Send output to:
Browser Blue - Charts White
Browser Black/White
CSV
Data X:
97.3 101.0 113.2 101.0 105.7 113.9 86.4 96.5 103.3 114.9 105.8 94.2 98.4 99.4 108.8 112.6 104.4 112.2 81.1 97.1 112.6 113.8 107.8 103.2 103.3 101.2 107.7 110.4 101.9 115.9 89.9 88.6 117.2 123.9 100.0 103.6 94.1 98.7 119.5 112.7 104.4 124.7 89.1 97.0 121.6 118.8 114.0 111.5 97.2 102.5 113.4 109.8 104.9 126.1 80.0 96.8 117.2 112.3 117.3 111.1 102.2 104.3 122.9 107.6 121.3 131.5 89.0 104.4 128.9 135.9 133.3 121.3 120.5 120.4 137.9 126.1 133.2 146.6 103.4 117.2
Data Y:
96.5 97.3 122.0 91.0 107.9 114.6 98.0 95.5 98.7 115.9 110.4 109.5 92.3 102.1 112.8 110.2 98.9 119.0 104.3 98.8 109.4 170.3 118.0 116.9 111.7 116.8 116.1 114.8 110.8 122.8 104.7 86.0 127.2 126.1 114.6 127.8 105.2 113.1 161.0 126.9 117.7 144.9 119.4 107.1 142.8 126.2 126.9 179.2 105.3 114.8 125.4 113.2 134.4 150.0 100.9 101.8 137.7 138.7 135.4 153.8 119.5 123.3 166.4 137.5 142.2 167.0 112.3 120.6 154.9 153.4 156.2 175.8 131.7 130.1 161.1 128.2 140.3 168.2 110.2 126.2
Chart options
Title:
Label y-axis:
Label x-axis:
R Code
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) 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') 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,'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')
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