Dear All,
Jari probably refer to that Mann-Whitney test suppose same shape of the
distributions (their positions may differ if H0 is false).
Best wishes
Zoltan
2014.03.24. 12:42 keltezéssel, Jari Oksanen írta:
Except that t-test does not assume that *observations* are normally
distributed, nor that variances are equal.
Avoid non-parametric tests: they assume too much of data properties.
For var.equal assumption in t.test, see ?t.test.
Cheers, Jari Oksanen
________________________________________
From: r-sig-ecology-boun...@r-project.org [r-sig-ecology-boun...@r-project.org]
on behalf of Richard Boyce [boy...@nku.edu]
Sent: 24 March 2014 13:23
To: r-sig-ecology@r-project.org
Subject: Re: [R-sig-eco] report out by t.test
Mike,
There is no way that your data meet the assumptions of a t-test (normal
distributions, equal variance). A nonparametric Mann-Whitney (aka Wilcoxon)
test is much better suited to your data.
Here's what I got when I ran it:
Q<-c(13,0,10,2,0,0,1,0,0,1,5)
WD<-c(0,0,1,0,0,0,0,0,0,0,1)
wilcox.test(Q,WD)
Wilcoxon rank sum test with continuity correction
data: Q and WD
W = 86.5, p-value = 0.05119
alternative hypothesis: true location shift is not equal to 0
Warning message:
In wilcox.test.default(Q, WD) : cannot compute exact p-value with ties
This has a p-value quite close to 0.05, giving some evidence that there's a
difference between your groups. Note that this you have different null and
alternative hypothesis: groups are the same vs. groups are different.
Rick Boyce
On Mar 24, 2014, at 7:00 AM,
r-sig-ecology-requ...@r-project.org<mailto:r-sig-ecology-requ...@r-project.org>
wrote:
Message: 1
Date: Sun, 23 Mar 2014 14:21:41 -0700
From: Michael Marsh <sw...@blarg.net<mailto:sw...@blarg.net>>
To: r-sig-ecology@r-project.org<mailto:r-sig-ecology@r-project.org>
Subject: [R-sig-eco] report out by t.test
Message-ID: <532f5065.7030...@blarg.net<mailto:532f5065.7030...@blarg.net>>
Content-Type: text/plain; charset=ISO-8859-1; format=flowed
I test differences between frequency of hits of exotic annual forbs in
plots on two sites, Q and WD.
Q<-c(13,0,10,2,0,0,1,0,0,1,5)
WD<-c(0,0,1,0,0,0,0,0,0,0,1)
t.test(Q,WD)
Welch Two Sample t-test
data: Q and WD
t = 1.9807, df = 10.158, p-value = 0.07533
alternative hypothesis: true difference in means is not equal to 0
95 percent confidence interval:
-0.3342006 5.7887460
sample estimates:
mean of x mean of y
2.9090909 0.1818182
The p-value is greater than 0.05, thus does not reach the 95% confidence
level, yet the difference in means is reported as not equal to 0.
Am I encountering a one-sided versus two sided comparison that I don't
understand, or is ther another explanation?
Mike Marsh
================================
Richard L. Boyce, Ph.D.
Director, Environmental Science Program
Professor
Department of Biological Sciences, SC 150
Northern Kentucky University
Nunn Drive
Highland Heights, KY 41099 USA
859-572-1407 (tel.)
859-572-5639 (fax)
boy...@nku.edu<mailto:boy...@nku.edu>
http://www.nku.edu/~boycer/
=================================
"One of the advantages of being disorderly is that one is constantly making exciting
discoveries." - A.A. Milne
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Botta-Dukát Zoltán
--------------------------------
Ökológiai és Botanikai Intézet
Magyar Tudományos Akadémia
Ökológiai Kutatóközpont
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Zoltán BOTTA-Dukát
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Institute of Ecology and Botany
Hungarian Academy of Sciences
Centre for Ecological Research
--------------------------------
H-2163 Vácrátót, Alkomány u. 2-4.
HUNGARY
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