Dear community,

 

That might be a stupid statistical question but I'm really not sure about
the answer:

 

Suppose I have two groups of numeric values x11-x19  and y11-y19. The
conventional way to check for difference in variance here is performing an
F-test with say

 

> g1 <- c(x11:x19)

> g2 <- c(y11:y19)

> var.test( g1, g2)

 

and looking at the resuting p.value. A second possibility is calculating
some adjusted values first like

 

> g1.adj <- abs(g1 - mean(g1))

> g2.adj <- abs(g2 - mean(g2))

 

And afterwards performing a T-test on those values. Should that give me the
same result? I tried to solve it mathematically and the statistic doesn't
seem to be the same. But then, why is the F-test calculated as it is AND is
it really better for a comparison than the second version?

 

Regards,

 

benjamin

 

--
Benjamin Otto
Universitaetsklinikum Eppendorf Hamburg
Institut fuer Klinische Chemie
Martinistrasse 52
20246 Hamburg

 


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