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Data X:
0 7 7 7 15 67 77 73 73 73 56 56 46 25 25 25 25 24 25 25 63 63 63 63 79 79 79 79 81.1 81 88 88 94 94 94 86.45 86.45 82.13 82.13 91 91 92 92 91 91 91 91 91 91 91 91 91 91 77 70 70 70 75.25 77 71.75 70 70 70 70 70 70 70 70 70 70 69.13 50 50 50 50 50 38.5 28 28 28 31 31 39.6 39.6 39.6 39.6 39.6 39.6 39.6 39.6 39.1 38.6 35 35 35 35 35 35 35 35 35 39.5 39.5
Data Y:
0.92 0.96 0.93 0.84 0.89 1.22 4.05 5.69 7.38 6.18 4.26 4.28 4.3 4.05 4.22 4.47 4.33 4.29 4.83 3.98 2.63 3.26 3.89 4.53 5.18 6.2 7.23 7.11 7 9.44 16.06 27.27 51.4 53.19 46.41 44.64 47.25 44.16 43.53 56.73 71.8 74.24 75.84 71.92 81.29 87.07 86.01 85.46 99.8 101.34 99.68 106.56 112.61 116.82 130.84 148.82 152.97 186.88 192.81 187.14 207.31 230.8 263.22 279.09 298.06 355.56 399.56 463.3 517.11 599.27 617.77 600.56 666.44 734.04 769.16 854.29 909.24 991.11 1031.96 1054.99 1091.21 1154.34 1258.57 1351.79 1453.05 1579.23 1721.73 1827.45 2025.19 1991.08 1853.14 1782.31 1880.11 2153.61 2406.87 2567.98 2523.99 2104.99 2162.71 2303.47 2450.16 2773.98 3001.72
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R Code
x <- x[!is.na(y)] y <- y[!is.na(y)] y <- y[!is.na(x)] x <- x[!is.na(x)] 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', na.rm = T) 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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