Send output to:
Browser Blue - Charts White
Browser Black/White
CSV
Data X:
80.7 86.9 105 95.1 100.2 182.4 90 78.2 97.4 84.2 90 100.9 84.5 92.3 90.3 91 96.4 167.6 88.5 67.5 83 77.7 80.6 96.1 71.2 75.3 90.9 106.4 96.3 181.2 65.4 72.2 80.4 77.7 76.5 100.1 73.5 77.3 98.6 112.4 77.3 139.3 75.4 64.2 86.8 79.1 71.7 100 82.1 74.8 92.3 83.3 83.7 148 71.4 71.2 84.6 80.9 80.6 105.5 79.2 78.4 92.6 88.3 98.2 157.4 73.9 80.9 93 84.9 96.2 106.5 81.7 82.9 96 92.6 116.5 155 95.1 86.2 105 89.7 97.1 120.8 92.2 98.8 104.1 106.5 113.4 192.4 103.6 97.6 99.9 106.2 104.9 114.2 94.5
Data Y:
86.7 87.9 89.8 103 102.7 156.3 95 84.6 106.5 98.7 103.5 110.7 96.2 89.2 97.1 104.8 132.5 154.8 83.6 82.4 103.9 87 93.2 110.5 96.4 76.3 94 103.4 137 150.1 112.6 81.4 113.6 99.6 98.2 118.6 86.8 79.3 98.4 93.6 101 161.2 92.5 99.8 104.1 90.2 99.2 116.5 98.4 90.6 130.5 107.4 106 196.5 107.8 90.5 123.8 114.7 115.3 197 88.4 93.8 111.3 105.9 123.6 171 97 99.2 126.6 103.4 121.3 129.6 110.8 98.9 122.8 120.9 133.1 203.1 110.2 119.5 135.1 113.9 137.4 157.1 126.4 112.2 128.8 136.8 156.5 215.2 146.7 130.8 133.1 154.4 160.4 175.1 145.3
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
0 seconds
R Server
Big Analytics Cloud Computing Center
Click here to blog (archive) this computation