[R] Odp: Three sigma rule

[Bert Gunter]

Folks:

On Tue, May 31, 2011 at 8:48 AM, Petr PIKAL <petr.pikal at precheza.cz> wrote:
> Hi
>
> r-help-bounces at r-project.org napsal dne 28.05.2011 20:12:33:
>
>> "Salil Sharma" <salil31 at gmail.com>
>> Odeslal: r-help-bounces at r-project.org
>> Dear Sir,
>>
>>
>>
>> I have data, coming from tests, consisting of 300 values. Is there a way
> in
>> R with which I can confirm this data to 68-95-99.8 rule or three-sigma
> rule?
>>
>> I need to look around percentile ranks and prediction intervals for this
>> data. I, however, used SixSigma package and used ss.ci() function, which
>> produced 95% confidence intervals. I still am not certain about
> percentile
>> ranks conforming to 68-95-99.7 rule for this data.
>>
>
> Not sure what you exactly want but you could look at function quantile.

-- Nor am I, but ...
>
> Or you could compute confidence interval for mean by e.g.
>

I'm pretty sure that this is NOT what he wants.

-- Bert


>> mean.int
> function (x, p = 0.95)
> {
>    x.na <- na.omit(x)
>    mu <- mean(x.na)
>    odch <- sd(x.na)
>    l <- length(x.na)
>    alfa <- (1 - p)/2
>    mu.d <- mu - qt(1 - alfa, l - 1) * odch/sqrt(l)
>    mu.h <- mu + qt(1 - alfa, l - 1) * odch/sqrt(l)
>    return(data.frame(mu.d, mu, mu.h))
> }
>
> Regards
> Petr
>
>
>>
>>
>> Thanks and regards,
>> Salil Sharma
>>
>>
>>    [[alternative HTML version deleted]]
>>
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>
> ______________________________________________
> R-help at r-project.org mailing list
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> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>



-- 
"Men by nature long to get on to the ultimate truths, and will often
be impatient with elementary studies or fight shy of them. If it were
possible to reach the ultimate truths without the elementary studies
usually prefixed to them, these would not be preparatory studies but
superfluous diversions."

-- Maimonides (1135-1204)

Bert Gunter
Genentech Nonclinical Biostatistics