This is probably better for Cross Validated
[https://stats.stackexchange.com]. Surprisingly, I can't quickly find an
answered question on this topic. My "tl;dr" answer would be: "inflated"
relative to what? Having an unbalanced sample certainly decreases the
*power* of an analysis, but there'
you say you asked elsewhere, but so many hits come up when I just search for
"unbalanced sample size" your justification for not following the posting guide
does not seem honest.
I also recall that various discussions of statistical power address this in
basic statistics.
On August 24, 2024 1
Hi,
I have asked this question elsewhere however failed to get any
response, so hoping to get some insight from experts and statisticians
here.
Let say we are fitting a regression equation where one explanatory
variable is categorical with 2 categories. However in the sample, one
category has 95%
В Sat, 24 Aug 2024 10:24:36 +0200
пишет:
> Yes indeed my raster "s" (the shape file for the boxplot classes) has
> several layers.
If 's' contains more than one layer, then this already prevents you
from giving two names to stack(r, s).
> That's way I tried to select a layer by "
> s<-sf$Unterr
Dear Ivan
Dear community
Quite nice book recommendation.
Yes indeed my raster "s" (the shape file for the boxplot classes) has several
layers. That's way I tried to select a layer by " s<-sf$Unterregio".
> sf <- read_sf("C:/Users/._BiogeoRegion.shp")
> names(sf)
> names(sf)
[1] "RegionNumm
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