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Data X:
2.354 2.318 2.25 2.219 2.206 2.146 2.212 2.243 2.275 2.291 2.141 2.134 2.18 2.183 2.169 2.132 2.092 2.069 2.099 2.073 2.051 2.082 2.059 2.101 2.158 2.153 2.145 2.149 2.135 2.097 2.143 2.13 2.132 2.142 2.094 2.147 2.203 2.244 2.26 2.254 2.231 2.211 2.209 2.191 2.21 2.257 2.252 2.266 2.264 2.265 2.255 2.28 2.288 2.284 2.282 2.271 2.296 2.303 2.316 2.325 2.415 2.402 2.425 2.4 2.424 2.393 2.419 2.415 2.425 2.421 2.378 2.364
Data Y:
352.8 458.2 461.4 422.5 338.1 326.9 414.6 412.7 369.7 409.5 354.2 351.8 333 390.7 384.4 405.6 308.8 339.4 407 371.1 374.4 393.3 328 332.6 300.4 376.1 379 377 272.8 332.4 398.4 327.2 349.1 370.4 293.4 311.9 285.6 297.9 364.2 356.8 244.1 319.5 330.1 297 310.8 315.2 295.4 297.6 264.7 347.8 394.2 343 242.9 310.8 322.9 302.9 319.1 336.4 301 296.7 258.1 320.4 365.1 325 261.1 309.3 347.1 319.8 314.5 345.8 307.6 327
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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')
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