On Sun, Oct 14, 2018 at 09:28:47AM +0200, Dr. Oliver Walter wrote: Am 14.10.2018 um 08:46 schrieb John Darrington: > AGGREGATE OUTFILE * MODE ADDVARIABLES > /BREAK=g > /Mean = mean(V) > /sd = sd(v) > /n = n(v) > . > > compute ci_upper=mean + sd/sqrt(n). > compute ci_lower=mean - sd/sqrt(n). > > list. Sorry for interrupting, but this doesn't give a 95% (or 90%) CI, but only mean +/- one standard error which is a 68%-CI if X is normally distributed and sd equals the population variance or an approximate 68% CI if the sample size goes to infinity (is large). You have to include a t value into the equation for calculating a 95% (or 90%) CI. If your sample sizes are small and differ from each other you should use different t values for each CI and each group. If you sample size is large you could use one z value (1.96) for all groups, but this is not appropriate in this case (n1 = n2 = 15, sample sizes are too small for this standard normal approximation).
You are right. Which is why I suggested using one of the CDF functions. There is no T function, but there is a F function, which I think is the same if you set DF2 to 1. But you probably know better than me about those details. Perhaps IDF.F (0.05, N -1, 1) is what Werner wants (I haven't tried it)? J' -- 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