Re: meeting probability question.
In article <[EMAIL PROTECTED]>, Patrick D. Rockwell <[EMAIL PROTECTED]> writes >I've posted this before, but right now I can't find the answers that >I've gotten, and I'd like to repost to see if I can get a simpler >solution than what I've gotten before. > >Let's say that n people agree to meet between 2:00 P.M. and 3:00 P.M.. >If each person >is willing to wait the same amount of time d where 0<=d<=1 and the >amount of minutes >the person is willing to wait is d * 60 minute (if d=0.25, means that >the people will >wait 15 minutes) Should we assume that these people all actually want to meet each other, or that some of them would prefer to avoid others, or that they act randomly? If randomly, do they arrive at a random time between 2 and 3, and go home anyway at 3, or choose their random interval so as to fit it all into the 2-3 slot? Nick -- Nick Wedd[EMAIL PROTECTED]
WebCT in statistics courses?
Are there any statistics teachers who are constructing courses or course components in WebCT? I would very much like to get in contact with you, because there must be lots of material - quizzes, links,... - we could share. By the way, does anyone know why I can't subscribe to edstat-l? No response whatsoever when I try to get in contact with the listserv. --robert Robert Lundquist Div of Quality Technology & Statitics Lulea University of Technology Sweden [EMAIL PROTECTED]
GLM vs. ANOVA
Will someone please enlighten me as to the general differences between GLM and ANOVA. In my short journey through graduate statistics, I somehow assumed they were the same. Thanks. Sent via Deja.com http://www.deja.com/ Before you buy.
Re: software and code information
In article <01bf3442$bfca8630$[EMAIL PROTECTED]>, [EMAIL PROTECTED] (Beatriz Margolis) wrote: > I would appreciate if somebody in the list could help me with the following > questions: > a. Where may I found a description of the internal format of a .xls > file? The internal format of an XLS file is documented at 'www.wotsit.org'. Regards, John Wallis. Independent Software Developer. Sent via Deja.com http://www.deja.com/ Before you buy.
Cox Hazard Function Plots
Hi - I often use Cox proportional hazards modelling (SPSS)for analyzing patient survival data. Although I know how the hazard function plot is generated I'm not certain how to interpret it and have been ignoring it up until now. I'd appreciate it if anyone could give me a quick explanation of what these plots can tell me and whether if I should be looking at this for every model. Thanks in advance. V Sent via Deja.com http://www.deja.com/ Before you buy.
Re: teaching statistical methods by rules?
Robert Dawson wrote: > Exactly... An example - we've been using Devore & Peck, which > unfortunately introduces the Z test for the mean, supposedly for pedagogical > reasons but without nearly a strong enough indication of this. A lot of > students infer a rule "if n>30 use z rather than t" despite my repeated > statements that Z is NEVER a better test for the mean under circumstances > they are likely to encounter [in psychology]. Of course, if they are cutting > lectures that day they won't hear the warning... Okay, I'll bite. Why?
Re: GLM vs. ANOVA
On Wed, 15 Dec 1999 [EMAIL PROTECTED] wrote:
> Will someone please enlighten me as to the general differences between
> GLM and ANOVA. In my short journey through graduate statistics, I
> somehow assumed they were the same.
Parallelling your short journey, here is a short distinction in one
sentence. (Some might want to quibble about details.)
GLM, as its name (General Linear Models) implies, is more
general than ANOVA (ANalysis Of VAriance), which is that subset of GLM
whose predictors (aka independent variables, aka factors) are categorical
(aka of nominal scale).
To elaborate:
In some contexts (e.g., for some packaged statistical programs)
ANOVA -- which in these contexts usually means "factorial ANOVA" -- is
further restricted to balanced designs, sometimes to balanced complete
designs.
