On Apr 18, 2013, at 05:35 , Thomas Lumley wrote:
> I just looked more carefully at your code.
>
> You are computing the unequal-variance (Welch) version of the t-test, so
> that's why there isn't a problem. Compare it with the equal-variance
> t-test, using the pooled variance estimate, which d
I just looked more carefully at your code.
You are computing the unequal-variance (Welch) version of the t-test, so
that's why there isn't a problem. Compare it with the equal-variance
t-test, using the pooled variance estimate, which does have a problem, as
below
-thomas
tstat4 <- function
OK,although the variance ratio was already 2.25 to 1, tried sigma1=10,
sigma2=25, which makes the ratios of the variances 6.25 to 1.
Still no change. See:
http://msemac.redwoods.edu/~darnold/math15/R/chapter11/DistributionForTwoIndependentSamplesPartII.html
D.
--
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Dear David,
On Wed, Apr 17, 2013 at 6:24 PM, David Arnold wrote:
> Hi,
[snip]
>
> D.
Before posting to StackExchange, check out the Wikipedia entry for
"Behrens-Fisher problem".
Cheers,
Jay
--
G. Jay Kerns, Ph.D.
Youngstown State University
http://people.ysu.edu/~gkerns/
_
On 04/17/2013 06:24 PM, David Arnold wrote:
Hi,
Typical things you read when new to stats are cautions about using a
t-statistic when comparing independent samples. You are steered toward a
pooled test or welch's approximation of the degrees of freedom in order to
make the distribution a t-dist
Hi,
Typical things you read when new to stats are cautions about using a
t-statistic when comparing independent samples. You are steered toward a
pooled test or welch's approximation of the degrees of freedom in order to
make the distribution a t-distribution. However, most texts give no
informati
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