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From: "email@thorstenschaefer.de" <email@thorstenschaefer.de>
To: Commons Users List <user@commons.apache.org>
Date: Thu, 12 Sep 2013 02:28:24 +0200
Subject: Re: [MATH] Estimate of the population mean given a sample
Thread-Topic: [MATH] Estimate of the population mean given a sample
Thread-Index: Ac6vTv7VZX5fuEYNT7SLaYJHVRdUYw==
Message-ID: <CE56907E.4247%email@thorstenschaefer.de>
In-Reply-To: <5230C7A0.9050501@gmail.com>
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Thanks Thomas, that worked :). I'm not yet too familiar with the
statistics background, but I guess I'll spend some more time with it and
if I really got it, I'll write a patch for a binomial test.

Cheers,

Thorsten

Am 9/11/13 4:42 PM schrieb "Thomas Neidhart" unter
<thomas.neidhart@gmail.com>:

>On 09/11/2013 08:37 PM, email@thorstenschaefer.de wrote:
>> We have a sample which comes from a binomial process with unknown
>>probability. Is it possible to get the likelihood of the population is
>>larger than a user-specified value (with e.g. 95% certainty) in
>>commons-math?
>> For example, given we have two samples:
>> S1: we have 4 out of 5 successes
>> S2: we have 80 out of 100 successes
>>=20
>> I would like to know the probability that the real mean is larger than
>>60% given one of the samples above. Is there an easy way to calculate it?
>
>Hi Thorsten,
>
>there is not yet a binomial test available (would be a nice addition),
>but you can calculate the requested values with the binomial distribution:
>
>// create a binomial distribution with null hypothesis of p=3D0.6
>BinomialDistribution s1 =3D new BinomialDistribution(5, 0.6);
>System.out.println(1 - s1.cumulativeProbability(4-1));
>
>// =3D 0.3369 > 0.05 significance level
>// thus null hypothesis can not be rejected
>
>BinomialDistribution s2 =3D new BinomialDistribution(100, 0.6);
>System.out.println(1 - s2.cumulativeProbability(80-1));
>
>// =3D 1.64e-5 < 0.05 significance level
>// thus null hypothesis can be rejected
>// the observed probability must be larger
>
>Note: the - 1 is used to get the same results as with R binom.test
>see also
>http://stats.stackexchange.com/questions/44125/is-there-an-error-in-the-on
>e-sided-binomial-test-in-r
>
>
>Best regards,
>
>Thomas
>
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