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Data X:
24.90 25.06 25.10 24.92 25.46 25.89 25.39 25.38 25.25 24.88 25.00 25.00 24.07 23.60 23.18 23.25 23.04 22.77 22.25 22.41 22.50 22.91 22.88 21.69 21.19 21.56 22.00 22.13 22.27 22.30 21.94 22.40 22.77 22.90 23.03 23.05 22.41 22.26 21.90 22.01 22.62 22.76 23.40 23.63 24.05 23.82 23.71 23.95 23.61 23.98 23.56 23.99 24.33 24.48 24.31 24.38 24.63 25.54 25.75 25.73 25.85 25.78 25.86 26.86 27.36 27.38 26.58 27.65 27.73 27.18 27.32 27.30 26.90 26.70 26.75 26.41 26.29 27.51 27.91 27.70 27.28 28.25 27.62 27.30 25.94 24.99 25.50 24.42 26.58 25.84 26.76 26.74 26.68 25.55 26.40 25.19 23.94 24.20 24.20 23.07 24.07 25.02 24.65 24.68 24.63 24.49 25.05 24.31 23.90 23.68 24.50 25.22 25.48 26.00 26.07 26.06 26.22 26.70 27.20 26.77 26.11 25.43 24.99 25.51 24.00 23.86 22.96 23.41 23.17 24.12 23.87 24.27 24.40 24.16 25.15 25.09 24.60 24.33 24.14 24.36 25.40 26.15 26.77 26.94 26.33 26.24 26.23 25.88 27.00 26.91 27.15 27.78 28.73 28.83 28.68 27.56 27.15 27.41 27.47 28.76 28.47 27.94 27.23 27.01 26.15 26.11 27.20 27.36 27.33 27.43 28.92 29.45 29.01 29.25 29.14 29.64 30.40 30.62 31.25 31.75 31.30 30.70 31.03 31.46 31.28 31.03 30.95 31.17 31.29 31.91 32.10 31.71 31.90 32.02 32.65 33.77 33.51 34.26 34.21 34.13 34.73 34.73 34.57 34.80 33.98 34.40 34.21 34.61 35.25 35.23 35.00 34.52 33.82 34.35 34.81 34.96 36.69 36.42 36.44 37.41 36.40 36.15 35.78 36.95 36.14 36.36 37.31 37.58 38.00 37.23 37.00 37.87 37.70 36.17 36.56 37.70 38.77 39.02 39.88 39.56 38.52 37.20 38.58 39.41 39.08 38.81 38.73 38.70 39.23 39.82 39.97 40.37 39.54 39.21 39.07 39.78 39.40 38.92
Data Y:
1.439 1.444 1.435 1.430 1.427 1.453 1.448 1.456 1.449 1.437 1.437 1.428 1.413 1.406 1.414 1.415 1.409 1.407 1.400 1.397 1.391 1.394 1.398 1.385 1.369 1.368 1.376 1.374 1.372 1.357 1.361 1.365 1.373 1.357 1.352 1.363 1.358 1.355 1.349 1.357 1.353 1.355 1.364 1.367 1.358 1.366 1.356 1.361 1.366 1.377 1.371 1.372 1.376 1.366 1.355 1.347 1.352 1.334 1.336 1.335 1.347 1.348 1.348 1.347 1.340 1.334 1.330 1.338 1.359 1.358 1.362 1.354 1.354 1.343 1.349 1.337 1.334 1.331 1.332 1.329 1.325 1.326 1.332 1.324 1.309 1.292 1.273 1.275 1.297 1.270 1.267 1.259 1.249 1.235 1.243 1.227 1.233 1.250 1.236 1.222 1.231 1.226 1.238 1.231 1.216 1.222 1.227 1.206 1.196 1.194 1.201 1.205 1.213 1.225 1.226 1.228 1.236 1.237 1.239 1.226 1.227 1.226 1.229 1.234 1.220 1.227 1.233 1.255 1.253 1.258 1.257 1.266 1.264 1.257 1.257 1.270 1.283 1.300 1.296 1.284 1.282 1.285 1.290 1.293 1.303 1.299 1.307 1.303 1.307 1.322 1.321 1.318 1.318 1.325 1.313 1.302 1.279 1.280 1.282 1.286 1.288 1.284 1.271 1.270 1.261 1.261 1.269 1.271 1.270 1.268 1.280 1.282 1.283 1.287 1.274 1.270 1.272 1.273 1.280 1.285 1.299 1.308 1.306 1.307 1.312 1.336 1.332 1.341 1.348 1.346 1.361 1.365 1.373 1.371 1.378 1.386 1.397 1.387 1.394 1.383 1.396 1.410 1.409 1.390 1.386 1.386 1.402 1.393 1.403 1.391 1.380 1.386 1.386 1.393 1.402 1.401 1.424 1.408 1.392 1.395 1.377 1.370 1.371 1.363 1.361 1.348 1.365 1.367 1.365 1.350 1.334 1.332 1.323 1.315 1.300 1.312 1.316 1.325 1.328 1.336 1.320 1.321 1.324 1.327 1.344 1.336 1.324 1.326 1.315 1.316 1.311 1.306 1.310 1.314 1.320 1.314 1.328 1.336
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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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