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Data X:
125 121.7 134.3 124.3 119.1 137.8 120.5 122.7 127.2 133.2 136.3 134.9 120.9 109.4 129.6 124.7 114.6 137.4 117.9 117.4 122 124.8 123.3 132.8 115.1 104.2 125.5 116.8 116.8 125.5 110.9 114.9 136.4 125.8 126.5 134 116.1 115 130.3 106.5 111.6 125 108.3 105 127.4 116.6 128.6 127.5 108.4 110.8 114.2 101.8 109.8 115.9 106.9 114.6 105.4 108.1 118.4 112.7 98.4 99.6 103.9 101.5 100.8 104.5 98.2 99.9 97.5 105.7 117.7 107.4 98.4 92 107.7 100.2 96.7 106.8 98 98.6
Data Y:
115.9 112.9 126.3 116.8 112 129.7 113.6 115.7 119.5 125.8 129.6 128 112.8 101.6 123.9 118.8 109.1 130.6 112.4 111 116.2 119.8 117.2 127.3 107.7 97.5 120.1 110.6 111.3 119.8 105.5 108.7 128.7 119.5 121.1 128.4 108.8 107.5 125.6 102.9 107.5 120.4 104.3 100.6 121.9 112.7 124.9 123.9 102.2 104.9 109.8 98.9 107.3 112.6 104 110.6 100.8 103.8 117 108.4 95.5 96.9 103.9 101.1 100.6 104.3 98 99.5 97.4 105.6 117.5 107.4 97.8 91.5 107.7 100.1 96.6 106.8 98 98.6
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R Code
bitmap(file='test1.png') 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() lx = length(x) makebiased = (lx-1)/lx varx = var(x)*makebiased vary = var(y)*makebiased corxy <- cor.test(x,y,method='pearson') cxy <- as.matrix(corxy$estimate)[1,1] load(file='createtable') a<-table.start() a<-table.row.start(a) a<-table.element(a,'Pearson Product Moment Correlation - Ungrouped Data',3,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Statistic',1,TRUE) a<-table.element(a,'Variable X',1,TRUE) a<-table.element(a,'Variable Y',1,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,hyperlink('http://www.xycoon.com/arithmetic_mean.htm','Mean',''),header=TRUE) a<-table.element(a,mean(x)) a<-table.element(a,mean(y)) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,hyperlink('http://www.xycoon.com/biased.htm','Biased Variance',''),header=TRUE) a<-table.element(a,varx) a<-table.element(a,vary) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,hyperlink('http://www.xycoon.com/biased1.htm','Biased Standard Deviation',''),header=TRUE) a<-table.element(a,sqrt(varx)) a<-table.element(a,sqrt(vary)) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,hyperlink('http://www.xycoon.com/covariance.htm','Covariance',''),header=TRUE) a<-table.element(a,cov(x,y),2) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,hyperlink('http://www.xycoon.com/pearson_correlation.htm','Correlation',''),header=TRUE) a<-table.element(a,cxy,2) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,hyperlink('http://www.xycoon.com/coeff_of_determination.htm','Determination',''),header=TRUE) a<-table.element(a,cxy*cxy,2) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,hyperlink('http://www.xycoon.com/ttest_statistic.htm','T-Test',''),header=TRUE) a<-table.element(a,as.matrix(corxy$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='mytable.tab')
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