Random numbers from 1 to 16
What would be the simplest and solid way to generate random numbers from 1 to 16 only? I don't have any compilers or languages handy except for an APL interpreter that's quite old but still powerful and BASIC that comes with the DOS operating system. I gather there must be some code to do a small pseudo-random number generator somewhere? Thanks, Adam Sundor === This list is open to everyone. Occasionally, less thoughtful people send inappropriate messages. Please DO NOT COMPLAIN TO THE POSTMASTER about these messages because the postmaster has no way of controlling them, and excessive complaints will result in termination of the list. For information about this list, including information about the problem of inappropriate messages and information about how to unsubscribe, please see the web page at http://jse.stat.ncsu.edu/ ===
Software for Reliability Generalization Theory?
Hello, Does anyone know of any software that conducts reliability analyses using the generalizability approach of Cronbach et al? Bill Chambers === This list is open to everyone. Occasionally, less thoughtful people send inappropriate messages. Please DO NOT COMPLAIN TO THE POSTMASTER about these messages because the postmaster has no way of controlling them, and excessive complaints will result in termination of the list. For information about this list, including information about the problem of inappropriate messages and information about how to unsubscribe, please see the web page at http://jse.stat.ncsu.edu/ ===
Re: Data assumptions in Log-linear models
Bojanowscy wrote: > > Hello > > I would be very grateful if anyone of you could give me (in short) a list of > assumptions about data (dimensions, frequencies in contingency table, > distribution etc) under which one can perform Loglinear analysis (ML > estimation). Log-linear analysis assumes that the data follows a Poisson distribution - this would be a counting problem (of the sort 'how many butterflies will fly past me today?') > ...And, if there are any diffrences, in Logit modelling. > Yes! This would assume a Binomial distribution - this is sampling from a finite group with replacement (something like 'of the 25 species of butterfly in this area, how many have I seen today?). Both models assume that the observations are independent, and that there is a constant rate or probability (butterflies may not meet these assumptions!) > I've read a few books in the subject (written for social scientists, so not > very "mathematical"), but I haven't found a full list of assumptions > underlying these procedures. > The 'classic' is probably McCullagh & Nelder (1989) Generalized Linear Models (2nd ed., Chapman & Hall). Although it's primarily aimed at statisticians, it is quite readable. Bob (who would rather spend today counting butterflies) -- Bob O'Hara Metapopulation Research Group Division of Population Biology Department of Ecology and Systematics PO Box 17 (Arkadiankatu 7) FIN-00014 University of Helsinki Finland tel: +358 9 191 7382 fax: +358 9 191 7301 email: [EMAIL PROTECTED] To induce catatonia, visit: http://www.helsinki.fi/science/metapop/ I have yet to see any problem, however complicated, which, when you looked at it in the right way, did not become still more complicated. - Poul Anderson === This list is open to everyone. Occasionally, less thoughtful people send inappropriate messages. Please DO NOT COMPLAIN TO THE POSTMASTER about these messages because the postmaster has no way of controlling them, and excessive complaints will result in termination of the list. For information about this list, including information about the problem of inappropriate messages and information about how to unsubscribe, please see the web page at http://jse.stat.ncsu.edu/ ===
No Subject
unsubscribe SAS-L === This list is open to everyone. Occasionally, less thoughtful people send inappropriate messages. Please DO NOT COMPLAIN TO THE POSTMASTER about these messages because the postmaster has no way of controlling them, and excessive complaints will result in termination of the list. For information about this list, including information about the problem of inappropriate messages and information about how to unsubscribe, please see the web page at http://jse.stat.ncsu.edu/ ===
Re: Elliptical plots with 84% bivariate conficence regions
On Wed, 15 Mar 2000, Ralf Sigmund (privat) wrote: > has anybody an idea, whether the following sentence should be correct? > > 'non-overlapping 84% bivariate confidence regions approximate > statistically significant differences with p < 0.05. Two-sided test.' I don't recall having seen a reply to this question. About the bivariate case I am not certain. For the univariate case, with two independent groups of about the same size, it is roughly correct, if the confidence regions are the usual symmetrical intervals. Analysis: For convenience assume equal variances in the two groups. Then the means differ (p < 0.05) if the distance between them is > 2 standard errors of the difference (i.e., if t > 2) approximately. For equal sample sizes, the standard error of the difference = sqrt(2) times the std. error of the mean; difference between means then > 2.8 std. errors of the mean. Half that difference = 1.4 std. errors. 84% confidence interval is (mean +/- 1.4 std. errors); so non-overlapping confidence intervals would show that the means were at least 1.4 + 1.4 = 2.8 std. errors apart, hence significantly different (p < 0.05). It is plausible that a similar relationship holds in the bivariate case. 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 === This list is open to everyone. Occasionally, less thoughtful people send inappropriate messages. Please DO NOT COMPLAIN TO THE POSTMASTER about these messages because the postmaster has no way of controlling them, and excessive complaints will result in termination of the list. For information about this list, including information about the problem of inappropriate messages and information about how to unsubscribe, please see the web page at http://jse.stat.ncsu.edu/ ===
