Send output to:
Browser Blue - Charts White
Browser Black/White
CSV
Data X:
58.5 59.8 64.6 62.2 68 64.3 58.9 64.8 67.5 76.2 73.7 70.4 67.7 63.7 72.4 66 70.1 70.4 66.6 72.6 74 79 76.1 72.3 71.6 67.2 73.8 70.8 71.4 70.4 70.7 70.6 75.5 82.1 74.3 76.3 74.5 71.1 73.3 73.8 69 71.1 71.9 69 77.3 82.8 74 77.6 72.3 70.7 81 76.4 72.3 79.5 73.3 74.5 82.7 83.8 81.6 85.5 76.7 71.8 80.2 76.8 76.1 80.7 71.3 80.9 85 84.5 87.7 87.7 80.2 74.4 85.8 77 84.5 83.6 77.7 85.7 87.9 93.7 92.3 87 89.1 81.3 92.7 83.9 87.3 89.1 86.9 91.7 93 105.3 101.6 94.2 100.5 95.8 95.8 102.1 96 96.8 98.9 93.4 105.5 110.9 98.6 102.6 93.5 90.8 99.7 97.8 91.1 98.1 96 93.5 101.2 105.2 98.9 101.3 92.1 90.6 105.4 98.4 92.7 101.2 93.4 98.3 104.3 107 107.7 108.9 99.6 96.1 109 99.5 104.6 99.9 94.1 105.3 110.4 110.5 110 108.5 104.3 101.2 109.2 99.6 105.6 106.2 102.2 107.5 105.8 120.5 113.2 104.3 107.7 99.2 105.1 104.3 106.1 100.8 106.7 101.6 104.4 114.8 105.4 104 102 96.5 102.3 105.3 101.9 102.2 102.8 100.4 110.7 116.4 106 109.2 103 99.8 109.8 107.3 101.2 111.8 106.9 103.5 113.1 119.4 113.3 115 104.7 107.2 116.6 111.3 111.4 115 102.4 111.4 113.2 112.9 114.2 115.6 107.1 102.3 117.9 105.8 114.3 113.1 102.9 112.2
Data Y:
55.5 63 77.2 71.1 90.1 91.5 76.1 87.8 81 77.2 73.8 68.9 68.4 65.2 78.7 77 97.6 88.1 98.7 93.4 68 87.9 75.8 66.3 68.4 71.3 77.4 87.1 88.5 85.9 92.7 88.5 80.2 81.8 70.4 82.2 72.8 69 83 92.4 92.3 100.5 106.9 99.5 85.9 92.6 77.4 84.1 75.3 73.8 100.1 90.7 96.5 111.8 97.4 100.8 93.7 82 86 84.3 73.1 75.4 97.9 97.5 106 112.8 99.5 100.8 102.9 88.8 91.3 88.3 77.4 80.5 96.7 93.8 105 117.1 111.1 105.8 95.7 97.1 91 90.9 83.5 82.3 101.7 108.3 114 118.2 103.4 106.8 95.4 101.8 95.6 94.8 94 82.4 95.8 106.7 114.1 103.9 117.4 105.9 101.7 98.7 91.3 102.3 80.5 86.7 102.6 107.3 108 124.3 117.1 103.9 104.7 95.9 94.2 102.7 70.3 90.2 107.3 104.6 102.7 124.5 117.8 104.2 99.9 91.5 95.7 91.4 86.2 91.5 115.5 113.9 131.9 121.2 105.2 107.5 113.8 100.5 104.8 103.8 93.1 106.2 117.5 109.9 123.6 131.7 111 122 110.9 108 103.6 107.3 94.4 85.2 113.2 111.7 124.3 124 133.4 112.6 115.8 112.3 103.6 111.4 95.1 93.4 117.3 121.5 123.1 139.3 125.8 108.6 121 111.6 99.7 116.7 90.3 90.4 117.3 121.6 114.6 133.3 127.4 115 112.6 108.3 107.6 109 89 102.5 124.5 124.2 130.8 138.7 127.6 130.9 136.9 125.2 131.3 124.1 103.2 118.1 136.5 117.8 145.1 158.8 136.9 132.7
Chart options
Title:
Label y-axis:
Label x-axis:
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()
Compute
Summary of computational transaction
Raw Input
view raw input (R code)
Raw Output
view raw output of R engine
Computing time
0 seconds
R Server
Big Analytics Cloud Computing Center
Click here to blog (archive) this computation