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Data X:
47.071 47.071 47.071 47.071 47.071 50.322 50.322 50.322 50.322 50.322 50.322 50.322 50.322 50.322 50.322 50.322 50.322 50.322 54.567 54.567 54.567 54.567 54.567 54.567 54.567 54.567 54.567 54.567 54.567 54.567 54.567 54.567 54.567 54.567 54.567 54.567 54.567 54.567 54.567 54.567 54.567 54.567 54.567 55.321 55.321 55.709 57.513 57.513 57.513 57.513 57.513 58.807 58.807 58.807 58.807 58.807 58.807 58.807 58.807 58.807 58.807 58.807 58.807 58.807 58.807 58.807 58.807 64.119 66.905 66.905 66.905 66.905 66.905 66.905 66.905 66.905 66.905 66.905 66.905 66.905 66.905 67.491 67.491 67.491 74.264 74.264 74.264 74.264 74.264 74.264 74.264 74.264 74.264 74.264 74.264 74.264 74.911 78.287 78.613 78.613 78.613 78.613 78.745 78.745 78.745 78.745 78.745 78.745 80.335 80.335 80.335 80.335 80.335 80.335 80.335 80.335 80.335 80.335 80.616 80.616 80.616 80.616 80.616 80.616 80.616 80.616 80.616 80.616 80.616 80.616 80.616 80.616 80.616 80.616 80.616 80.616 82.559 83.934 83.934 83.934 83.934 83.934 85.508 85.508 85.508 85.97 85.97 85.97 85.97 85.97 85.97 85.97 85.97 85.97 85.97 85.97 85.97 86.291 86.291 86.291 86.291 86.921 86.921 86.921 89.543 89.543 89.543 89.543 89.543 89.543 89.543 89.543 89.543 93.342 93.342 93.342 93.342 93.342 93.342 93.342 93.342 93.342 93.342 93.342 93.342 93.342 93.342 93.342 93.342 93.342 93.342 93.342 93.342 93.342 93.342 93.342 93.342 93.342 93.342 93.342 93.342 93.342 93.342 93.342 93.342 93.342 96.505 96.505 96.505 96.505 96.505 97.527 97.527 97.527 97.527 97.527 97.527 97.527 97.527 97.527 102.115 102.422 102.422 102.422 102.422 102.422 102.422 102.422 102.422 102.422 102.422 102.422 102.422 105.76 105.76 105.76 105.76 105.76 105.76 105.76 105.76 105.76 105.76 105.76 105.76 112.731 112.731 112.731 112.731 112.731 113.496 118.657 120.012 120.012 120.012 120.012 120.012 120.012 120.012 120.012 120.012 120.012 120.012 120.012 120.012 120.012 120.012 120.012 120.012 120.012 120.012 120.012 120.012 120.012 120.012 120.012 120.012 125.604 125.604 137.855 137.855 137.855 137.855 137.855 137.855 137.855 137.855 137.855 137.855 137.855 151.481 151.481 151.481 151.481 151.481 151.481 151.481 151.481 186.848
Data Y:
44 43 38 18 13 68 61 60 48 47 37 36 33 29 27 26 26 20 78 57 53 48 47 47 45 44 42 38 35 35 35 32 32 31 30 30 29 29 29 28 25 24 20 33 17 16 49 46 39 27 10 56 55 48 44 42 39 37 34 34 34 32 31 28 24 23 17 60 74 73 70 70 68 66 58 57 54 49 48 43 33 52 41 36 61 60 51 49 42 41 36 30 24 23 20 17 35 17 80 47 47 46 74 70 53 40 34 29 84 67 66 61 57 56 51 40 35 31 97 89 84 83 81 79 77 74 70 65 62 61 58 56 55 54 52 35 93 76 69 56 51 41 63 45 19 69 57 56 56 52 47 40 39 35 31 26 22 59 49 38 24 56 49 29 81 72 59 53 48 47 40 39 37 95 95 94 91 91 89 87 85 85 81 80 80 80 74 70 69 69 68 67 64 63 60 58 57 57 57 52 52 49 49 47 41 39 75 73 73 70 64 97 77 69 68 68 59 52 46 44 81 81 76 71 69 67 65 60 56 53 53 47 45 92 91 90 90 87 86 85 84 82 82 81 70 93 86 85 85 84 55 42 100 99 99 96 96 95 95 94 94 93 93 91 91 91 89 89 86 82 82 81 80 69 63 62 57 89 66 93 92 85 85 83 66 55 55 52 47 24 100 98 96 95 93 93 92 91 57
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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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