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Data X:
17 19 18 17 17 19 19 12 15 16 16 14 15 16 14 18 15 18 19 15 17 9 18 17 15 13 17 14 15 14 17 14 13 19 15 14 11 16 13 15 17 15 12 15 15 8 16 12 13 16 16 8 14 15 16 16 17 18 9 19 14 14 15 19 12 17 16 17 15 11 8 16 20 20 13 11 15 15 14 16 15 15 16 19 20 14 16 14 11 16 16 15 16 12 13 11 20 11 14 16 15 13 15 13 17 18 14 13 12 17 6 9 15 15 17 19 20 10 9 15 16 16 9 10 9 17 17 19 10 12 9 11 17 9 14 19 17 13 11 14 7 17 16 12 10 10 8 18 15 18 14 16 11 16 17 20 14 16 17 11 13 11 8 9 9 12 15 18 10 15 16 18 15 17 17 14 17 13 16 12 17 10 9 15 14 16 17 18 14 17 14 15 14 10 9 12 13 14 18 15 14 10 9 17 12 16 11 13 12 15 15 10 16 11 14 17 16 16 11 16 13 7 13 14 14 9 15 16 11 20 14 9 16 13 15 15 15 15 14 15 13 12 17 8 17 10 9 9 15 14 12 16 19 6 11 16 12 12 8 11 8 12 16 18 16 15 20 10 15 14 14 8 19 17 18 10 15 16 12 13 10 14 15 20 9 12 13 16 12 14 15 19 16 16 14 14 14 13 18 15 15 15 13 14 15 14 19 16 16 12 10 11 13 14 11 11 16 9 16 19 13 15 14 15 11 14 15 17 16 13 15 14 15 14 12 12 15 17 13 5 7 10 15 9 9 15 14 11 18 20 20 16 15 14 13 18 14 12 9 19 13 12 14 6 14 11 11 14 12 19 13 14 17 12 16 15 15 15 16 15 12 13 14 17 14 14 14 15 11 11 16 12 12 19 18 16 16 13 11 10 14 14 14 16 10 16 7 16 15 17 11 11 10 13 14 13 13 12 10 15 6 15 15 11 14 14 16 12 15 20 12 9 13 15 19 11 11 17 15 14 15 11 12 15 16 16
Data Y:
22 39 40 34 38 39 39 38 31 34 32 37 36 38 29 33 35 34 45 30 33 30 40 34 31 27 33 42 36 33 42 33 21 43 34 32 34 28 30 27 29 40 29 41 33 42 39 35 33 33 44 34 30 30 35 39 34 39 25 39 33 34 36 34 31 35 34 36 40 31 33 28 42 38 35 34 28 35 25 39 25 32 35 41 34 33 32 34 25 38 37 38 36 39 31 40 34 33 32 33 32 28 32 34 36 38 31 36 27 31 28 30 29 29 31 35 42 28 38 34 28 30 26 27 31 35 33 34 30 28 30 29 32 34 34 35 40 34 28 35 31 33 36 30 27 30 25 39 36 31 33 30 31 32 33 43 35 36 42 31 26 38 27 27 31 32 36 36 25 33 32 40 36 36 35 31 31 36 36 37 31 31 26 35 32 36 37 34 33 35 31 38 36 32 28 33 31 34 33 36 36 29 31 35 31 35 36 35 38 28 28 28 34 31 44 36 36 34 32 36 38 28 37 32 36 30 38 37 33 43 26 33 34 36 36 36 36 39 33 35 25 26 35 16 40 14 22 21 38 38 27 40 40 19 29 37 27 26 24 29 26 27 35 39 38 36 37 36 32 33 39 34 39 36 33 30 39 37 37 35 32 36 36 41 36 37 29 39 37 32 36 43 30 33 28 30 28 39 34 34 29 32 33 27 35 38 40 34 34 26 39 34 39 26 30 34 34 29 41 43 31 33 34 30 23 29 35 40 27 30 27 29 33 32 33 36 34 45 30 22 24 25 26 27 27 35 36 32 35 35 36 37 33 25 35 37 36 35 29 35 31 30 37 36 35 32 34 37 36 39 37 31 40 38 35 38 32 41 28 40 25 28 37 37 40 26 30 32 31 28 34 39 33 43 37 31 31 34 32 27 34 28 32 39 28 39 32 36 31 39 23 25 32 32 36 39 31 32 28 34 28 38 35 32 26 32 28 31 33 38 38 36 31 36 43 37 28 35 34 40 31 41 35 38 37 31
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R Code
library(psychometric) 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$estimate)[1,1] load(file='createtable') a<-table.start() a<-table.row.start(a) a<-table.element(a,'Pearson Product Moment Correlation - Ungrouped Data',3,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Statistic',1,TRUE) a<-table.element(a,'Variable X',1,TRUE) a<-table.element(a,'Variable Y',1,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Mean',header=TRUE) a<-table.element(a,mean(x)) a<-table.element(a,mean(y)) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Biased Variance',header=TRUE) a<-table.element(a,varx) a<-table.element(a,vary) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Biased Standard Deviation',header=TRUE) a<-table.element(a,sqrt(varx)) a<-table.element(a,sqrt(vary)) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Covariance',header=TRUE) a<-table.element(a,cov(x,y),2) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Correlation',header=TRUE) a<-table.element(a,cxy,2) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Determination',header=TRUE) a<-table.element(a,cxy*cxy,2) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'T-Test',header=TRUE) a<-table.element(a,as.matrix(corxy$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,'95% CI of Correlation',header=TRUE) a<-table.element(a,paste('[',CIr(r=cxy, n = lx, level = .95)[1],', ', CIr(r=cxy, n = lx, level = .95)[2],']',sep=''),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') qqPlot(x,main='QQplot of variable x') dev.off() bitmap(file='test3.png') qqPlot(y,main='QQplot of variable y') dev.off()
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