Send output to:
Browser Blue - Charts White
Browser Black/White
CSV
Data X:
4.75 4.71 4.74 4.92 4.43 4.66 4.82 4.84 4.79 4.95 4.51 4.57 4.73 4.79 4.82 4.97 4.51 4.74 4.93 4.91 4.88 4.97 4.62 4.69 4.91 4.82 4.93 5.06 4.54 4.83 5.04 5.03 5.00 5.14 4.83 4.90 5.04 5.00 5.12 5.17 4.76 4.95 5.10 5.16 5.12 5.12 4.91 5.06 5.02 5.12 5.11 5.23 4.83 4.97 5.20 5.17 5.11 5.20 4.80 4.90 5.09
Data Y:
4.70 4.60 4.46 4.71 4.36 4.34 4.74 4.60 4.55 5.16 4.42 4.49 4.88 4.80 4.65 4.90 4.15 4.72 4.79 4.72 4.84 5.34 4.51 4.76 4.92 4.68 4.92 5.03 4.74 4.79 4.88 4.86 5.23 5.24 4.69 5.06 5.17 4.83 5.04 5.14 4.60 4.94 5.13 4.91 5.13 5.76 5.04 5.08 5.21 5.11 5.31 5.16 4.82 5.04 5.14 5.13 5.14 5.67 4.98 4.90 5.13
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
0 seconds
R Server
Big Analytics Cloud Computing Center
Click here to blog (archive) this computation