[OASIS Issue Tracker] Commented: (OFFICE-2311) ZTEST

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    [ http://tools.oasis-open.org/issues/browse/OFFICE-2311?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17482#action_17482 ] 

Andreas Guelzow  commented on OFFICE-2311:
------------------------------------------

please see my proposed solution send to the open-formula list and attached to OFFICE-2300.

> ZTEST
> -----
>
>                 Key: OFFICE-2311
>                 URL: http://tools.oasis-open.org/issues/browse/OFFICE-2311
>             Project: OASIS Open Document Format for Office Applications (OpenDocument) TC
>          Issue Type: Sub-task
>          Components: OpenFormula
>    Affects Versions: ODF 1.2
>            Reporter: Robert Weir 
>
> 5.) ZTEST
> > TODO: OOo Calc and Gnumeric produce the same results. Excel (2007 
> > beta) claims to calculate the one-tailed test.
> > All produce different results than expected! What OOo Calc and 
> > Gnumeric calculate is out of my scope. Excel tries to calculate the 
> > probability by integrating from minus infinity to z and substracts 
> > this from one. That would only be right, if the absolute value of z is 
> > taken, not the signed z! (I speak already of the one-tailed results 
> > for this case, so no confusion here.)
> > So, either I made a mistake/misinterpretation or all three apps don't 
> > get it right(TM)
> Well, I'll test it in R. There is NO standard z-test, BUT the t-test 
> will do it, too. [There is also the package 'TeachingDemos' wich does 
> define the z-test]
> > > z.test(x, mu=15, sd=sd(x))
> >
> >         One Sample z-test
> >
> > data:  x
> > z = 0.3111, n = 30.000, Std. Dev. = 8.803, Std. Dev. of the sample mean
> > = 1.607, p-value = 0.7557
> > alternative hypothesis: true mean is not equal to 15
> > 95 percent confidence interval:
> >  12.34980 18.65020
> > sample estimates:
> > mean of x
> >      15.5
> where x = 1..30
> This same example gives a value of 0.38 in Calc. I have NO idea what 
> 0.38 stands for. And I just noticed that it is impossible to compute a 
> t-test on a single array in Calc against the expected mean - or did I 
> miss something?
> [The t-test in R gives virtually identical results, because a sample 
> size of 30 is large enough to approximate the z-distribution.]

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