In other contexts (as in "the ANOVA summary table"), ANOVA is
much more general -- as general as GLM, actually. The phrase often
refers to the partitioning of variance (in a response variable, aka a
dependent variable or DV) into random ("error") and systematic
components. (There may be more than one of each kind, reflecting the
structure of the design that generated the data.) In this sense, one
encounters analysis of variance as part of the output of a multiple
linear regression (MLR) analysis. (MLR is that subset of GLM whose
predictors are [treated as] "quantitative", meaning quasi-continuous,
aka of interval scale.)
-- DFB.
Donald F. Burrill [EMAIL PROTECTED]
348 Hyde Hall, Plymouth State College, [EMAIL PROTECTED]
MSC #29, Plymouth, NH 03264 603-535-2597
184 Nashua Road, Bedford, NH 03110 603-471-7128
Re: teaching statistical methods by rules?
> Robert Dawson wrote: > > Exactly... An example - we've been using Devore & Peck, which > > unfortunately introduces the Z test for the mean, supposedly for pedagogical > > reasons but without nearly a strong enough indication of this. A lot of > > students infer a rule "if n>30 use z rather than t" despite my repeated > > statements that Z is NEVER a better test for the mean under circumstances > > they are likely to encounter [in psychology]. Of course, if they are cutting > > lectures that day they won't hear the warning... > > Okay, I'll bite. Why? Recall that "the" z test for the mean is actually two often-confused tests. The first, the "Z test with sigma", involves exact prior knowledge of sigma. This is an artificial situation very unlikely to arise if the variation is intrinsic to what is being measured. If the variation comes from a separate source (eg, instrumentation) it is possible that one might know sigma but not mu - but this is more of an engineering scenario, and probably oversimplified even then. The "Z test with s" is nothing but an unnecessary approximation of the t distribution for n>>1 degrees of freedom by the z distribution. The most that can be said for it is that if n is large it is not wrong by very much. However: -inasmuch as the outcomes, p values, or confidence intervals obtained differ from those of the t procedures, the z outcomes are wrong and the t procedures are right. Z is never mathematically better. -Students need to learn how to use both tables anyhow. Using "z above thirty" does not reduce the amount students need to learn. If they are using a stats package the same principle applies. For this and the next two reasons, z is never pedagogically better. Caveat: Old fashioned t tables fashioned after the tradition the Church of the Holy 5% make it hard to compute p values that are not round numbers. See Devore & Peck's 3rd edition, or my article "Turning the Tables - a t-table for Today" in JSE a couple years ago, for alternatives. -The test-selection decision process is made more complicated if the "z over thirty" rule is added, not less so. -Students tend to somehow twist the "z over thirty" rule around to say (to them) "t is incorrect over thirty". This could be embarrassing to them in later life (eg, if they were refereeing a paper and demanded that the author change a t test to a z test). -Robert Dawson
Re: GLM vs. ANOVA
In SAS, ANOVA is for design of one-way and balanced multi-way classifications. The main point here is "balanced." ANOVA may be used for unbalanced data if the factors do not interact, otherwise, GLM is a better procedure. Chong-ho (Alex) Yu, Ph.D., CNE, MCSE Instruction and Research Support Information Technology Arizona State University Tempe AZ 85287-0101 Voice: (602)965-7402 Fax: (602)965-6317 Email: [EMAIL PROTECTED] URL:http://seamonkey.ed.asu.edu/~alex/
Deadline for MMBIA 2000 is extended to Jan 10, 1999
ended to Jan 10, 1999 The deadline for paper submission for MMBIA has been extended; papers must be received by Monday January 10th, 1999. However, authors should send email in advance to [EMAIL PROTECTED] with the following information: 1) list of authors 2) title 3) top two matching workshop areas 4) brief description of the paper's contributions, so that a paper number can be assigned. Further details can be found at www.lems.brown.edu/vision/conferences/MMBIA2000 - End Included Message -
RE: teaching statistical methods by rules?
