label "experiment" to mean a > > study that randomly assigns participants to conditions. However I wonder if > > I am not with it in the way we scientists think these days. I was looking at > > NASA research and found that they seem to call any scientific activity an > > experiment. > > > > Here's an example: > > http://lsda.jsc.nasa.gov/scripts/cf/exper.cfm?exp_index=848 > > > > I have a problem with students who show me published studies that are very > > poorly designed but they want to believe them because the studies are in > > print. When NASA calls non-experiments "experiments" I find myself losing > > credibility. Am I behind the times? > > > > Bill Scott > > > > > > > > --- > > You are currently subscribed to tips as: [EMAIL PROTECTED] > > To unsubscribe send a blank email to [EMAIL PROTECTED] > > > > > Annette Kujawski Taylor, Ph. D. > Department of Psychology > University of San Diego > 5998 Alcala Park > San Diego, CA 92110 > [EMAIL PROTECTED] > > ---------------------------------------------------------------------- > > Subject: What is an experiment? > From: "Karl L. Wuensch" <[EMAIL PROTECTED]> > Date: Tue, 25 Feb 2003 22:48:17 -0500 > X-Message-Number: 30 > > What is an experiment? In quite simple words, "you do something and see > what happens." The critical element is that you manipulate the putative > causal variable ("you do something") rather than just passively observe. > This does not, IMHO, necessarily involve random assignment of experimental > units to conditions -- if it did, all research involving only > within-subjects comparisons would be considered nonexperimental. > > When a chemist experiments, does she randomly assign experimental units > to conditions? No, she achieves control by other means. She does > manipulate variables of interest and then observes what happens following > such manipulations. > > Karl W. > > Quoting Bill Scott <[EMAIL PROTECTED]>: > > > I just today asked a student to change the word "experiment" in her paper > to > > the word "study" because she simply asked different groups to respond to > > questionnaires. Around here, I reserve the label "experiment" to mean a > > study that randomly assigns participants to conditions. However I wonder > if > > I am not with it in the way we scientists think these days. I was looking > at > > NASA research and found that they seem to call any scientific activity an > > experiment. > > > > > --- > > END OF DIGEST > > --- > You are currently subscribed to tips as: [EMAIL PROTECTED] > To unsubscribe send a blank email to [EMAIL PROTECTED] >
