On 29/04/2008 8:09 AM, mad_bassie wrote:
I'm using F-distributions :)
I allready found some things...I could plot the qqplot as you say and that
gives me clear results.
Allthough I still want a clear graphic and I 'll explain it as good as I
can...
I plotted 2 graphics
plot(density(rf(1,2,49
I'm using F-distributions :)
I allready found some things...I could plot the qqplot as you say and that
gives me clear results.
Allthough I still want a clear graphic and I 'll explain it as good as I
can...
I plotted 2 graphics
plot(density(rf(1,2,49)))
plot(density(disttest))
On 29/04/2008 4:13 AM, mad_bassie wrote:
It's not really homework :)
It's just an a little extra I want to explore.
I allready compared the empirical null distribution and the theoritical null
distribution by comparing their quantiles. The results are clear... But I
just wondered if there isn't a
It's not really homework :)
It's just an a little extra I want to explore.
I allready compared the empirical null distribution and the theoritical null
distribution by comparing their quantiles. The results are clear... But I
just wondered if there isn't any way to make a graph of it...so you don'
mad_bassie <[EMAIL PROTECTED]> wrote in
news:[EMAIL PROTECTED]:
>
> I simulated data for the ANOVA-test where the condition of equal
> variances was not accomplished.
> I have three groups:
> X<-rnorm(50,30,5)
> Y<-rnorm(50,30,10)
> Z<-rnorm(50,30,5)
> (this is just an examplethe variables
I simulated data for the ANOVA-test where the condition of equal variances
was not accomplished.
I have three groups:
X<-rnorm(50,30,5)
Y<-rnorm(50,30,10)
Z<-rnorm(50,30,5)
(this is just an examplethe variables might still change depending on
how clear the results are)
Now I want to construc
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