Hello Robert and All -- Please forgive the intrusion of a lurker in a domain above my pay grade, as it were, but I have a slight question... > The "Z test with s" is nothing but an unnecessary approximation of the > t distribution for n>>1 degrees of freedom by the z distribution. The most > that can be said for it is that if n is large it is not wrong by very much. > It would seem to me that more than this most can be said. If my reading of the central limit theorem is up to snuff, I should be able to use the "Z test with s" without an underlying assumption of the normality of the parent population, required for the t. I am not etching n = 30 in stone, here -- but there is _some_ large n that will make the underlying sampling distribution of the mean sufficiently close to normal to justify the "Z with s." So how far off base is my understanding? -- Chris Chris Olsen George Washington High School 2205 Forest Dr. S.E. Cedar Rapids, IA 52403 (319)-398-2161 [EMAIL PROTECTED]
Re: GLM vs. ANOVA
[EMAIL PROTECTED] wrote: > > Will someone please enlighten me as to the general differences between > GLM and ANOVA. In my short journey through graduate statistics, I > somehow assumed they were the same. If you are referring the SAS procedures GLM And ANOVA, ANOVA works only on balanced designs, GLM works on any design. If you are referring to GLM and ANOVA in general, ANOVA refers to situations where your independent variables are classification variables, while GLM can be used for any combination of continuous or classification independent variables. -- Paige Miller Eastman Kodak Company [EMAIL PROTECTED] "It's nothing until I call it!" -- Bill Klem, NL Umpire
z and t
of course ... if one believes that NEITHER really give you any useful information about population parameters ... means ... or correlation values, etc. ... remember, the t distribution and associated tests using it, is not JUST used for means ... THEN, maybe this distinction is trivial ... in all cases ... and the effort needed (and it does take SOME effort) to make this distinction is not worth the instructional time devoted to it but of course, this is just one view in cyberspace ... (and my eudora keeps telling me that "cyberspace" is a misspelling it needs to get with the program!) -- 208 Cedar Bldg., University Park, PA 16802 AC 814-863-2401Email mailto:[EMAIL PROTECTED] WWW: http://roberts.ed.psu.edu/users/droberts/drober~1.htm FAX: AC 814-863-1002
Re: GLM vs. ANOVA
in minitab for example ... the command ANOVA insists on equal ns in the cells ... glm does not ... this is not a conceptual difference as don was pointing out ... but, it is important IF you happen to be using minitab -- 208 Cedar Bldg., University Park, PA 16802 AC 814-863-2401Email mailto:[EMAIL PROTECTED] WWW: http://roberts.ed.psu.edu/users/droberts/drober~1.htm FAX: AC 814-863-1002
interactive statistics tutorials and applets
Hi Robert, We have a website featuring interactive applets with tutorials for some introductory concepts. The applet for power is particularly cool - the user can control effect size, n, or power, and see dynamic connections. The URL is wise.cgu.edu These are free to use, though we appreciate being told about usage. Cheers, Dale Berger Dale Berger Professor and Chair, Psychology Claremont Graduate University 123 East Eighth Street Claremont, CA 91711 FAX: 909-621-8905 Phone: 909-621-8084 http://www.cgu.edu/faculty/bergerd.html - Original Message - From: Robert Lundquist <[EMAIL PROTECTED]> To: <[EMAIL PROTECTED]> Sent: Wednesday, December 15, 1999 5:33 AM Subject: WebCT in statistics courses? > Are there any statistics teachers who are constructing courses or course > components in WebCT? I would very much like to get in contact with you, > because there must be lots of material - quizzes, links,... - we could > share. > > By the way, does anyone know why I can't subscribe to edstat-l? No > response whatsoever when I try to get in contact with the listserv. > > --robert > > Robert Lundquist > Div of Quality Technology & Statitics > Lulea University of Technology > Sweden > > [EMAIL PROTECTED] >
Millennium Mathematical Frieze
