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Data X:
68 39 32 62 33 52 62 77 76 41 48 63 30 78 19 31 66 35 42 45 21 25 44 69 54 74 80 42 61 41 46 39 34 51 42 31 39 20 49 53 31 39 54 49 34 46 55 42 50 13 37 25 30 28 45 35 28 41 6 45 73 17 40 64 37 25 65 100 28 35 56 29 43 59 50 59 27 61 28 51 35 29 48 25 44 64 32 20 28 34 31 26 58 23 21 21 33 16 20 37 35 33 27 41 40 35 28 32 22 44 27 17 12 45 37 37 108 10 68 72 143 9 55 17 37 27 37 58 66 21 19 78 35 48 27 43 30 25 69 72 23 13 61 43 51 67 36 44 45 34 36 72 39 43 25 56 80 40 73 34 72 42 61 23 74 16 66 9 41 57 48 51 53 29 29 55 54 43 51 20 79 39 61 55 30 55 22 37 2 38 27 56 25 39 33 43 57 43 23 44 54 28 36 39 16 23 40 24 78 57 37 27 61 27 69 34 44 34 39 51 34 31 13 12 51 24 19 30 81 42 22 85 27 25 22 19 14 45 45 28 51 41 31 74 19 51 73 24 61 23 14 54 51 62 36 59 24 26 54 39 16 36 31 31 42 39 25 31 38 31 17 22 55 62 51 30 49 16
Data Y:
12.9 12.2 12.8 7.4 6.7 12.6 14.8 13.3 11.1 8.2 11.4 6.4 10.6 12 6.3 11.3 11.9 9.3 9.6 10 6.4 13.8 10.8 13.8 11.7 10.9 16.1 13.4 9.9 11.5 8.3 11.7 9 9.7 10.8 10.3 10.4 12.7 9.3 11.8 5.9 11.4 13 10.8 12.3 11.3 11.8 7.9 12.7 12.3 11.6 6.7 10.9 12.1 13.3 10.1 5.7 14.3 8 13.3 9.3 12.5 7.6 15.9 9.2 9.1 11.1 13 14.5 12.2 12.3 11.4 8.8 14.6 12.6 13 12.6 13.2 9.9 7.7 10.5 13.4 10.9 4.3 10.3 11.8 11.2 11.4 8.6 13.2 12.6 5.6 9.9 8.8 7.7 9 7.3 11.4 13.6 7.9 10.7 10.3 8.3 9.6 14.2 8.5 13.5 4.9 6.4 9.6 11.6 11.1 4.35 12.7 18.1 17.85 16.6 12.6 17.1 19.1 16.1 13.35 18.4 14.7 10.6 12.6 16.2 13.6 18.9 14.1 14.5 16.15 14.75 14.8 12.45 12.65 17.35 8.6 18.4 16.1 11.6 17.75 15.25 17.65 16.35 17.65 13.6 14.35 14.75 18.25 9.9 16 18.25 16.85 14.6 13.85 18.95 15.6 14.85 11.75 18.45 15.9 17.1 16.1 19.9 10.95 18.45 15.1 15 11.35 15.95 18.1 14.6 15.4 15.4 17.6 13.35 19.1 15.35 7.6 13.4 13.9 19.1 15.25 12.9 16.1 17.35 13.15 12.15 12.6 10.35 15.4 9.6 18.2 13.6 14.85 14.75 14.1 14.9 16.25 19.25 13.6 13.6 15.65 12.75 14.6 9.85 12.65 19.2 16.6 11.2 15.25 11.9 13.2 16.35 12.4 15.85 18.15 11.15 15.65 17.75 7.65 12.35 15.6 19.3 15.2 17.1 15.6 18.4 19.05 18.55 19.1 13.1 12.85 9.5 4.5 11.85 13.6 11.7 12.4 13.35 11.4 14.9 19.9 11.2 14.6 17.6 14.05 16.1 13.35 11.85 11.95 14.75 15.15 13.2 16.85 7.85 7.7 12.6 7.85 10.95 12.35 9.95 14.9 16.65 13.4 13.95 15.7 16.85 10.95 15.35 12.2 15.1 17.75 15.2 14.6 16.65 8.1
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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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