I just responded to your statements about the relations between
CIs and hypothesis test that a CI is not always associated
with a hypothesis. The equations I mentioned were only examples
for a confidence interval and its equivalent hypothesis test.
BTW: It's not safe to always use z instead of t. If your sample
size is small and you don't know the population variance, it's
better to use t instead of z.
Am 12.10.2018 um 16:56 schrieb Mark
Hancock:
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
< address@hidden>
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 < address@hidden>
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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