> On 18.05.2020, at 14:18, Dang Ngoc Chan, Christophe
> <christophe.d...@sidel.com> wrote:
>
> Hello,
>
>> De Heinz Nabielek
>> Envoyé : dimanche 17 mai 2020 23:50
>>
>> CONF=0.95; N=1432; n=1:
>> One-sided 95% upper confidence limit fraction = BETA.INV(CONF, n+1, N+1-n)
>> = 0.003306121
>>
>> How would I do that in Scilab?
>
> Would it be :
>
> [X,Y]=cdfbet("XY", n+1, N+1-n, CONF, 1-CONF)
> X =
>
> 0.0033061
Written with more digits
0.0033061215, and EXCEL finds
0.003306121493. Very good agreement. I am glad I had asked.
And the HELP provides real support with the statement
Description
Calculates any one parameter of the beta distribution given values for the
others (The beta density is proportional to t^(A-1) * (1-t)^(B-1).
Since my originating binomial distribution is obviously
t^n * (1-t)^(N-n),
the parameters for the Beta Function have to be
A=n+1
B=N+1-n
to obtain an upper conficende limit fraction = Beta.Inv(CONF, n+1, N+1-n) !!!
Textbooks write Beta.Inv(CONF, n+1, N-n) since the last 50 years and it is
wrong. And "R" is also using this wrong correlation in their binom.test
Great many thanks for all the help.
Heinz
______________
Dr Heinz Nabielek
Schüttelstrasse 77A/11
A-1020 Wien, Österreich
Tel +43 1 276 56 13
cell +43 677 616 349 22
heinznabie...@me.com
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