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Data X:
185.9 169.9 169.9 168.7 159.5 156 160.7 161.6 156.6 155.4 151.8 141.2 133.6 133.9 138.4 134.7 138.4 136 135 137.3 135.2 127.4 122.1 122 120.8 124.9 131 132.5 129.3 128.1 132.9 120.1 115.5 116.6 112.3 108.5 111.5 113.6 125 134.7 139.4 142.9 141.7 131.7 128.8 121.4 118.4 115 110.9 106 104.8 108.2 113.4 111.3 110.3 115.9 113.7 112.6 113.8 115.9 116.2 109.7 107 99 96.4 95.8 95.6 92 92.4 91.7 91.3 88.3 90.9 93.9 94.3 91.7 93.1 91.5 93.6 95.3 97.4 96.9 95.7 97.1 96.6 94.3 97 101.4 105.8 103.4 103.8 103 105.3
Data Y:
211.4 184.6 177.7 184.8 172.3 169.6 180.3 180.9 175.8 175 170.4 159.3 139.9 134.5 143 137.3 140.3 131.3 127.8 126.5 119.2 116 110.8 115.4 115.1 114.1 119.1 114 112.1 111.2 116 109.5 109.5 110.2 108.8 108.2 111.4 110.8 117.2 130.7 137.4 141.4 137.1 129.8 127.3 121.7 117.6 111.2 113 111.1 103.7 110.8 115.3 111.4 112.5 115.5 114.9 119.9 125.6 131.8 134.2 124.5 114.4 103.8 98.5 97 98.1 99 99.7 98.6 97.4 97.8 100.3 101.2 100.7 96.3 98.4 99.5 101.4 101.1 104.7 102.3 100.8 98.5 93.4 90.3 92.1 100.7 107.2 103.9 105.6 103.2 102.7
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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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1 seconds
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Big Analytics Cloud Computing Center
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