Posts Tagged ‘ test ’

Want to say one thing and the exact oppositive with strong confidence ?

March 15, 2011
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Want to say one thing and the exact oppositive with strong confidence ?

No need to do politics. Just take a statistical course. And I do not talk about misinterpretation of statistics, but I talk about the mathematical foundations of statistical tests. Consider the following parametric test, with a one-dimensional para...

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The distribution of rho…

March 21, 2010
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The distribution of rho…

There was a post here about obtaining non-standard p-values for testing the correlation coefficient. The R-library SuppDists deals with this problem efficiently. library(SuppDists) plot(function(x)dPearson(x,N=23,rho=0.7),-1,1,ylim=c(0,10),ylab="density") plot(function(x)dPearson(x,N=23,rho=0),-1,1,add=TRUE,col="steelblue") plot(function(x)dPearson(x,N=23,rho=-.2),-1,1,add=TRUE,col="green") plot(function(x)dPearson(x,N=23,rho=.9),-1,1,add=TRUE,col="red");grid() legend("topleft", col=c("black","steelblue","red","green"),lty=1, legend=c("rho=0.7","rho=0","rho=-.2","rho=.9"))</pre> This is how it looks like, Now, let’s construct a table of critical values for some arbitrary or not significance levels. q=c(.025,.05,.075,.1,.15,.2) xtabs(qPearson(p=q, N=23, rho

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Post hoc analysis for Friedman’s Test (R code)

February 22, 2010
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Post hoc analysis for Friedman’s Test  (R code)

My goal in this post is to give an overview of Friedman’s Test and then offer R code to perform post hoc analysis on Friedman’s Test results. (The R function can be downloaded from here) Preface: What is Friedman’s Test Friedman test is a non-parametric randomized block analysis of variance. Which is to say it is a non-parametric version of...

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Show me the mean(ing)…

November 5, 2009
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Show me the mean(ing)…

Well testing a bunch of samples for the largest population mean isn’t that common yet a simple test is at hand. Under the obvious title “The rank sum maximum test for the largest K population means” the test relies on the calculation of the sum of ranks under the combined sample of size , where

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