R version 3.1.0 beta (2014-03-28 r65330) -- "Spring Dance"
Copyright (C) 2014 The R Foundation for Statistical Computing
Platform: i686-pc-linux-gnu (32-bit)

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> y <- c(6236,5678,5753,6459,6213,6679,6640,6486,6243,6492,7237,7349,7409,7776,7734,7706,8050,7247,6729,5809,5694,6269,6779,7610,7944,7617,8174,8829,10197,11917,13681,14587,14230,12502,12223,12589,12356,13256,14041,14333,14741,14401,15178,15217,15263,14870,15669,15787,15953,16709,17221,17991,18907,19888,20136,20848,21228,21003,21474,22371,23413,23033,22737,23699,24521,25610,26126,25774,26183,25436,26338,27968,28855,29577,30240,31190,32005,32302,31831,32507,33023,33947,34373,35221,36339,37456,38781,39786,39819,40132,40800,41826,42715,43430,43841,43282,41588,42227,42682,43308,43325,44324)
> x <- c(7,7,7,15,67,77,73,73,73,56,56,46,25,25,25,25,24,25,25,63,63,63,63,79,79,79,79,81.1,81,88,88,94,94,94,86.45,86.45,82.13,82.13,91,91,92,92,91,91,91,91,91,91,91,91,91,91,77,70,70,70,75.25,77,71.75,70,70,70,70,70,70,70,70,70,70,69.13,50,50,50,50,50,38.5,28,28,28,31,31,39.6,39.6,39.6,39.6,39.6,39.6,39.6,39.6,39.1,38.6,35,35,35,35,35,35,35,35,35,39.5,39.5)
> ylab = 'Real Per-capita GDP'
> xlab = 'Tax Rates'
> #'GNU S' R Code compiled by R2WASP v. 1.2.291 ()
> #Author: root
> #To cite this work: Wessa P., (2012), Pearson Correlation (v1.0.6) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_correlation.wasp/
> #Source of accompanying publication: Office for Research, Development, and Education
> #
> x <- x[!is.na(y)]
> y <- y[!is.na(y)]
> y <- y[!is.na(x)]
> x <- x[!is.na(x)]
> postscript(file="/var/wessaorg/rcomp/tmp/19jz91396747983.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=8.3333333333333) 
> histx <- hist(x, plot=FALSE)
> histy <- hist(y, plot=FALSE)
> maxcounts <- max(c(histx$counts, histx$counts))
> xrange <- c(min(x),max(x))
> yrange <- c(min(y),max(y))
> nf <- layout(matrix(c(2,0,1,3),2,2,byrow=TRUE), c(3,1), c(1,3), TRUE)
> par(mar=c(4,4,1,1))
> plot(x, y, xlim=xrange, ylim=yrange, xlab=xlab, ylab=ylab)
> par(mar=c(0,4,1,1))
> barplot(histx$counts, axes=FALSE, ylim=c(0, maxcounts), space=0)
> par(mar=c(4,0,1,1))
> barplot(histy$counts, axes=FALSE, xlim=c(0, maxcounts), space=0, horiz=TRUE)
> dev.off()
null device 
          1 
> lx = length(x)
> makebiased = (lx-1)/lx
> varx = var(x)*makebiased
> vary = var(y)*makebiased
> corxy <- cor.test(x,y,method='pearson', na.rm = T)
> cxy <- as.matrix(corxy$estimate)[1,1]
> 
> #Note: the /var/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/wessaorg/rcomp/createtable")
> 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Pearson Product Moment Correlation - Ungrouped Data',3,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Statistic',1,TRUE)
> a<-table.element(a,'Variable X',1,TRUE)
> a<-table.element(a,'Variable Y',1,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,hyperlink('http://www.xycoon.com/arithmetic_mean.htm','Mean',''),header=TRUE)
> a<-table.element(a,mean(x))
> a<-table.element(a,mean(y))
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,hyperlink('http://www.xycoon.com/biased.htm','Biased Variance',''),header=TRUE)
> a<-table.element(a,varx)
> a<-table.element(a,vary)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,hyperlink('http://www.xycoon.com/biased1.htm','Biased Standard Deviation',''),header=TRUE)
> a<-table.element(a,sqrt(varx))
> a<-table.element(a,sqrt(vary))
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,hyperlink('http://www.xycoon.com/covariance.htm','Covariance',''),header=TRUE)
> a<-table.element(a,cov(x,y),2)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,hyperlink('http://www.xycoon.com/pearson_correlation.htm','Correlation',''),header=TRUE)
> a<-table.element(a,cxy,2)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,hyperlink('http://www.xycoon.com/coeff_of_determination.htm','Determination',''),header=TRUE)
> a<-table.element(a,cxy*cxy,2)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,hyperlink('http://www.xycoon.com/ttest_statistic.htm','T-Test',''),header=TRUE)
> a<-table.element(a,as.matrix(corxy$statistic)[1,1],2)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'p-value (2 sided)',header=TRUE)
> a<-table.element(a,(p2 <- as.matrix(corxy$p.value)[1,1]),2)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'p-value (1 sided)',header=TRUE)
> a<-table.element(a,p2/2,2)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Degrees of Freedom',header=TRUE)
> a<-table.element(a,lx-2,2)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Number of Observations',header=TRUE)
> a<-table.element(a,lx,2)
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/2v0vu1396747983.tab") 
> 
> try(system("convert tmp/19jz91396747983.ps tmp/19jz91396747983.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.382   0.282   1.754