Send output to:
Browser Blue - Charts White
Browser Black/White
CSV
Data X:
3.9 4.4 4.1 4.1 3.8 3.4 3.4 3.6 3.6 3.4 3.3 3.1 3.2 3.4 3.1 3 2.8 2.5 2.5 2.6 2.5 2.3 2.2 2.1 2.1 2.3 2.2 2.1 1.9 1.7 1.7 1.9 1.8 1.7 1.6 1.6 1.6 1.9 1.8 1.8 1.6 1.5 1.5 1.7 1.7 1.7 1.8 2 2.3 3 3.2 3.4 3.5 3.2 3.2 3.4 3.3 3.1 3.1 3.1
Data Y:
3.2 3.7 3.5 3.4 3.3 3.1 3.4 3.9 3.8 3.4 3.3 3 2.9 3.1 2.9 2.8 2.7 2.5 2.7 3.1 3 2.5 2.3 2.1 2 2.3 2.1 2 1.9 1.8 1.9 2.3 2.2 1.9 1.7 1.6 1.5 1.7 1.6 1.6 1.5 1.4 1.6 1.9 1.8 1.6 1.6 1.6 1.7 2 1.9 2 2.1 2 2.2 2.6 2.6 2.2 2.1 2.1
Sample Range:
(leave blank to include all observations)
From:
To:
Chart options
Label y-axis:
Label x-axis:
R Code
library('Kendall') k <- Kendall(x,y) bitmap(file='test1.png') par(bg=rgb(0.2,0.4,0.6)) plot(x,y,main='Scatterplot',xlab=xlab,ylab=ylab) grid() dev.off() bitmap(file='test2.png') par(bg=rgb(0.2,0.4,0.6)) plot(rank(x),rank(y),main='Scatterplot of Ranks',xlab=xlab,ylab=ylab) grid() dev.off() load(file='createtable') a<-table.start() a<-table.row.start(a) a<-table.element(a,'Kendall tau Rank Correlation',2,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Kendall tau',header=TRUE) a<-table.element(a,k$tau) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'2-sided p-value',header=TRUE) a<-table.element(a,k$sl) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Score',header=TRUE) a<-table.element(a,k$S) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Var(Score)',header=TRUE) a<-table.element(a,k$varS) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Denominator',header=TRUE) a<-table.element(a,k$D) a<-table.row.end(a) a<-table.end(a) table.save(a,file='mytable.tab')
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