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Data X:
14.15 13.95 13.96 13.99 14.08 14.03 13.93 13.95 13.94 14.01 13.98 13.84 14.16 13.92 13.97 14 14 13.87 13.94 13.98 13.95 14.01 13.96 13.88 13.76 13.79 13.97 13.84 13.94 13.97 13.92 13.87 13.9 13.85 13.7 13.87 13.74 13.64 13.83 13.88 14.01 13.98 14.02 14.1 14.11 14.14 14.04 14.19 14.17 14.14 13.94 14.09 14.06 14.07 14.07 14.07 14.05 13.99 13.85 13.95 14.13 14.2 14.2 14.18 14.13 14.07 14.06 14.07 14.1 14.1 14 14.16 13.85 13.97 13.91 13.9 13.83 13.9 13.79 13.88 13.94 13.95 14.08 13.87 14.16 13.9 13.74 13.82 13.82 13.88 13.9 14.04 13.92 13.96 13.8 13.74 13.84 13.71 13.78 13.78 13.76 13.81 13.87 13.76 13.82 13.82 13.83 13.91 13.92 14 13.99 14.01 14.09 14.13 14.03 14.1 14.05 14.02 14.11 14.21 14.38 14.23 14.1 14.04 14.12 14 14.11 14.03 14.03 14.04 14.06 14.1 14.11 14.12 14.24 14.17 14.08 14.07 14.09 14.02 14.01 13.98 13.92 14.03 14.01 14.19 13.73 13.92 13.94 14.03 14.04 14.03 14.07 14.04 13.93 14.17 14.06 14.2 14.16 14.11 14.16 14.13 14.01 14.05 14.04 14.1 14.05 14.02 14.11 14.21 14.38 14.23 14.1 14.04 14.12 14 14.11 14.03 14.03 14.04 14.06 14.1 14.11 14.12 14.24 14.17 14.08 14.07 14.09 14.02 14.01 13.98 13.92 14.03 14.01 14.19 13.73 13.92 13.94 14.03 14.04 14.03 14.07 14.04 13.93 14.17 14.06 14.2 14.16 14.11 14.16 14.13 14.01 14.05 14.04 14.03 14.04 13.9 14.09 14.16 14.09 14.08 13.95 14.01 14 13.99 14 14.02 14.06 14.02 13.97 14.19 13.97 13.98 14.03 14.04 14.13 14.22 14.21 14.15 14.17 14.03 14.02 13.91 13.81 13.78 13.83 13.96 13.9 14.1 13.99 13.9 13.88 13.89 14.03 14.19 14.16 14.1 14.03 14.06 14.07 14.11 14.17 14.23 14.11 14.25 14.03 14.07 13.99 14.01 13.98 13.93 14.06 13.98 14 13.86 13.98 13.8 13.8 13.89 13.88 13.78 13.89 13.93 13.95 13.92 13.96 13.91 13.76 13.79 13.99 13.99 13.99 14.04 14.01 14.13 14.01 14.07 14.04 14.18 14.26 14.31 14.26 14.2 14.18 14.14 14.08 14 14.04 14.08 14 13.94 13.83 13.75 13.92 13.91 13.91 13.9 13.95 14.02 13.89 13.89 13.89 13.87 14.03 13.96 14.06 13.98 14.08 13.95 13.95 13.84 13.94 13.88 13.83 13.8 13.92 13.9 13.73 13.87 13.76 13.86 13.9 13.85 13.9 13.75 13.87 13.97 13.97 14.14 14.18 14.17 14.2 14.17 14.15 14.1 14.04 14.01 14.15 14.03 14.04 14.05 14.12 14.09 13.98 13.94 14.04 13.86 14.03 13.99 14.08 14.01 14.04 13.9 14.09 14.04 13.97 14.08 13.99 14.11 14.16 14.18 14.18 14.38 14.18 14.22 14.13 14.2 14.25 14.14 14.15 14.13 14.1 14.09 14.23 14.11 14.4 14.3 14.37 14.24 14.14 14.17 14.19 14.24 14.11 14.07 14.15 14.28 14.03 14.06 13.94 14.05 14.12 14 14.12 13.99 14.04 14.05 14.06 14.33 14.45 14.39 14.39 14.23 14.25 14.15 14.12 14.26 14.28 14.12 14.29 14.12 14.22 14.09 14.17 14.01 14.22 13.98 14.12 14.09 14.11 14.05 13.96 13.81 14.09 13.87 14.1 14.08 14.09 14.08 13.95 14.08 14 14.05 13.98 14.04 14.24 14.28 14.23 14.16 14.11 14.07 14.07 14.08 14.02 14.08 14.01 14.08 14.23 14.39 14.13 14.21 14.21 14.26 14.36 14.18 14.34 14.26 14.22 14.46 14.51 14.32 14.44 14.35 14.3 14.32 14.24 14.27 14.26 14.26 14.05 14.22 14.11 14.25 14.26 14.16 14.07 14.06 14.22 14.24 14.25 14.23 14.14 14.29 14.33 14.34 14.65 14.43 14.32 14.31 14.34 14.28 14.23 14.4 14.45 14.39 14.35 14.43 14.29 14.41 14.31 14.42 14.43 14.3 14.36 14.22 14.16 14.2 14.38 14.37 14.34 14.19 14.22 14.15 14 14.01 13.94 14 13.93 14.13 14.28 14.26 14.3 14.18 14.18 14.1 14.09 14.03 14.02 14.16 14 14.14 14.28 13.94 14.25 14.26 14.22 14.29 14.2 14.19 14.25 14.38 14.37 14.29 14.44 14.7 14.44 14.34 14.11 14.33 14.46 14.37 14.24 14.42 14.37 14.26 14.23 14.43 14.25 14.2 14.21 14.18 14.3 14.32 14.16 14.15 14.28 14.31 14.27 14.31 14.46 14.33 14.31 14.43 14.28 14.36 14.45 14.5 14.55 14.53 14.55 14.83 14.56 14.58 14.59 14.59 14.67 14.6 14.43 14.42 14.4 14.51 14.45 14.64 14.27 14.28 14.23 14.28 14.26 14.27 14.25 14.3 14.32 14.37 14.21 14.49 14.46 14.5 14.3 14.31 14.28 14.37 14.29 14.21 14.21 14.19 14.38 14.4 14.56 14.42 14.47 14.45 14.46 14.45 14.45 14.43 14.68 14.47 14.74 14.75 14.81 14.54 14.51 14.43 14.53 14.43 14.46 14.48 14.51 14.33
