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Data X:
0.468 0.716 0.717 0.83 0.526 0.774 0.808 0.73 0.933 0.881 0.747 0.789 0.815 0.558 0.776 0.786 0.881 0.732 0.476 0.476 0.584 0.584 0.731 0.683 0.744 0.852 0.777 0.388 0.389 0.584 0.504 0.902 0.636 0.341 0.372 0.822 0.719 0.711 0.488 0.564 0.763 0.812 0.815 0.845 0.861 0.9 0.467 0.717 0.7 0.7 0.711 0.682 0.662 0.556 0.381 0.84 0.435 0.724 0.879 0.884 0.674 0.441 0.744 0.911 0.573 0.853 0.744 0.628 0.392 0.396 0.638 0.471 0.617 0.818 0.895 0.586 0.684 0.684 0.642 0.899 0.888 0.872 0.872 0.715 0.89 0.745 0.757 0.535 0.607 0.891 0.891 0.814 0.628 0.628 0.81 0.765 0.486 0.412 0.784 0.889 0.834 0.881 0.881 0.498 0.414 0.773 0.698 0.407 0.829 0.829 0.487 0.771 0.756 0.756 0.63 0.663 0.698 0.789 0.617 0.393 0.524 0.624 0.624 0.54 0.915 0.91 0.614 0.337 0.504 0.944 0.783 0.537 0.775 0.686 0.765 0.491 0.676 0.737 0.66 0.834 0.822 0.851 0.851 0.785 0.785 0.506 0.75 0.714 0.694 0.694 0.836 0.485 0.745 0.745 0.756 0.374 0.901 0.83 0.874 0.491 0.658 0.658 0.869 0.75 0.75 0.473 0.705 0.53 0.898 0.917 0.658 0.658 0.607 0.607 0.722 0.473 0.705 0.766 0.721 0.759 0.698 0.484 0.734 0.827 0.892 0.914 0.79 0.661 0.616 0.616 0.638 0.5 0.561 0.492
Data Y:
307 487 471 NA 370 353 591 554 590 591 514 424 427 488 484 575 591 447 459 558 461 451 442 444 560 441 572 406 412 338 445 565 NA NA NA 574 582 499 NA 397 521 521 386 523 571 550 NA 383 429 NA 457 463 450 NA 389 564 427 NA 522 559 468 464 527 570 419 526 NA 490 382 NA 417 403 462 580 506 577 509 520 360 562 484 561 448 428 542 440 501 427 NA NA 581 344 536 383 562 492 490 314 355 556 550 558 558 468 399 549 400 433 547 NA 354 557 496 NA 528 NA 474 477 505 369 462 347 NA 478 536 608 463 408 418 540 405 497 NA 389 480 NA 508 543 516 565 559 441 312 576 553 396 368 420 NA NA 311 452 551 NA NA 341 605 527 557 398 475 NA 578 477 NA 435 403 446 510 580 470 548 437 368 498 428 NA 479 497 550 472 407 542 385 590 532 587 521 NA 496 542 395 417 488
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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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