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Data X:
117.7 124.6 144.4 109.6 117.9 122.2 89.3 78.4 119.1 110.3 118.3 105.5 97.7 101.5 119.6 108.1 117.8 125.5 89.1 92.3 104.5 122.8 96 94.5 93.4 101.1 114.2 104.8 113.3 118.2 83.6 73.9 99.5 97.7 103 106.3 92.2 101.8 122.8 111.8 106.3 121.5 81.9 85.4 110.9 117.3 106.3 105.6 101.2 105.9 126.3 111.9 108.9 127.2 94.2 85.7 116.2 107.2 110.5 112 104.4 112 132.8 110.8 128.7 136.8 94.8 88.8 123.2 125.3 122.7 125.8 116.3 118.6 142.1 127.9 132 152.4 110.8 99.1 134.9 133.2 131 133.9 119.9 137 148.9 145.1 142.4 159.6 120.7
Data Y:
96.1 101.7 109.9 98.1 102.4 110 71.6 74.8 110.3 109.2 104.9 100.6 85 95.9 108.9 96.1 100.1 105.8 64.4 66.9 110.4 96.1 102.5 97.6 83.6 86.5 96 91 87.2 84.5 59.1 61.6 98.8 97.9 92.8 84.2 74.6 79.8 86.7 79.8 87 91.3 58.7 62.8 87.8 90.4 80.6 73.5 71.5 70.6 78.3 76 77.4 80.9 63.5 58 88.2 81.2 84.9 76.4 71.5 76.1 82.9 78.1 82 84.7 55.7 59.5 83.2 87.6 76.2 76.4 68.2 70 76.3 70.9 72.5 80.1 57.4 62.7 82.6 88.9 80.5 72.1 69.4 69.3 77.4 79.3 78.6 76.2 64
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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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