Send output to:
Browser Blue - Charts White
Browser Black/White
CSV
Data X:
4.000 50.000 1.02.909 40.500 27.500 31.500 60.500 47.500 26.94.420 16.75.000 81.564 4.90.531 44.500 9.35.321 12.83.190 14.53.640 14.53.640 1.69.769 4.91.182 2.12.400 10.66.550 51.23.210 1.07.589 50.000 25.15.000 1.34.926 77.799 6.38.394 25.39.000 3.30.314 12.51.320 8.46.000 20.000 11.00.000 6.48.000 6.38.500 1.95.000 6.67.000 6.92.864 11.05.000 2.26.641 17.08.000 5.94.500 6.79.000 6.67.047 9.32.159 2.39.000 26.304 9.34.000 3.90.453 4.28.000 1.40.000 12.96.520 85.500 5.38.000 63.05.000 3.99.050 10.91.950 2.48.000 1.82.200 65.56.000 7.71.000 44.50.000 11.20.820 19.34.000 40.00.000 7.07.001 10.31.210 12.98.750 19.45.000 1.63.000 2.33.500 2.04.000 13.96.000 4.75.882 3.59.900 6.12.264 92.300 10.19.000 97.250 3.66.000 2.59.538 4.73.000 3.00.000 17.97.000 16.31.000 9.81.000 14.80.630 41.46.000 60.250 1.67.987 1.98.604 10.25.130 2.22.000 8.79.166 19.00.000 14.60.000 9.14.874 28.85.000 12.35.770 42.07.960 7.11.250 23.47.000 18.11.350 2.02.532 8.72.074 1.25.520 7.85.000 82.500 52.00.000 23.25.000 4.20.385 66.000 28.85.000 11.53.000 14.99.340 4.31.492 3.50.000 34.24.470 14.13.670 50.13.090 91.260 5.67.000 69.50.420 2.78.900 8.99.000 10.38.240 21.46.550 3.81.157 22.02.810 28.62.000 2.14.733 7.20.482 4.02.500 8.49.330 5.96.833 2.10.000 10.83.750 1.87.940 14.53.000 12.12.700 8.00.430 3.18.032 21.00.000 3.99.217 40.000 6.79.000 40.00.000 18.10.000 20.65.890 26.15.000 3.52.000 1.46.000 1.76.000 34.47.010 1.15.000 10.26.600 7.08.000 2.26.054 12.22.000 4.34.724 2.54.832 8.68.964 8.75.000 13.13.000 12.15.000 21.87.000 17.66.000 11.58.000 1.30.89.000 17.54.420 9.81.469 69.400 9.56.550 30.34.000 59.000 1.16.807 6.83.000 9.67.000 7.82.400 8.62.500 9.26.247 15.95.000 11.53.470 4.30.000 20.25.420 67.74.000 24.67.400 13.28.000 36.600 93.000 2.79.200 5.44.847 1.78.500 23.82.290 8.40.000 3.42.000 8.53.000 1.13.000 65.000 1.60.797 4.34.000
Data Y:
715 9.55.646 13.75.649 5.00.000 47.06.424 10.43.000 8.93.367 10.15.236 10.55.68.000 67.83.67.000 27.61.149 5.48.39.000 31.17.144 32.46.10.000 1.08.86.42.000 18.20.23.000 18.20.23.000 58.29.596 4.86.92.339 1.02.54.799 22.54.38.000 1.66.81.00.000 4.71.33.850 78.33.000 37.48.00.000 1.36.41.221 3.88.06.307 6.24.63.000 71.41.51.000 2.55.26.452 30.52.88.000 2.73.22.000 16.00.000 1.43.79.77.000 2.76.01.000 82.76.33.000 2.20.11.000 17.44.07.000 11.81.05.000 44.97.64.000 2.41.53.310 26.33.12.000 21.44.52.000 63.54.87.000 6.61.79.000 14.30.00.000 8.01.39.887 66.52.015 20.07.00.000 5.99.13.000 7.55.43.000 1.44.56.000 65.59.68.000 35.83.600 8.40.20.000 5.31.78.58.000 5.29.56.000 33.63.89.000 4.88.89.000 3.75.14.000 6.27.35.16.000 12.88.19.000 1.40.13.07.000 55.58.69.000 91.25.08.000 11.45.90.00.000 8.38.14.000 30.70.02.000 6.78.85.000 23.33.88.000 1.15.25.000 4.79.15.000 17.26.60.729 42.96.86.000 11.61.71.000 2.18.56.000 14.74.70.000 1.02.00.000 19.97.95.000 2.94.71.835 15.50.02.000 10.11.86.000 8.09.44.000 4.11.29.205 53.18.72.000 65.72.38.000 14.71.44.000 40.76.57.000 1.39.28.42.000 64.37.036 2.80.41.000 31.54.230 66.36.56.000 2.69.21.000 55.24.56.000 1.36.15.97.000 66.69.31.000 35.02.01.000 37.41.45.000 24.88.15.000 3.12.38.97.000 25.13.55.000 1.76.24.00.000 81.11.30.000 2.51.36.000 16.19.30.000 58.27.041 29.65.57.000 95.48.849 2.71.95.46.000 3.56.65.00.000 10.79.46.000 3.47.00.000 2.96.79.30.000 45.89.63.000 25.28.32.000 22.42.11.000 4.61.77.000 3.35.07.27.000 21.93.72.000 39.77.54.000 3.80.55.000 9.75.11.941 3.08.17.75.000 6.42.08.000 1.02.18.98.000 1.06.91.78.000 54.30.58.000 4.92.00.000 2.69.68.95.000 5.12.72.42.000 7.77.55.000 