This is a good point, yes. I'm not the original requester, but I think they were really asking for a simple way to get a CI when reporting summary/descriptive statistics (without having a second mean to compare to). In SPSS you can do this: https://en.wikibooks.org/wiki/Using_SPSS_and_PASW/Confidence_Intervals
Maybe this is just my misunderstanding of AGGREGATE and PSPP syntax, but my point was just that there's nothing inherent about the question that should require a t-test - i.e., you can use z by default (and t-tests are really just extensions of z-scores anyway). z=1.96 works for 95% CIs, and Alan's suggestion does what I think the original requester was asking. Pointing to t-tests isn't a bad idea either, though, and maybe providing syntax for how to reduce it to a z-score would help the original requester (though I don't think they have another mean or value to compare it to). On Fri, Oct 12, 2018 at 9:33 AM Dr. Oliver Walter < o.wal...@psychometrie-online.de> wrote: > A confidence interval is mathematically equivalent to its corresponding > hypothesis test. The hypothesis test is significant if the corresponding > confidence interval does not contain the parameter value of the null > hypothesis. The confidence interval does not contain the parameter value of > the null hypothesis if the hypothesis test is significant. Hence, wether > you calculate the confidence interval or conduct the hypothesis test, > doesn't really matter. > > mean(X) +/- t * sd/sqrt(n): confidence interval for the expected value of > X, mu, X normally distributed with unknown population variance > > t = (mean - mü0)/ (sd/sqrt(n)) : test statistic for testing if mu equals > the value in the null hypothesis, mu0, X normally distributed with unknown > population variance > > If mü0 is not contained in the confidence interval, the hypothesis test is > significant. > > Dr. Oliver Walter > > Am 12.10.2018 um 15:01 schrieb Mark Hancock: > > I unfortunately don't know enough about PSPP syntax to suggest how to do > this, but a CI is *not* always associated with a hypothesis and can be > calculated from just a mean and SD (and a cumulative distribution function, > which is typically the normal one). Typically the formula is something > like: > > mean ± z(SD/sqrt(n)), where z is from the CDF. > > On Fri, Oct 12, 2018 at 6:29 AM John Darrington < > j...@darrington.wattle.id.au> wrote: > >> The confidence interval is a concept associated with a hypothesis. >> If it's the confidence interval on the test for a mean value, typically >> you >> would get that by using a T-Test. >> >> >> On Fri, Oct 12, 2018 at 10:40:22AM +0200, Werner LEMBERG wrote: >> >> Folks, >> >> >> I would like to get a 95% confidence interval so that I could use it >> in AGGREGATE, e.g., >> >> AGGREGATE OUTFILE * MODE ADDVARIABLES >> /BREAK=... >> /Mean = mean(V) >> /CI = ci(V, 0.95) >> >> What must I do to get the result of my hypothetical `ci' function? >> I'm a PSPP novice, so maybe there is a better solution than AGGREGATE >> ??? what I ultimately want is to emit the confidence interval of a >> variable to a CSV file using SAVE TRANSLATE. >> >> >> Werner >> _______________________________________________ >> Pspp-users mailing list >> Pspp-users@gnu.org >> https://lists.gnu.org/mailman/listinfo/pspp-users >> >> -- >> Avoid eavesdropping. Send strong encrypted email. >> PGP Public key ID: 1024D/2DE827B3 >> fingerprint = 8797 A26D 0854 2EAB 0285 A290 8A67 719C 2DE8 27B3 >> See http://sks-keyservers.net or any PGP keyserver for public key. >> >> >> _______________________________________________ >> Pspp-users mailing list >> Pspp-users@gnu.org >> https://lists.gnu.org/mailman/listinfo/pspp-users >> > > > _______________________________________________ > Pspp-users mailing > listPspp-users@gnu.orghttps://lists.gnu.org/mailman/listinfo/pspp-users > > > _______________________________________________ > Pspp-users mailing list > Pspp-users@gnu.org > https://lists.gnu.org/mailman/listinfo/pspp-users >
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