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Data X:
39.46 29.92 42.83 16.41 21.03 40.42 25.07 30.38 16.02 13.47 56.40 58.88 48.36 52.43 12.75 23.43 30.32 30.73 33.88 27.83 24.93 33.58 53.72 35.01 23.85 55.78 42.07 41.59 16.53 18.02 36.12 39.66 20.53 77.66 41.47 24.33 36.73 11.93 29.59 71.75 19.79 16.91 52.67 10.36 70.54 26.76 33.64 55.78 27.24 66.47 84.24 13.55 50.34 28.64 8.92 22.24 34.83 46.70 27.76 14.97 17.95 30.89 39.33 33.15 30.09 26.80 26.36 43.75 29.46 29.01 13.03 42.94 39.93 65.12 54.03 14.08 31.01 26.26 30.42 12.73 29.44 43.24 54.01 31.20 30.45 33.61 30.92 66.41 18.62 33.01 28.78 31.12 56.81 20.31 21.37 14.72 35.74 26.71 28.97 46.89 39.30 38.27 24.76 26.49 26.67 48.97 30.41 28.95 33.65 42.42 31.05 41.82 17.08 33.02 11.28 13.98 31.01 27.21 39.69 84.98 29.88 7.60 40.46 22.10 43.55 42.90 32.12 25.07 35.64 30.98 41.08 26.47 15.77 39.83 24.46 49.45 54.11 66.02 26.72 28.05 30.86 30.73 51.10 15.51 21.70 65.95 20.12 27.61 48.16 18.69 44.34 73.56 16.07 51.27 8.27 12.13 81.49 24.37 50.27 30.65 44.69 32.82 30.75 24.97 20.62 32.22 52.98 84.19 35.94 33.19 39.39 22.26 23.88 17.43 66.11 42.94 73.96 65.80 36.48 41.44
Data Y:
21.056 13.001 175.493 124.034 1.535 619.872 11.037 1390.15 409.316 39.207 9.127 33.873 250.023 4.821 52.783 491.672 1.819 9.41 2.321 37.776 17.457 16.725 2080.916 11.963 55.954 13.187 3.393 1.728 22.252 30.652 1640.385 1.992 9.74 263.206 11937.562 307.475 0.659 40.415 7.799 58.909 53.481 21.109 209.652 39.906 324.146 2.082 0.608 74.873 98.576 nodata 27.407 10.069 6.05 25.683 79.735 11.416 5.054 251.481 2574.807 14.467 1.038 15.23 3651.871 45.464 204.299 1.111 70.806 9.183 1.295 3.591 8.36 22.675 334.104 132.034 24.848 2439.008 1010.937 427.666 192.66 325.649 348.006 1921.139 14.29 4884.489 40.487 156.189 78.397 0.186 1529.743 6.684 118.271 7.061 17.152 30.176 52.698 2.721 2.14 33.314 46.666 63.517 51.16 10.557 6.261 309.858 4.52 14.998 12.011 0.199 4.985 12.273 1142.453 0.329 7.945 10.869 4.405 110.708 12.345 66.966 12.558 0.114 24.065 824.48 200.837 13.692 7.892 394.818 392.052 71.931 nodata 0.321 59.051 21.811 28.78 210.013 321.189 509.955 211.696 103.243 166.346 204.943 1469.341 8.918 0.939 1.717 0.815 0.844 1.633 678.541 16.057 39.366 1.479 3.897 305.757 94.997 48.078 1.273 6.522 344.064 2.915 1307.17 83.567 118.979 3.665 4.03 541.889 680.645 nodata 0.372 571.453 7.234 51.614 437.807 2.716 4.797 0.437 20.3 39.883 841.206 41.67 0.04 26.391 104.062 378.656 2565.051 19362.129 60.266 67.505 0.837 215.307 215.963 25.673 25.576 17.105
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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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