R help - Apr 2001 - Hypothesis test

Dear colleague:

Actually that is what is done.

When using the z-test between proportions in two different groups, or using 
chi-squared to test the null hypothesis of equal proportions of two or more 
groups, the null hypothesis is that

H0: p1=p2=p3.....=p

where this p is the pooled proportion, the proportion in the summed groups = 
n1+n2+n3+..../N1+N2+N3....

in the z-test between two proportions, p1 and p2 are put in the numerator 
(p1-p2) while the pooled p is used in the denominator as part of Standard 
error of the difference.  If you thisk in putting the numerator as p1-p(the 
pooled p) there will be a problem of dependence as p(the pooled p) will 
change as p1 changes.

Mostafa


>From: "syed gillani" <syed at saudionline.com.sa>
>To: <r-help at stat.math.ethz.ch>
>Subject: [R] Hypothesis test
>Date: Sat, 7 Apr 2001 06:11:42 +0300
>
>Hello,
>
>Is it reasonable to run a test of significance regarding a proportion in a
>group versus that in the whole population?
>What kind of problems can one face in analysis?
>
>Thanks.
>
>syed
>
>
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From:           	"Moustafa ElHousinie" <drhosini at hotmail.com>
To:             	r-help at stat.math.ethz.ch
Copies to:      	syed at saudionline.com.sa
Subject:        	Re: [R] Hypothesis test
Date sent:      	Sat, 07 Apr 2001 06:33:16 -0000
> Dear colleague:
> 
> Actually that is what is done.
> 
> When using the z-test between proportions in two different groups, or using
> chi-squared to test the null hypothesis of equal proportions of two or more
> groups, the null hypothesis is that
> 
> H0: p1=p2=p3.....=p
> 
	<<SNIP>>
> Mostafa
> 
Ahem.  I believe this is not the question originally
posed:
> 
> 
> >From: "syed gillani" <syed at saudionline.com.sa>
> >To: <r-help at stat.math.ethz.ch>
> >Subject: [R] Hypothesis test
> >Date: Sat, 7 Apr 2001 06:11:42 +0300
> >
> >Hello,
> >
> >Is it reasonable to run a test of significance regarding a proportion
in a
> >group versus that in the whole population?
> >What kind of problems can one face in analysis?

That would seem to be:  How do I test Ho: p = p0 for some fixed 
value of p0, given an observed proportion p-hat (based on a 
sample of size n)?

Answer:  Calculate a p-value directly from the binomial distribution 
B(n, p0) or, if min(n*p0, n*(1-p0)) is not too small, use the normal 
approximation based on

	z = (p-hat - p0) / sqrt(p0*(1-p0)/n)

To that z you may or may not want to add a continuity correction, 
depending on your position on that particular issue.

Both tests assume that n is small compared to the population size,  
are standard fare in intro textbooks, and easily calculated from R's 
command line.

---JRG



John R. Gleason

Syracuse University
430 Huntington Hall                      Voice:   315-443-3107
Syracuse, NY 13244-2340  USA             FAX:     315-443-4085

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