The null hypothesis is that the AVERAGE percentages (or counts) across
categories are not significantly different between groups.
Is there an easy way to test this using the data as they are
structured (basically need to obtain a 2x2 table of means by group)?
On Tue, Dec 22, 2009 at 12:54 PM, Maarten buis <[email protected]> wrote:
> --------------------------
> Maarten L. Buis
> Institut fuer Soziologie
> Universitaet Tuebingen
> Wilhelmstrasse 36
> 72074 Tuebingen
> Germany
>
> http://www.maartenbuis.nl
> --------------------------
>
>
> --- On Tue, 22/12/09, B Web <[email protected]> wrote:
>> I have some group data (2 groups),
>> but my question is about the counts
>> (or averages) between groups.
>>
>> tab group, sum( tot_asian)
>> tab group, sum( tot_white)
>> tab group, sum( tot_pacisland)
>> tab group, sum( tot_afam)
>>
>> I would like to get a chi-square test, but not sure how to
>> easily get these down to a 2x2 table where I can do a
>> chi-square test across group on counts on average. The
>> tot_ variables are continuous, but I think the chi-square
>> test is the right thing here.
>
> The key to determining the right test is specifying the
> null-hypothesis, i.e. determining what it is that you
> want to test. So, what is your null-hypothesis?
>
> -- Maarten
>
>
>
>
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