Please let me know if you would like to see FREE sample pages from the QED Millennium Mathematical Frieze. This is our calendar for the New Year, and takes the place of FunMaths!, which has receeived high acclaim in recent years. Like FunMaths, the Millennium Frieze contains countless interesting mathematical problems and a theme per month. Its 12 full-colour posters outline the history of mathematics and science since the year 1000. The project is supported by Maths Year 2000, the UK government's official contribution to World Mathematical Year. The posters are well illustrated in full colour. Written in a chatty and contemporary newspaper style, topics covered include: * "Big zero" - how the number zero reached Europe via India, Africa and the Middle East * Geoffrey Chaucer and the astrolabe * the history of numbers * Newton and his apple (of course!), but also the less-known theory of rainbows * the "history of the future" - where will maths be in the year 2100? The Millennium Frieze costs 9.50 UK pounds for one copy (20 pounds for 3, or £50 for 10). This includes UK postage to one address. We will mail direct to your friends if you wish to use them as presents. Christmas delivery is still possible (just!). Send us the details now, and we will do the rest. Substantial trade discounts available. Please send your mailing address if you would like to see some sample pages, plus credit card authorisation if you would like to buy a copy (FULL MONEY BACK GUARANTEE). The Millennium Frieze is being sold on behalf of MatheMagic, the new charitable organisation promoting the popularisation of mathematics. All retail profits go to MatheMagic. Yours sincerely JOHN BIBBY QED/MatheMagic 1 Straylands Grove York YO31 1EB, England (+44) Tel: 01904-424242Fax: 01904-424381Email: [EMAIL PROTECTED] == PS: We had some 1300 visitors at this year's York Maths FunFair. Make a note of next year's date NOW: October 21st 2000. Further details: www.anglia.co.uk/education/mathsnet/ymff/ or email [EMAIL PROTECTED] or phone: 01904-424242
RE: teaching statistical methods by rules?
i would highly recommend a paper by ken brewer ... titled: behavioral statistics textbooks: source of myths and misconceptions, Journal of Educational Statistics .. Fall, 1985, V 10, #3, pp 252-268 ... for an excellent discussion of the CLT At 12:20 PM 12/15/99 -0600, Olsen, Chris wrote: > Hello Robert and All -- > > It would seem to me that more than this most can be said. If my reading >of the central limit theorem is up to snuff, I should be able to use the "Z >test with s" without an underlying assumption of the normality of the parent >population, required for the t. I am not etching n = 30 in stone, here -- >but there is _some_ large n that will make the underlying sampling >distribution of the mean sufficiently close to normal to justify the "Z with >s." -- 208 Cedar Bldg., University Park, PA 16802 AC 814-863-2401Email mailto:[EMAIL PROTECTED] WWW: http://roberts.ed.psu.edu/users/droberts/drober~1.htm FAX: AC 814-863-1002
Re: teaching statistical methods by rules?
I thought there was a chance it would hinge on "better". Since it was "never" that got the emphasis, I thought I'd ask. The problem for me with the statement "Z is NEVER a better test for the mean under circumstances they are likely to encounter [in psychology]" is that it reads like an indictment. While technically correct in some sense, the use of percentiles of the standard normal distribution in place of those from the t distribution for large samples doesn't make much (any?) difference, so the NEVER rule struck me as unnecessary overkill. In fact, in place of the precise 0.05 two-sided critical value of 1.96, many people use 2, which is the critical value for a t with 60 d.f. > However: > > -inasmuch as the outcomes, p values, or confidence intervals > obtained > differ from those of the t procedures, the z outcomes are wrong and the t > procedures are right. Z is never mathematically better. I would think that for percentiles of the t distribution to be more right than percentiles of the standard normal distribution for large degrees of freedom, underlying normality would be critical. However, I haven't done any formal study of this and will defer to anyone who has. > Caveat: Old fashioned t tables fashioned after the tradition the > Church > of the Holy 5% make it hard to compute p values that are not round numbers. So maybe z is sometimes better? In fact, it's hard to imagine circumstances where anyone dealing with real data will not be using a computer, if only to establish an audit trail. Since software insists on using t, the question is moot for all practical purposes.
