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Data X:
7.5 2.5 6.0 6.5 1.0 1.0 5.5 8.5 6.5 4.5 2.0 5.0 0.5 5.0 5.0 2.5 5.0 5.5 3.5 3.0 4.0 0.5 6.5 4.5 7.5 5.5 4.0 7.5 7.0 4.0 5.5 2.5 5.5 0.5 3.5 2.5 4.5 4.5 4.5 6.0 2.5 5.0 0.0 5.0 6.5 5.0 6.0 4.5 5.5 1.0 7.5 6.0 5.0 1.0 5.0 6.5 7.0 4.5 0.0 8.5 3.5 7.5 3.5 6.0 1.5 9.0 3.5 3.5 4.0 6.5 7.5 6.0 5.0 5.5 3.5 7.5 1.0 6.5 NA 6.5 6.5 7.0 3.5 1.5 4.0 7.5 4.5 0.0 3.5 5.5 5.0 4.5 2.5 7.5 7.0 0.0 4.5 3.0 1.5 3.5 2.5 5.5 8.0 1.0 5.0 4.5 3.0 3.0 8.0 2.5 7.0 0.0 1.0 3.5 5.5 5.5 0.5 7.5 9 9.5 8.5 7 8 10 7 8.5 9 9.5 4 6 8 5.5 9.5 7.5 7 7.5 8 7 7 6 10 2.5 9 8 6 8.5 6 9 8 8 9 5.5 5 7 5.5 9 2 8.5 9 8.5 9 7.5 10 9 7.5 6 10.5 8.5 8 10 10.5 6.5 9.5 8.5 7.5 5 8 10 7 7.5 7.5 9.5 6 10 7 3 6 7 10 7 3.5 8 10 5.5 6 6.5 6.5 8.5 4 9.5 8 8.5 5.5 7 9 8 10 8 6 8 5 9 4.5 8.5 7 9.5 8.5 7.5 7.5 5 7 8 5.5 8.5 7.5 9.5 7 8 8.5 3.5 6.5 6.5 10.5 8.5 8 10 10 9.5 9 10 7.5 4.5 4.5 0.5 6.5 4.5 5.5 5 6 4 8 10.5 8.5 6.5 8 8.5 5.5 7 5 3.5 5 9 8.5 5 9.5 3 1.5 6 0.5 6.5 7.5 4.5 8 9 7.5 8.5 7 9.5 6.5 9.5 6 8 9.5 8 8 9 5
Data Y:
21 26 22 22 18 23 12 20 22 21 19 22 15 20 19 18 15 20 21 21 15 16 23 21 18 25 9 30 20 23 16 16 19 25 25 18 23 21 10 14 22 26 23 23 24 24 18 23 15 19 16 25 23 17 19 21 18 27 21 13 8 29 28 23 21 19 19 20 18 19 17 19 25 19 22 23 26 14 28 16 24 20 12 24 22 12 22 20 10 23 17 22 24 18 21 20 20 22 19 20 26 23 24 21 21 19 8 17 20 11 8 15 18 18 19 19 23 22 21 25 30 17 27 23 23 18 18 23 19 15 20 16 24 25 25 19 19 16 19 19 23 21 22 19 20 20 3 23 14 23 20 15 13 16 7 24 17 24 24 19 25 20 28 23 27 18 28 21 19 23 27 22 28 25 21 22 28 20 29 25 25 20 20 16 20 20 23 18 25 18 19 25 25 25 24 19 26 10 17 13 17 30 25 4 16 21 23 22 17 20 20 22 16 23 16 0 18 25 23 12 18 24 11 18 14 23 24 29 18 15 29 16 19 22 16 23 23 19 4 20 24 20 4 24 22 16 3 15 24 17 20 27 23 26 23 17 20 22 19 24 19 23 15 27 26 22 22 18 15 22 27 10 20 17 23 19 13 27 23 16 25 2 26 20 23 22 24
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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, sub=main) 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') library(moments) library(nortest) jarque.x <- jarque.test(x) jarque.y <- jarque.test(y) if(lx>7) { ad.x <- ad.test(x) ad.y <- ad.test(y) } a<-table.start() a<-table.row.start(a) a<-table.element(a,'Normality Tests',1,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,paste('<pre>',RC.texteval('jarque.x'),'</pre>',sep='')) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,paste('<pre>',RC.texteval('jarque.y'),'</pre>',sep='')) a<-table.row.end(a) if(lx>7) { a<-table.row.start(a) a<-table.element(a,paste('<pre>',RC.texteval('ad.x'),'</pre>',sep='')) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,paste('<pre>',RC.texteval('ad.y'),'</pre>',sep='')) a<-table.row.end(a) } a<-table.end(a) table.save(a,file='mytable1.tab') library(car) bitmap(file='test2.png') qq.plot(x,main='QQplot of variable x') dev.off() bitmap(file='test3.png') qq.plot(y,main='QQplot of variable y') dev.off()
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