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Data X:
13.5 16.2 17.6 15.8 17.6 15.2 15.9 12.0 13.3 14.8 16.1 16.9 17.6 13.9 10.0 7.6 7.1 8.1 8.1 7.7 4.0 1.4 0.3 -1.0 -1.9 -1.5 -0.2 3.4 3.0 4.1 3.4 3.2 6.1 5.8 6.2 5.8 5.9 6.7 5.9 3.8 1.7 1.4 1.8 3.0 3.6 4.8 4.3 4.2 2.9 4.9 7.2 8.7 9.1 8.9 9.0 11.6 9.6 9.1 9.2 10.8 11.0 8.5 6.5 7.2 7.8 8.7 7.8 7.5 7.7 7.5 8.3 7.9 10.4 11.5 14.0 11.9 11.9 10.3 11.3 9.9 8.9 9.2 8.8 6.7 7.1 6.6 7.2 5.0 5.3 6.3
Data Y:
87.3 97.6 107.1 96.1 109.5 105.0 83.9 89.2 107.0 113.6 108.1 91.9 104.9 99.2 104.3 104.0 101.5 105.4 88.7 83.6 98.0 108.9 92.8 82.0 101.3 106.3 94.0 102.8 102.0 105.1 92.4 81.4 105.8 120.3 100.7 88.8 94.3 99.9 103.4 103.3 98.8 104.2 91.2 74.7 108.5 114.5 96.9 89.6 97.1 100.3 122.6 115.4 109.0 129.1 102.8 96.2 127.7 128.9 126.5 119.8 113.2 114.1 134.1 130.0 121.8 132.1 105.3 103.0 117.1 126.3 138.1 119.5 138.0 135.5 178.6 162.2 176.9 204.9 132.2 142.5 164.3 174.9 175.4 143.0 158.7 155.4 176.6 163.3 178.9 182.7
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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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