Re: teaching statistical methods by rules?
My initial thought was that teaching statistical methods by rules was a bad idea, but after reading some of the posts I realize that it wasn't rules per se that have bugged me in the past, but rules that are either not very good or rules that make it appear that correct application of statistical methods can be achieved by following a tree diagram. I think that students need to move from the concrete to the abstract as their knowlege and skill base improves. Rules provide a concrete place for them to start from. The important thing is that the rules provided are sensible and that students are encouraged to understand that the rules are often guidelines not absolutes. M. Granaas On Mon, 13 Dec 1999, EAKIN MARK E wrote: > I just received a review which stated that statistics should not be taught > by the use of rules. For example a rule might be: "if you wish to infer > about the central tendency of a non-normal but continuous population using > a small random sample, then use nonparametrics methods." > > I see why rules might not be appropriate in mathematical statistics > classes where everything is developed by theory and proof. However I teach > statistical methods classes to business students. > > It is my belief that if faculty do not give rules in methods classes, then > students will infer the rules from the presentation. These > student-developed rules may or may not be valid. > > I would be intested in reading what other faculty say about > rule-based teaching depending on whether you teach theory or methods > classes. > > Mark Eakin > Associate Professor > Information Systems and Management Sciences Department > University of Texas at Arlington > [EMAIL PROTECTED] or > [EMAIL PROTECTED] > > *** Michael M. Granaas Associate Professor[EMAIL PROTECTED] Department of Psychology University of South Dakota Phone: (605) 677-5295 Vermillion, SD 57069 FAX: (605) 677-6604 *** All views expressed are those of the author and do not necessarily reflect those of the University of South Dakota, or the South Dakota Board of Regents.
Re: Cox Hazard Function Plots
The best and most intuitive interpretation of hazard rate and plot I've ever read is in the book by Kleinbaum. The complete reference is: Kleinbaum DG. Survival analysis. A self-learning text. N. York, Springer, 1996. -- -- Juan Ramon Lacalle e-mail: [EMAIL PROTECTED] Unidad de Bioestadistica Departamento de Ciencias Sociosanitarias Universidad de Sevilla Avda. Sanchez Pizjuan s/n Tfno: +34 5 4551771 41012 Sevilla Fax : +34 5 4556481 --
dissertation
Hello all -- I am a PhD student in biostats. who will be starting the dissertation process in about a year and a half. Could anyone direct me to some useful books/web sites/other references on beginning, researching, writing the dissertation? Most of the books I have found so far seem to be written more for students in non-science related fields. TIA, -- JL
Re: dissertation
"J.L." wrote: > I am a PhD student in biostats. who will be starting the dissertation > process in about a year and a half. Could anyone direct me to some > useful books/web sites/other references on beginning, researching, > writing the dissertation? Most of the books I have found so far seem > to be written more for students in non-science related fields. I may be misunderstanding the question, but many of these details are specific to the university and program, even at the early stages. For example, some programs point students in the general direction of a research topic; others leave students to sink or swim according to their ability to formulate a proper proposal. Dare I say there are even programs that tell students exactly what to work on? You should start with your advisor and director of graduate studies. Since you're 18 months away, you should consult with senior graduate students. You should also look at recent dissertations from your department. Your question is entirely reasonable and deserves an answer. Many programs expect this information to be transferred informally, almost by osmosis. This is sufficient for some students, but doesn't have to be for all. Don't be afraid to ask.
Re: teaching statistical methods by rules?
