Send output to:
Browser Blue - Charts White
Browser Black/White
CSV
Data X:
12 8 11 13 11 10 7 10 15 12 12 10 10 14 6 12 14 11 8 12 15 13 11 12 7 11 7 12 12 13 9 11 12 15 12 6 5 13 11 6 12 10 6 12 11 6 12 12 8 10 11 7 12 13 14 12 6 14 10 12 11 10 7 12 7 12 12 10 10 12 12 12 8 10 5 10 12 11 9 12 11 10 12 10 9 11 12 7 11 12 6 9 15 10 11 12 12 12 11 9 11 12 12 14 8 10 9 10 9 10 12 11 9 11 12 12 7 12 12 12 10 15 10 15 10 15 9 15 12 13 12 12 8 9 15 12 12 15 11 12 6 14 12 12 12 11 12 12 12 12 8 8 12 12 11 10 11 12 13 12 12 10 10 11 8 12 9 12 9 11 15 8 8 11 11 11 13 7 12 8 8 4 11 10 7 12 11 9 10 8 8 11 12 10 10 12 8 11 8 10 14 9 9 10 13 12 13 8 3 8 12 11 9 12 12 12 10 13 9 12 11 14 11 9 12 8 15 12 14 12 9 9 13 13 15 11 7 10 11 14 14 13 12 8 13 9 12 13 11 11 13 12 12 10 9 10 13 13 9 11 12 8 12 12 12 9 12 12 11 12 6 7 10 12 10 12 9 3
Data Y:
4 4 5 4 4 9 8 11 4 4 6 4 8 4 4 11 4 4 6 6 4 8 5 4 9 4 7 10 4 4 7 12 7 5 8 5 4 9 7 4 4 4 4 4 7 4 7 4 4 4 4 8 4 4 4 4 7 12 4 4 4 5 15 5 10 9 8 4 5 4 9 4 10 4 4 7 5 4 4 4 4 4 4 6 10 7 4 4 7 4 8 11 6 14 5 4 8 9 4 4 5 4 5 4 4 7 10 4 5 4 4 4 6 4 8 5 4 17 4 4 8 4 7 4 4 5 7 4 4 7 11 7 4 4 4 4 4 4 6 8 23 4 8 6 4 7 4 4 4 10 6 5 5 4 4 5 5 5 5 4 6 4 4 4 9 18 6 5 4 11 4 10 6 8 8 6 8 4 4 9 9 5 4 4 15 10 9 7 9 6 4 7 4 7 4 15 4 9 4 4 28 4 4 4 5 4 4 12 4 6 6 5 4 4 4 10 7 4 7 4 4 12 5 8 6 17 4 5 4 5 5 6 4 4 4 6 8 10 4 5 4 4 4 16 7 4 4 14 5 5 5 5 7 19 16 4 4 7 9 5 14 4 16 10 5 6 4 4 4 5 4 4 5 4 4 5 8 15
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$estimate)[1,1] load(file='createtable') a<-table.start() a<-table.row.start(a) a<-table.element(a,'Pearson Product Moment Correlation - Ungrouped Data',3,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Statistic',1,TRUE) a<-table.element(a,'Variable X',1,TRUE) a<-table.element(a,'Variable Y',1,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,hyperlink('http://www.xycoon.com/arithmetic_mean.htm','Mean',''),header=TRUE) a<-table.element(a,mean(x)) a<-table.element(a,mean(y)) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,hyperlink('http://www.xycoon.com/biased.htm','Biased Variance',''),header=TRUE) a<-table.element(a,varx) a<-table.element(a,vary) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,hyperlink('http://www.xycoon.com/biased1.htm','Biased Standard Deviation',''),header=TRUE) a<-table.element(a,sqrt(varx)) a<-table.element(a,sqrt(vary)) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,hyperlink('http://www.xycoon.com/covariance.htm','Covariance',''),header=TRUE) a<-table.element(a,cov(x,y),2) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,hyperlink('http://www.xycoon.com/pearson_correlation.htm','Correlation',''),header=TRUE) a<-table.element(a,cxy,2) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,hyperlink('http://www.xycoon.com/coeff_of_determination.htm','Determination',''),header=TRUE) a<-table.element(a,cxy*cxy,2) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,hyperlink('http://www.xycoon.com/ttest_statistic.htm','T-Test',''),header=TRUE) a<-table.element(a,as.matrix(corxy$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()
Compute
Summary of computational transaction
Raw Input
view raw input (R code)
Raw Output
view raw output of R engine
Computing time
1 seconds
R Server
Big Analytics Cloud Computing Center
Click here to blog (archive) this computation