12.04.73.000 20.70.04.000 31.26.36.000 11.15.97.000 5.14.54.000 1.40.45.67.000 8.71.31.376 47.48.28.000 68.00.41.000 24.63.14.000 5.73.89.000 2.41.43.00.000 3.37.26.952 28.33.345 11.54.27.000 9.07.80.00.000 1.16.57.81.000 1.46.57.20.000 1.96.33.00.000 8.40.80.000 1.65.98.200 5.17.48.825 1.87.25.29.000 1.82.08.000 1.02.26.72.000 27.53.86.000 6.21.55.250 91.53.49.000 14.37.29.000 5.17.00.000 19.03.04.000 24.59.58.000 34.45.67.000 1.35.25.91.000 3.36.94.07.000 33.09.47.000 24.18.21.000 53.09.50.00.000 52.59.30.000 42.07.95.000 3.05.94.342 74.28.38.000 3.21.91.84.000 97.65.000 30.26.000 9.26.73.000 2.40.57.11.000 10.64.42.000 18.32.24.468 32.75.79.000 2.29.32.31.000 61.63.18.000 5.60.78.000 73.74.23.000 12.11.90.00.000 2.81.19.01.000 78.02.90.000 54.82.439 3.44.69.000 58.51.600 29.26.93.000 2.77.77.678 3.34.95.12.000 1.42.15.29.000 14.44.15.000 32.55.62.000 4.25.66.440 2.00.000 44.77.670 1.39.80.000
Chart options
Title:
Label y-axis:
Label x-axis:
R Code
library(psychometric) x <- x[!is.na(y)] y <- y[!is.na(y)] y <- y[!is.na(x)] x <- x[!is.na(x)] 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, sub=main) 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', na.rm = T) cxy <- as.matrix(corxy$estimate)[1,1] load(file='createtable') a<-table.start() a<-table.row.start(a) a<-table.element(a,'Pearson Product Moment Correlation - Ungrouped Data',3,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Statistic',1,TRUE) a<-table.element(a,'Variable X',1,TRUE) a<-table.element(a,'Variable Y',1,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Mean',header=TRUE) a<-table.element(a,mean(x)) a<-table.element(a,mean(y)) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Biased Variance',header=TRUE) a<-table.element(a,varx) a<-table.element(a,vary) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Biased Standard Deviation',header=TRUE) a<-table.element(a,sqrt(varx)) a<-table.element(a,sqrt(vary)) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Covariance',header=TRUE) a<-table.element(a,cov(x,y),2) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Correlation',header=TRUE) a<-table.element(a,cxy,2) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Determination',header=TRUE) a<-table.element(a,cxy*cxy,2) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'T-Test',header=TRUE) a<-table.element(a,as.matrix(corxy$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,'95% CI of Correlation',header=TRUE) a<-table.element(a,paste('[',CIr(r=cxy, n = lx, level = .95)[1],', ', CIr(r=cxy, n = lx, level = .95)[2],']',sep=''),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') library(moments) library(nortest) jarque.x <- jarque.test(x) jarque.y <- jarque.test(y) if(lx>7) { ad.x <- ad.test(x) ad.y <- ad.test(y) } a<-table.start() a<-table.row.start(a) a<-table.element(a,'Normality Tests',1,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,paste('<pre>',RC.texteval('jarque.x'),'</pre>',sep='')) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,paste('<pre>',RC.texteval('jarque.y'),'</pre>',sep='')) a<-table.row.end(a) if(lx>7) { a<-table.row.start(a) a<-table.element(a,paste('<pre>',RC.texteval('ad.x'),'</pre>',sep='')) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,paste('<pre>',RC.texteval('ad.y'),'</pre>',sep='')) a<-table.row.end(a) } a<-table.end(a) table.save(a,file='mytable1.tab') library(car) bitmap(file='test2.png') qqPlot(x,main='QQplot of variable x') dev.off() bitmap(file='test3.png') qqPlot(y,main='QQplot of variable y') dev.off()
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