Chris Olsen wrote: > It would seem to me that more than this most can be said. If my reading > of the central limit theorem is up to snuff, I should be able to use the "Z > test with s" without an underlying assumption of the normality of the parent > population, Yes, as an unnecessary approximation, > required for the t. and no. The utility of either test for non-normal populations depends on the central limit theorem and related results. "Z with s" relies on the same assumptions about the sampling distribution of s and mu that the t test does. > I am not etching n = 30 in stone, here Good... There are distributions (ie, the normal distributions) for which n=1 suffices. There are distributions (eg. lottery prizes) for which n=1 is too small. If t won't work for a population, z-with-s won't either. > but there is _some_ large n that will make the underlying sampling > distribution of the mean sufficiently close to normal to justify the "Z with > s." No - at least not if you mean "there is some large n independent of the distribution..." -RJMD
Re: teaching statistical methods by rules?
Jerry Dallal wrote: >The problem for me > with the statement "Z is NEVER a better test for the mean under > circumstances they are likely to encounter [in psychology]" is that it > reads like an indictment It is. The last thing students in Intro Stats need is one more red herring. > > Caveat: Old fashioned t tables fashioned after the tradition the > > Church > > of the Holy 5% make it hard to compute p values that are not round numbers. > > So maybe z is sometimes better? Under certain artificial "desert island" scenarios, yes. But: >In fact, it's hard to imagine > circumstances where anyone dealing with real data will not be using a > computer, if only to establish an audit trail. A new and different motive > Since software > insists on using t, the question is moot for all practical purposes. No, MINITAB (frinstance) will use Z if you insist. (And a pistol will shoot you in the foot if you point it there & pull the trigger.) But it is rarely the right thing to do. -Robert Dawson
RE: dissertation
I'm not sure if this will be pertinent to your field as it is written more from a psychologist's reference, but for an excellent text try: Cone, J. D., & Foster, S. L. (1993). Dissertations and theses from start to finish. Washington, DC: American Psychological Association. Dale Glaser -Original Message- From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED]] On Behalf Of J.L. Sent: Wednesday, December 15, 1999 12:18 PM To: [EMAIL PROTECTED] Subject:dissertation Hello all -- I am a PhD student in biostats. who will be starting the dissertation process in about a year and a half. Could anyone direct me to some useful books/web sites/other references on beginning, researching, writing the dissertation? Most of the books I have found so far seem to be written more for students in non-science related fields. TIA, -- JL
Re: ANOVA with proportions
On 14 Dec 1999 08:40:18 -0800, [EMAIL PROTECTED] (William B. Ware) wrote: > As I recall, there was an article by Lunney et al that appeared in the > Journal of Educational Measurement that examined the use of ANOVA with "1" > and "0" as the DV. I believe that they concluded that distortion was > minimal when the distributions were within an 80/20 split... I think that > the article was in the early 70s, perhaps 1971. > > As Don has noted, proportions are means... which will be symmetrically > distributed when the split is about 50/50. Apparently, the Central Limit > Theorem applies as long as sample size is sufficiently large... < ... > The problem that I am aware of has nothing to do with the Central Limit Theorem -- and I'm not positive what that problem is supposed to be -- and everything to do with additivity and linearity. If you have a 2x2 table, and the four groups have means on the dichotomous outcome, of (1%, 4%; 4%, 16%), do you decide that this is additive and has an interaction, or do you label it a simple pair of multiplicative main-effects? - The interaction apparent by ANOVA does not exist in the log-linear model. So it may be worth using the ANOVA computer-procedure, and ignoring the interaction, if it is a lot simpler to use that computer program. I am willing to use the systematic absence of the interaction as evidence that the multiplicative model is the better one. The linearity-artifact does not exist for a simple t-test, one-way ANOVA, or regression with small effect size (low R-squared, AND low Odds ratios). So far as I know, you can do those ANOVA analyses with proportions that may be beyond 20%, with very little loss of power. Further, you should note, you have the risk of similar linearity-artifacts when you analyze continuous variables that have been re-expressed as their *rank-transformed values*. That applies for essentiall the same set of models -- multiway, multi-variable, or high R-squared. -- Rich Ulrich, [EMAIL PROTECTED] http://www.pitt.edu/~wpilib/index.html
