R version 2.7.0 (2008-04-22)
Copyright (C) 2008 The R Foundation for Statistical Computing
ISBN 3-900051-07-0

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> par2 = 'actual computing'
> par1 = 'reported computing'
> #'GNU S' R Code compiled by R2WASP v. 1.0.44 ()
> #Author: Prof. Dr. P. Wessa
> #To cite this work: Wessa P., (2008), ICVL 2008 (v1.0.0) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_icvl2008.wasp/
> #Source of accompanying publication: Office for Research, Development, and Education
> #Technical description: 
> x <- as.data.frame(read.table(file='http://www.wessa.net/download/statdb.csv',sep=',',header=T))
> library(GenKern)
Loading required package: KernSmooth
KernSmooth 2.22 installed
Copyright M. P. Wand 1997

Loading GenKern version 1.1
Copyright Lucy and Aykroyd 2000
last update October 2004
requires KernSmooth


Package GenKern installed

> 
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
> 
> doplot1 <- function(myxcol,myycol,myxlab='',myylab='') {
+ p0 <- x[x$Pop==0,]
+ p1 <- x[x$Pop==1,]
+ dum <- cbind(p0[,myxcol],rank(p0[,myxcol]),p0[,'Gender'])
+ xf0 <- dum[dum[,3]==0,2]
+ xm0 <- dum[dum[,3]==1,2]
+ dum <- cbind(p0[,myycol],rank(p0[,myycol]),p0[,'Gender'])
+ yf0 <- dum[dum[,3]==0,2]
+ ym0 <- dum[dum[,3]==1,2]
+ dum <- cbind(p1[,myxcol],rank(p1[,myxcol]),p1[,'Gender'])
+ xf1 <- dum[dum[,3]==0,2]
+ xm1 <- dum[dum[,3]==1,2]
+ dum <- cbind(p1[,myycol],rank(p1[,myycol]),p1[,'Gender'])
+ yf1 <- dum[dum[,3]==0,2]
+ ym1 <- dum[dum[,3]==1,2]
+ xf <- rank(x[x$Gender==0,myxcol])
+ yf <- rank(x[x$Gender==0,myycol])
+ xm <- rank(x[x$Gender==1,myxcol])
+ ym <- rank(x[x$Gender==1,myycol])
+ x0 <- rank(x[x$Pop==0,myxcol])
+ y0 <- rank(x[x$Pop==0,myycol])
+ x1 <- rank(x[x$Pop==1,myxcol])
+ y1 <- rank(x[x$Pop==1,myycol])
+ mycorr <- array(NA,dim=c(4,4))
+ rownames(mycorr) <- c('Female Bachelor Students','Male Bachelor Students','Female Switching Students','Male Switching Students')
+ colnames(mycorr) <- c('Pearson rho','Pearson p-value','Kendall tau','Kendall p-value')
+ postscript(file="/var/www/html/rcomp/tmp/1wqq01214841098.ps",horizontal=F,pagecentre=F,paper="special",width=10.416666666667,height=10.416666666667) 
+ par(mfrow=c(2,2))
+ r <- cor.test(xf0,yf0,method='pearson')
+ mycorr[1,1] <- r$estimate
+ mycorr[1,2] <- r$p.value
+ r <- cor.test(xf0,yf0,method='kendall')
+ mycorr[1,3] <- r$estimate
+ mycorr[1,4] <- r$p.value
+ op <- KernSur(xf0,yf0, xgridsize=150, ygridsize=150,na.rm=T)
+ image(op$xords, op$yords, op$zden, col=topo.colors(100), axes=TRUE, xlab=myxlab, ylab=myylab, main=rownames(mycorr)[1])
+ contour(op$xords, op$yords, op$zden, add=TRUE)
+ box()
+ abline(0,1)
+ lines(stats::lowess(cbind(xf0,yf0)),col='white')
+ r <- cor.test(xm0,ym0,method='pearson')
+ mycorr[2,1] <- r$estimate
+ mycorr[2,2] <- r$p.value
+ r <- cor.test(xm0,ym0,method='kendall')
+ mycorr[2,3] <- r$estimate
+ mycorr[2,4] <- r$p.value
+ op <- KernSur(xm0,ym0, xgridsize=150, ygridsize=150,na.rm=T)
