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Data X:
4.000 50.000 102.909 40.500 27.500 31.500 60.500 47.500 2.694.420 1.675.000 81.564 490.531 44.500 935.321 1.283.190 1.453.640 1.453.640 169.769 491.182 212.400 1.066.550 5.123.210 107.589 50.000 2.515.000 134.926 77.799 638.394 2.539.000 330.314 1.251.320 846.000 20.000 1.100.000 648.000 638.500 195.000 667.000 692.864 1.105.000 226.641 1.708.000 594.500 679.000 667.047 932.159 239.000 26.304 934.000 390.453 428.000 140.000 1.296.520 85.500 538.000 6.305.000 399.050 1.091.950 248.000 182.200 6.556.000 771.000 4.450.000 1.120.820 1.934.000 4.000.000 707.001 1.031.210 1.298.750 1.945.000 163.000 233.500 204.000 1.396.000 475.882 359.900 612.264 92.300 1.019.000 97.250 366.000 259.538 473.000 300.000 1.797.000 1.631.000 981.000 1.480.630 4.146.000 60.250 167.987 198.604 1.025.130 222.000 879.166 1.900.000 1.460.000 914.874 2.885.000 1.235.770 4.207.960 711.250 2.347.000 1.811.350 202.532 872.074 125.520 785.000 82.500 5.200.000 2.325.000 420.385 66.000 2.885.000 1.153.000 1.499.340 431.492 350.000 3.424.470 1.413.670 5.013.090 91.260 567.000 6.950.420 278.900 899.000 1.038.240 2.146.550 381.157 2.202.810 2.862.000 214.733 720.482 402.500 849.330 596.833 210.000 1.083.750 187.940 1.453.000 1.212.700 800.430 318.032 2.100.000 399.217 40.000 679.000 4.000.000 1.810.000 2.065.890 2.615.000 352.000 146.000 176.000 3.447.010 115.000 1.026.600 708.000 226.054 1.222.000 434.724 254.832 868.964 875.000 1.313.000 1.215.000 2.187.000 1.766.000 1.158.000 13.089.000 1.754.420 981.469 69.400 956.550 3.034.000 59.000 116.807 683.000 967.000 782.400 862.500 926.247 1.595.000 1.153.470 430.000 2.025.420 6.774.000 2.467.400 1.328.000 36.600 93.000 279.200 544.847 178.500 2.382.290 840.000 342.000 853.000 113.000 65.000 160.797 434.000
Data Y:
13.1224 13.7701 14.1344 13.1224 15.3644 13.8576 13.7028 13.8306 18.4749 20.3352 14.8312 17.8199 14.9524 19.5981 20.8082 19.0196 19.0196 15.5785 17.7010 16.1433 19.2336 21.2350 17.6685 15.8739 19.7419 16.4286 17.4741 17.9501 20.3866 17.0552 19.5368 17.1232 14.2855 21.0865 17.1334 20.5341 16.9071 18.9769 18.5871 19.9242 16.9999 19.3889 19.1836 20.2699 18.0079 18.7784 18.1993 15.7104 19.1173 17.9084 18.1402 16.4866 20.3016 15.0919 18.2466 22.3943 17.7850 19.6338 17.7051 17.4402 22.5596 18.6739 21.0607 20.1360 20.6317 23.1620 18.2441 19.5424 18.0333 19.2682 16.2600 17.6849 18.9668 19.8786 18.5706 16.9000 18.8091 16.1379 19.1128 17.1989 18.8589 18.4325 18.2093 17.5322 20.0919 20.3036 18.8069 19.8259 21.0546 15.6776 17.1492 14.9643 20.3133 17.1084 20.1299 21.0319 20.3182 19.6740 19.7402 19.3322 21.8623 19.3424 21.2899 20.5139 17.0398 18.9027 15.5780 19.5078 16.0719 21.7237 21.9949 18.4971 17.3623 21.8111 19.9445 19.3482 19.2281 17.6480 21.9324 19.2063 19.8013 17.4545 18.3955 21.8488 17.9776 20.7449 20.7902 20.1127 17.7114 21.7154 22.3578 18.1691 18.6069 19.1482 19.5606 18.5304 17.7562 21.0630 18.2829 19.9785 20.3377 19.3221 17.8654 21.6047 17.3338 14.8570 18.5641 22.9291 20.8767 21.1056 21.3979 18.2473 16.6248 17.7619 21.3506 16.7174 20.7457 19.4337 17.9451 20.6348 18.7834 17.7610 19.0641 19.3207 19.6578 21.0253 21.9380 19.6175 19.3037 23.1620 20.0807 19.8577 17.2363 20.4260 21.8924 16.0943 14.9228 18.3446 21.6011 18.4831 19.0262 19.6072 21.5532 20.2393 17.8423 20.4187 23.1620 21.7571 20.4752 15.5171 17.3556 15.5822 19.4946 17.1397 21.9321 21.0750 18.7882 19.6011 17.5666 13.1224 15.3146 16.4531
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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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