Re: ANOVA with proportions
On 14 Dec 1999 16:38:00 -0800, [EMAIL PROTECTED] (Rich Strauss) wrote: < snip > > I'll just add the usual caveat that hasn't yet been mentioned in these > responses about proportions: the transformations, use of the binomial, and > comment about proportions just being means all assume that the data really > are proportions, not ratios -- that is, that the denominator is fixed among > all values, not variable. The problem is that many people use the terms > interchangably, talking about proportions or percentages when they're > actually dealing with ratios. Ratios are one problem. Right -- be careful about them. But Proportions are another problem when the denominators are not the same. If one subject is scored a proportion which is none-for-one, 0/1= 0%, that is usually a score with far less "information," and bigger standard error on the response, than if another subject rates 0/20=0%. I am not referring just to zero -- if subjects have data based on vastly different Ns, it may be wasteful to lump them based on percents. One approach that seemed useful for some analyses of genotypes was: do separate analyses for different N, and then combine those analyses. -- Rich Ulrich, [EMAIL PROTECTED] http://www.pitt.edu/~wpilib/index.html
t vs. z
- Forwarded message from Olsen, Chris - It would seem to me that more than this most can be said. If my reading of the central limit theorem is up to snuff, I should be able to use the "Z test with s" without an underlying assumption of the normality of the parent population, required for the t. I am not etching n = 30 in stone, here -- but there is _some_ large n that will make the underlying sampling distribution of the mean sufficiently close to normal to justify the "Z with s." - End of forwarded message from Olsen, Chris - (x-bar minus hyp.x-bar)/sigma approaches a normal distribution but (x-bar minus hyp.x-bar)/s approaches t if x is normal. If x is not normal, it is true that (x-bar minus hyp.x-bar)/s eventually approaches a normal distribution, too, but so does t. This leaves it an open question whether the mystery distribution is betwen the t approaching z or t'other side of t from z yet still approaching z. 1/x, 2/x and 3/x all aproach 0 for large n. The fact that 3/x approaches 1/x does not mean it ever gets closer than 2/x does. _ | | Robert W. Hayden | | Department of Mathematics / | Plymouth State College MSC#29 | | Plymouth, New Hampshire 03264 USA | * | Rural Route 1, Box 10 /| Ashland, NH 03217-9702 | ) (603) 968-9914 (home) L_/ [EMAIL PROTECTED] fax (603) 535-2943 (work)
Re: dissertation
One of the first things to do is to pose your queries with a senior faculty member with whom you are acquainted. Perhaps, you might even boldly bounce a few subject/topic areas for your thesis with him/her. Some professors have favorite dissertations "on the shelf" portraying what has been acceptable in the past. Take a look at those to get a general idea. Usually, university graduate libraries will have dissertations and/or abstracts for visual review as well. Many graduate schools have a step by step manual or handbook on the various procedures for the progression toward the doctorate starting with obtaining a committee chair, writing an acceptable proposal and ending with a successful defense of the thesis. Doing independent research is a lonely task and you must be prepared for a struggle right from the start. There are lots of hurdles and roadblocks, but with patience and diligence plus a modicum of talent you'll make it. Don't get discouraged. By the time you are finished, you'll know more about that dissertation than anyone else if all goes correctly. You probably have wondered how some of us (faculty) ever made it through the system. In my case, the same way you will...bumbling and stumbling. Good Luck. j. williams In article <838sqb$26ho$[EMAIL PROTECTED]>, "J.L." <[EMAIL PROTECTED]> wrote: > >Hello all -- > >I am a PhD student in biostats. who will be starting the dissertation >process in about a year and a half. Could anyone direct me to some >useful books/web sites/other references on beginning, researching, >writing the dissertation? Most of the books I have found so far seem >to be written more for students in non-science related fields. > >TIA,
