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
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