Dear R-users
Idea:
Analysing tree height frequency with hist(), normal distribution (ks.test &
shapiro.test) and skewness (package e1071 - thanks a lot for this useful
package)as an indication of possible self-thinning in an experimental tree
stand.
Problem:
Results from the ks.test and the shapiro.test are not comparable (see example
of both tests). Tree height is a nice continuous variable. Sample size is
around n= 250-350. Does anybode know about a problem in ks tests using a large
sample size and working with subsets (e.g file[,])? Comparing tests with
qqplots, I would appreciate shapiro, but I am wondering about the results from
ks (test ist not very sensitive, D=1, p=2.2e-16 many times?
Thanks
Sibylle
> shapiro.test(Biotree[Ac,]$Height2008)
Shapiro-Wilk normality test
data: Biotree[Ac, ]$Height2008
W = 0.9908, p-value = 0.05175
> ks.test(Biotree[Ac,]$Height2008, "pnorm")
One-sample Kolmogorov-Smirnov test
data: Biotree[Ac, ]$Height2008
D = 1, p-value < 2.2e-16
alternative hypothesis: two-sided
Warning message:
In ks.test(Biotree[Ac, ]$Height2008, "pnorm") :
cannot compute correct p-values with ties
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