Mauchly sphericity test
--2D8C3C50CB5B5CF7F6B17A7A Content-Type: text/plain; charset=us-ascii Content-Transfer-Encoding: 7bit Hi, can anyone tell me more about the Mauchly sphericity test? Exact problem: I am using spss and the Mauchly sphericity test prints out: Mauchly-W = 0.000 approx-chi2 = . df = 9 significance = . Does this mean the within-subject factors fail to meet the assumption of sphericity? I guess yes, but I am not shure. Thanks for your help, Eike -- _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ Eike Rietzel Gesellschaft fuer Schwerionenforschung Biophysik Planckstr. 1 64291 Darmstadt fon: +49-6159-71-2156 fax: +49-6159-71-2106 _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ --2D8C3C50CB5B5CF7F6B17A7A Content-Type: text/html; charset=us-ascii Content-Transfer-Encoding: 7bit Hi, can anyone tell me more about the Mauchly sphericity test? Exact problem: I am using spss and the Mauchly sphericity test prints out: Mauchly-W = 0.000 approx-chi2 = . df = 9 significance = . Does this mean the within-subject factors fail to meet the assumption of sphericity? I guess yes, but I am not shure. Thanks for your help, Eike -- _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ Eike Rietzel Gesellschaft fuer Schwerionenforschung Biophysik Planckstr. 1 64291 Darmstadt fon: +49-6159-71-2156 fax: +49-6159-71-2106 _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ --2D8C3C50CB5B5CF7F6B17A7A--
Re: meeting probability question.
Nick Wedd wrote: > > In article <[EMAIL PROTECTED]>, Patrick D. Rockwell > <[EMAIL PROTECTED]> writes > >I've posted this before, but right now I can't find the answers that > >I've gotten, and I'd like to repost to see if I can get a simpler > >solution than what I've gotten before. > > > >Let's say that n people agree to meet between 2:00 P.M. and 3:00 P.M.. > >If each person > >is willing to wait the same amount of time d where 0<=d<=1 and the > >amount of minutes > >the person is willing to wait is d * 60 minute (if d=0.25, means that > >the people will > >wait 15 minutes) > > Should we assume > that these people all actually want to meet each other, or > that some of them would prefer to avoid others, or > that they act randomly? > > If randomly, do they > arrive at a random time between 2 and 3, and go home anyway at 3, or > choose their random interval so as to fit it all into the 2-3 slot? > > Nick > -- > Nick Wedd[EMAIL PROTECTED] I guess randomly. They want to meet eachother but arrive at random times and leave at 3:00 P.M. so that P(All meet) and p(None meet) would fit the formulas given in my first post, IF they were willing to wait the same amount of time. ANYONE? :-) -- Patrick D. Rockwell mailto:[EMAIL PROTECTED] mailto:[EMAIL PROTECTED] mailto:[EMAIL PROTECTED]
dissertation
- Forwarded message from J.L. - I am a PhD student in biostats. who will be starting the dissertation process in about a year and a half. Could anyone direct me to some useful books/web sites/other references on beginning, researching, writing the dissertation? Most of the books I have found so far seem to be written more for students in non-science related fields. - End of forwarded message from J.L. - I would like to encourage this student, other students, and faculty to consider breaking the rules. I had a joint major in mathematics and education. In math. the rules are pretty much "write a publishable paper" and dissertations tend to be very short (in page count, anyway!). Education had a standard template. However, the chair of the Math. Dept. said he was tired of dissertations that were never read by anyone and proposed that I write one that could be understood by an educated layperson -- say, a school board member. So, I did. It did not even SOUND like a dissertation, I'm proud to say!-) _ | | Robert W. Hayden | | Department of Mathematics / | Plymouth State College MSC#29 | | Plymouth, New Hampshire 03264 USA | * | Rural Route 1, Box 10 /| Ashland, NH 03217-9702 | ) (603) 968-9914 (home) L_/ [EMAIL PROTECTED] fax (603) 535-2943 (work)
