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Data X:
88 89.7 106.7 106 104.4 123.7 97.1 95.5 112.2 101.4 106.9 109.5 96.4 93.9 104.2 109.2 108.9 117.9 98.2 101.4 111.6 113.6 110.8 113.9 105.5 95.9 115.8 119.9 107.3 126.9 107.8 105.5 120.2 116 110.4 120.8 110.7 99.9 126.8 128.6 112.9 136.6 113.3 116.3 137.5 126.7 118.5 136.4 120.2 117.2 133.3 134.8 129.9 149.5 118.5 122.8 145.7 133.6 130.8 146.8 126 124.4 145.5 146.3 145 162 132.2 140.2 164.8 143.7 144.2 156.4 135.9 134.2 156.5 154.8 155.2 159.5 151.5 150.1 170.6 150.4 156.5 168.4 149.7 142.2 163 172.6 164.3 171.8 166.6 171.5 179.4 182.3 169.9 187.6 176.8
Data Y:
86.7 87.9 89.8 103 102.7 156.3 95 84.6 106.5 98.7 103.5 110.7 96.2 89.2 97.1 104.8 132.5 154.8 83.6 82.4 103.9 87 93.2 110.5 96.4 76.3 94 103.4 137 150.1 112.6 81.4 113.6 99.6 98.2 118.6 86.8 79.3 98.4 93.6 101 161.2 92.5 99.8 104.1 90.2 99.2 116.5 98.4 90.6 130.5 107.4 106 196.5 107.8 90.5 123.8 114.7 115.3 197 88.4 93.8 111.3 105.9 123.6 171 97 99.2 126.6 103.4 121.3 129.6 110.8 98.9 122.8 120.9 133.1 203.1 110.2 119.5 135.1 113.9 137.4 157.1 126.4 112.2 128.8 136.8 156.5 215.2 146.7 130.8 133.1 154.4 160.4 175.1 145.3
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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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