Send output to:
Browser Blue - Charts White
Browser Black/White
CSV
Data X:
7 8 8 10 8 9 8 10 7 10 8 8 6 7 9 9 8 8 10 7 7 7 6 9 7 8 10 9 8 8 10 8 4 6 7 7 3 8 8 6 10 8 4 8 7 6 9 10 9 7 10 7 10 9 7 10 8 8 6 9 7 8 8 9 5 9 6 8 10 7 5 4 9 10 8 6 6 9 3 7 9 7 8 9 9 8 9 6 7 8 7 9 9 5 6 8 10 5 8 8 10 7 9 8 8 10 9 9 6 8 5 3 6 6 10 9 9 5 6 7 8 9 3 5 5 9 10 7 8 6 5 8 7 5 6 10 10 6 4 8 5 7 10 8 7 2 7 9 8 5 8 6 7 10 8 10 9 8 10 4 6 9 4 6 7 9 8 6 4 8 8 9 6 5 5 8 8 9 7 9 8 6 7 8 8 7 7 8 8 9 9 9 8 2 8 8 8 7 10 8 10 5 4 10 8 7 5 7 9 8 8 2 9 8 5 7 8 7 5 10 6 6 5 7 8 8 4 9 4 10 6 6 8 8 8 8 8 8 7 7 8 10 10 3 8 2 4 4 9 10 6 10 10 3 9 9 6 5 4 4 6 6 8 8 5 7 6 10 8 8 9 5 10 8 9 8 7 10 10 9 4 4 8 9 10 8 5 10 8 7 8 8 9 8 6 8 8 5 9 8 8 8 6 6 9 8 9 10 8 8 7 7 10 8 7 10 7 7 9 9 8 6 8 9 2 6 8 8 7 8 6 10 10 10 8 8 7 10 5 3 2 3 4 2 6 8 8 5 10 9 8 9 8 5 7 9 8 4 7 8 7 7 9 6 7 4 6 10 9 10 8 4 8 5 8 9 8 4 8 10 6 7 10 9 8 3 8 7 7 8 8 7 7 9 9 9 4 6 6 6 8 3 8 8 6 10 2 9 6 6 5 4 7 5 8 6 9 6 4 7 2 8 9 6 5 7 8 4 9 9 9 7 5 7 9 8 6 9 8 7 7 7 8 10 6 6
Data Y:
22 35 35 32 33 36 35 34 27 30 29 33 32 34 27 31 31 30 40 28 30 27 35 31 28 24 29 38 32 29 37 29 16 38 30 29 30 25 26 24 26 35 25 36 29 37 35 32 29 29 39 30 26 28 32 35 30 34 23 35 29 30 32 32 29 31 30 32 38 29 29 25 37 33 31 30 25 32 22 35 24 30 32 36 32 29 29 30 21 34 33 34 32 35 26 35 29 31 29 29 28 25 31 30 32 34 27 31 24 29 25 28 26 26 27 30 38 24 34 29 24 28 23 24 27 31 30 30 26 25 27 28 29 29 30 30 35 32 24 31 28 30 32 26 24 27 22 34 32 30 29 29 28 30 29 38 32 32 38 27 23 33 23 24 27 29 32 34 23 29 29 36 32 32 30 29 29 33 32 33 28 28 24 32 28 32 33 30 29 32 28 33 32 28 26 30 26 29 31 33 32 24 27 30 27 32 31 33 35 27 27 23 30 27 39 32 32 29 30 35 33 25 33 28 33 29 35 32 29 38 23 29 30 32 32 32 32 34 29 31 23 23 30 14 35 12 20 19 33 33 24 35 35 16 29 33 24 23 22 26 22 24 31 34 34 32 32 32 31 31 35 30 35 33 30 26 35 35 34 32 30 32 32 36 32 33 27 34 34 28 33 38 28 29 26 28 24 35 31 30 26 28 29 24 32 34 37 30 30 23 35 30 35 24 28 30 30 24 38 38 29 29 30 29 21 26 32 35 24 26 25 26 30 27 30 32 30 40 27 18 20 21 22 23 25 31 32 27 33 34 31 33 29 22 31 33 31 33 26 31 28 28 33 34 31 29 31 34 33 37 33 28 35 34 32 34 30 37 24 35 22 25 33 32 35 23 27 27 29 24 31 36 31 38 33 29 26 30 30 24 30 25 30 35 25 35 27 32 27 34 20 22 28 28 33 34 29 29 24 31 24 36 33 28 24 29 26 28 29 35 34 32 28 34 39 33 25 31 31 37 27 36 32 35 33 28
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