Art Kendall wrote:
>In SPSS output ignore the lines for equal variances, and use the lines for
>unequal variances.
Last year on this group, there was an interesting dataset posted, in which the
equal and unequal variance t tests give very different results:
Temperatures from Portion 1 of a st
In article ,
Matthias <[EMAIL PROTECTED]> wrote:
>Hello,
>would be nice if someone can give me some advice with regard to the
>following problem:
>I would like to compare the means of two independent numerical sets of data
>whether they are significantly different f
On Thu, 14 Feb 2002 23:48:02 +0100, "Matthias" <[EMAIL PROTECTED]>
wrote:
> Hello,
>
> would be nice if someone can give me some advice with regard to the
> following problem:
>
> I would like to compare the means of two independent numerical sets of data
> whether they are significantly differ
In SPSS output ignore the lines for equal variances, and use the lines for
unequal variances.
Matthias wrote:
> Hello,
>
> would be nice if someone can give me some advice with regard to the
> following problem:
>
> I would like to compare the means of two independent numerical sets of data
> w
Excuse the bad grammar or typo noted below... It's been a "long
morning" already, and it's still not 9 am...
:)
Bill
On Fri, 15 Feb 2002, William B. Ware wrote:
> What are your samples sizes? If there are equal or nearly so, the t-test
*they*
> is robust wit
What are your samples sizes? If there are equal or nearly so, the t-test
is robust with regard to unequal variances.
On the other hand, you could just read the part of the output that reports
results for "equal variances not assumed." You might also consider using
a nonparametric procedure such
"Matthias" <[EMAIL PROTECTED]> wrote in message
news:...
> Hello,
>
> would be nice if someone can give me some advice with regard to the
> following problem:
>
> I would like to compare the means of two independent numerical sets of data
> whether they are signifi
it's called the behrens-fisher problem ... there is nothing that says that
population variances HAVE to be equal
essentially what you do is to be a bit more conservative in your degrees of
freedom ... most software packages do this as the default ... or at least
give you the choice between mak
Hello,
would be nice if someone can give me some advice with regard to the
following problem:
I would like to compare the means of two independent numerical sets of data
whether they are significantly different from each other or not. One of the
two underlying assumption to calculate the T-Test