Data Y:
0 0 0 0 1 0 1 2 3 1 1 0 0 0 0 0 0 0 0 3 7 2 1 0 0 0 0 0 0 0 0 4 3 6 0 0 0 0 0 0 1 0 0 3 4 2 0 0 0 1 0 0 0 0 0 2 2 2 0 0 0 0 0 0 1 0 0 3 3 4 1 1 0 0 0 0 0 1 1 2 4 1 1 1 0 0 0 0 0 0 1 4 5 2 0 0 0 0 0 0 0 1 1 1 3 1 0 0 0 0 0 0 0 2 0 1 3 1 0 0 0 0 0 0 0 1 0 4 4 1 0 0 0 0 0 0 1 2 1 1 3 2 0 0 0 0 0 0 0 1 2 2 2 0 0 0 0 0 0 0 0 0 1 0 6 2 3 1 0 0 0 0 0 0 0 1 0 4 4 1 0 0 0 0 0 0 1 2 1 1 3 2 0 0 0 0 0 0 0 1 2 2 2 0 0 0 0 0 0 0 0 0 1 0 6 2 2 0 0 0 0 0 0 0 0 2 2 1 0 0 0 0 0 0 0 0 1 1 5 2 0 0 0 0 0 0 0 1 1 1 0 0 0 0 0 0 0 0 1 5 6 5 1 0 0 0 0 0 1 0 2 2 3 2 0 0 0 0 0 0 0 0 1 4 6 1 1 0 0 0 0 0 1 1 0 2 2 0 1 0 0 0 0 0 0 0 2 2 2 2 0 0 0 0 0 0 0 1 1 4 4 1 0 0 0 0 0 0 0 1 1 2 3 1 0 1 0 0 0 0 1 0 1 6 2 1 0 0 0 0 0 0 0 0 0 1 3 2 0 0 1 0 0 0 0 0 1 4 3 3 0 0 0 0 0 0 0 1 2 3 2 1 0 0 0 0 0 0 0 0 1 2 5 1 2 0 0 0 0 0 1 1 0 3 4 1 2 0 0 0 0 0 0 2 0 1 3 0 0 0 0 0 0 0 0 0 0 2 2 0 0 0 0 0 0 0 0 0 0 4 6 1 1 1 0 0 0 0 0 0 2 3 3 2 1 0 0 0 0 0 0 2 0 1 2 0 1 0 0 0 0 0 0 0 0 3 3 1 0 0 0 0 0 0 0 0 0 4 6 1 1 0 0 0 0 0 0 1 3 3 2 1 1 0 0 0 0 0 0 0 3 5 2 4 0 0 0 0 0 0 0 1 0 1 3 3 0 0 0 0 0 1 0 0 0 1 4 1 0 0 0 0 0 0 0 1 0 4 3 0 0 0 0 0 0 0 0 1 0 2 2 0 2 0 0 0 0 0 0 1 5 7 3 4 0 0 0 0 0 0 0 1 2 4 2 3 1 0 0 0 0 0 0 1 3 0 1 2 0 0 0 0 0 0 0 0 1 4 6 1 1 0 0 0 0 0 0 1 0 4 3 3 1 0 0 0 0 0 0 0 0 4 7 4 0 0 0 0 0 0 0 1 1 3 5 5 2 0 0 0 0 0 0 0 1 3 8 0 0 0
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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$estimate)[1,1] load(file='createtable') a<-table.start() a<-table.row.start(a) a<-table.element(a,'Pearson Product Moment Correlation - Ungrouped Data',3,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Statistic',1,TRUE) a<-table.element(a,'Variable X',1,TRUE) a<-table.element(a,'Variable Y',1,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,hyperlink('http://www.xycoon.com/arithmetic_mean.htm','Mean',''),header=TRUE) a<-table.element(a,mean(x)) a<-table.element(a,mean(y)) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,hyperlink('http://www.xycoon.com/biased.htm','Biased Variance',''),header=TRUE) a<-table.element(a,varx) a<-table.element(a,vary) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,hyperlink('http://www.xycoon.com/biased1.htm','Biased Standard Deviation',''),header=TRUE) a<-table.element(a,sqrt(varx)) a<-table.element(a,sqrt(vary)) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,hyperlink('http://www.xycoon.com/covariance.htm','Covariance',''),header=TRUE) a<-table.element(a,cov(x,y),2) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,hyperlink('http://www.xycoon.com/pearson_correlation.htm','Correlation',''),header=TRUE) a<-table.element(a,cxy,2) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,hyperlink('http://www.xycoon.com/coeff_of_determination.htm','Determination',''),header=TRUE) a<-table.element(a,cxy*cxy,2) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,hyperlink('http://www.xycoon.com/ttest_statistic.htm','T-Test',''),header=TRUE) a<-table.element(a,as.matrix(corxy$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,'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') 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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