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Data X:
26 20 19 19 20 25 25 22 26 22 17 22 19 24 26 21 13 26 20 22 14 21 7 23 17 25 25 19 20 23 22 22 21 15 20 22 18 20 28 22 18 23 20 25 26 15 17 23 21 13 18 19 22 16 24 18 20 24 14 22 24 18 21 23 17 22 24 21 22 16 21 23 22 24 24 16 16 21 26 15 25 18 23 20 17 25 24 17 19 20 15 27 22 23 16 19 25 19 19 26 21 20 24 22 20 18 18 24 24 22 23 22 20 18 25 18 16 20 19 15 19 19 16 17 28 23 25 20 17 23 16 23 11 18 24 23 21 16 24 23 18 20 9 24 25 20 21 25 22 21 21 22 27 24 24 21 18 16 22 20 18 20
Data Y:
21 16 19 18 16 23 17 12 19 16 19 20 13 20 27 17 8 25 26 13 19 15 5 16 14 24 24 9 19 19 25 19 18 15 12 21 12 15 28 25 19 20 24 26 25 12 12 15 17 14 16 11 20 11 22 20 19 17 21 23 18 17 27 25 19 22 24 20 19 11 22 22 16 20 24 16 16 22 24 16 27 11 21 20 20 27 20 12 8 21 18 24 16 18 20 20 19 17 16 26 15 22 17 23 21 19 14 17 12 24 18 20 16 20 22 12 16 17 22 12 14 23 15 17 28 20 23 13 18 23 19 23 12 16 23 13 22 18 23 20 10 17 18 15 23 17 17 22 20 20 19 18 22 20 22 18 16 16 16 16 17 18
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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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Computing time
1 seconds
R Server
Big Analytics Cloud Computing Center
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