+ image(op$xords, op$yords, op$zden, col=topo.colors(100), axes=TRUE, xlab=myxlab, ylab=myylab, main=rownames(mycorr)[2])
+ contour(op$xords, op$yords, op$zden, add=TRUE)
+ box()
+ abline(0,1)
+ lines(stats::lowess(cbind(xm0,ym0)),col='white')
+ r <- cor.test(xf1,yf1,method='pearson')
+ mycorr[3,1] <- r$estimate
+ mycorr[3,2] <- r$p.value
+ r <- cor.test(xf1,yf1,method='kendall')
+ mycorr[3,3] <- r$estimate
+ mycorr[3,4] <- r$p.value
+ op <- KernSur(xf1,yf1, xgridsize=150, ygridsize=150,na.rm=T)
+ image(op$xords, op$yords, op$zden, col=topo.colors(100), axes=TRUE, xlab=myxlab, ylab=myylab, main=rownames(mycorr)[3])
+ contour(op$xords, op$yords, op$zden, add=TRUE)
+ box()
+ abline(0,1)
+ lines(stats::lowess(cbind(xf1,yf1)),col='white')
+ r <- cor.test(xm1,ym1,method='pearson')
+ mycorr[4,1] <- r$estimate
+ mycorr[4,2] <- r$p.value
+ r <- cor.test(xm1,ym1,method='kendall')
+ mycorr[4,3] <- r$estimate
+ mycorr[4,4] <- r$p.value
+ op <- KernSur(xm1,ym1, xgridsize=150, ygridsize=150,na.rm=T)
+ image(op$xords, op$yords, op$zden, col=topo.colors(100), axes=TRUE, xlab=myxlab, ylab=myylab, main=rownames(mycorr)[4])
+ contour(op$xords, op$yords, op$zden, add=TRUE)
+ box()
+ abline(0,1)
+ lines(stats::lowess(cbind(xm1,ym1)),col='white')
+ dev.off()
+ mycorr
+ }
> if (par1 == 'actual feedback') {
+ myxcol='nnzfg'
+ myxlab = '# submitted messages'
+ }
> if (par1 == 'reported feedback') {
+ myxcol = 'Reflection'
+ myxlab = 'reported feedback submissions'
+ }
> if (par1 == 'reported computing') {
+ myxcol = 'Future'
+ myxlab = 'reported intention to use'
+ }
> if (par2 == 'actual computing') {
+ myycol = 'Bcount'
+ myylab = '# reproducible computations'
+ }
> if (par2 == 'actual feedback') {
+ myycol = 'nnzfg'
+ myylab = 'actual feedback submissions'
+ }
> if (par2 == 'reported computing') {
+ myycol = 'Future'
+ myylab = 'reported intention to use'
+ }
> mycorr <- doplot1(myxcol=myxcol,myycol=myycol,myxlab=myxlab,myylab=myylab)
> a<-table.start()
> a<-table.row.start(a)
> dum <- 'Correlations between'
> dum <- paste(dum,myxlab,sep=' ')
> dum <- paste(dum,myylab,sep=' and ')
> a<-table.element(a,dum,5,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'',header=TRUE)
> a<-table.element(a,'Pearson rho',header=TRUE)
> a<-table.element(a,'Pearson p-value',header=TRUE)
> a<-table.element(a,'Kendall tau',header=TRUE)
> a<-table.element(a,'Kendall p-value',header=TRUE)
> a<-table.row.end(a)
> for (myrow in 1:4) {
+ a<-table.row.start(a)
+ a<-table.element(a,rownames(mycorr)[myrow],header=TRUE)
+ a<-table.element(a,round(mycorr[myrow,1],4))
+ a<-table.element(a,round(mycorr[myrow,2],4))
+ a<-table.element(a,round(mycorr[myrow,3],4))
+ a<-table.element(a,round(mycorr[myrow,4],4))
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/2wuj81214841098.tab") 
> 
> system("convert tmp/1wqq01214841098.ps tmp/1wqq01214841098.png")
> 
> 
> proc.time()
   user  system elapsed 
  7.971   4.884   9.235