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Data:
-2.8383455253 -6.8876476771 -7.4106697959 21.5609086781 -14.7163972633 -8.9731065875 -21.3856911445 -12.92515467 29.2447935282 3.2344204049 -35.2373838504 -27.1792379163 5.6337793547 -17.4188046701 1.57717113 14.7492731318 -8.6464544896 -28.2505458756 11.8466034378 -4.2815086526 -19.5294728073 -9.7870674112 3.9260353751 -10.6842063204 5.2482378668 -8.2496164978 11.8185907956 13.5347210251 -8.3055882213 -11.4457118176 -29.7146224435 -2.9525507815 11.8343015352 -14.580699983 17.468430382 -18.3658451479 -12.4496913271 14.4134668292 14.7736363482 28.5434853104 5.6047909046 -20.0055017819 -11.8235293595 13.2232096387 42.9217520606 15.1990682348 5.4721970806 -1.235261552 6.2473801417 2.6208358575 -4.731176187 34.2228181964 -15.9938460107 13.4948790191 8.5358919008 -38.9718418159 9.3537516169 -0.9476791512 29.4611346487 -20.0530302742 5.187887602 1.0711050037 15.2581910924 10.1549289227 -24.470923332 27.0065923012 7.1923091618 13.2445018346 12.1883858068 -29.4688903527 6.8485379664 15.2470262084 18.1806960883 18.6627589331 15.5690757884 -3.8188078036 13.4365678512 -10.7144988358 17.2186220641 1.8802105698 24.7921510147 -13.5084923467 23.966532712 26.9724458943 11.1740372181 -2.4950325527 -21.2665295414 -13.0130569535 10.579067621 -15.5669323549 0.7161494212 26.6346510236 3.7208761669 -27.9710694652 -0.0648377608 -9.1023753862 -14.1195227024 -0.9888045718 23.994963672 6.1141151687 18.8590831063 -6.2679218578 33.654771004 -11.8338248695 -66.1273159327 -14.8034081555 4.7257859336 35.0184266599 41.5978086796 -50.0753579077 -50.4927006049 -44.4856366272 0.0336439267 -5.0427554882 9.8664792844 -30.5456405658 30.510595308 32.9930138008 4.9380784794 -17.486826193 -29.1683681672 2.5726588033 15.9187027322 -7.4464242839 -37.0097494808 12.1802755329 -24.857269276 0.8353015574 8.7395262687 37.1026630382 -28.3412120096 28.0745111985 -4.4937418387 6.7722682701 17.3390204789 -1.9768117774 -4.7802133527 -9.6924338679 5.2322440793 -6.1785460882 14.5541593128 9.4626062006 -7.1795635107 23.139950353 -15.3692470207 0.6380593989 -0.1913211067 8.393052097 -2.7043425142 19.3025817229 11.8590522423 13.737435535 -32.976809998 8.9321765586 -23.4072121248 29.1797829312 -6.4315902457 -33.6187541773 -12.7532638124 17.900629555 -28.6638737224 -7.9134852185 0.5440465541 1.5308076778 -9.9445935911 24.2138934862 34.2585254263 -21.6496089751 21.8993054602 -64.3898034075 3.8566750666 22.0351854485 -41.4050648243 -28.600778474 -1.7926413646 -23.0791094171 44.2911962949 -34.4859128744 15.9985201915 -13.0489016616 24.6440844032 8.4955651609 23.7684747276 2.5890443113 27.7934097507 4.4967994243 5.171841539 -46.4502832315 -1.0057205665 -21.0381984609 0.9399927234 13.5110981027 12.6978693833 19.9779995145 30.217075069 -23.2973535559 -37.1214968815 -1.3331763845 8.6701470333 -17.857403047 1.1282704284 17.2453755416 21.0867167816 2.929145428 6.8033064931 -32.4708151229 19.3329284734 43.7845158826 -23.5864717383 -31.6624837326 5.1618724628 -7.5894285805 -46.6677640237 -6.4590214655 8.6433795337 27.5144187137 2.7080226974 -0.8711790688 -38.3967541283 -40.8912582438 24.0155339282 110.9616414718 5.9051934629 -36.6386140834 -21.0086524619 -21.8505511409 52.5971924268 19.3857309698 33.592904279 1.0945412587 5.8081517202 -12.6016245649 48.2523678578 -45.1149045784 -19.4985759372 26.0414455706 -24.6417039855 -40.4089848418 36.0058194456 1.6296105786 -7.7212461123 -10.7484313744 12.9541166185 -12.8221559942 48.5900401558 -37.6556594764 -9.9746259919 7.5428874735 23.8640277893 18.2360952313 49.0302087067 -12.020615523 -38.1531654177 37.8849583281 -36.9571423385 -18.5873987221 -18.2247924757 7.7544651181 0.3562041314 -11.0810827941 36.1855810186 -17.1381672207 -14.1659765118 -13.647508575 -24.1415952183 4.538750917 12.2560450727 2.144174854 -6.6478122338
Sample Range:
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Number of bins
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Colour
grey
grey
white
blue
red
black
brown
yellow
Bins are closed on right side
FALSE
FALSE
TRUE
Scale of data
Interval/Ratio
Unknown
Interval/Ratio
3-point Likert
4-point Likert
5-point Likert
6-point Likert
7-point Likert
8-point Likert
9-point Likert
10-point Likert
11-point Likert
Chart options
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Label x-axis:
R Code
par4 <- 'Unknown' par3 <- 'FALSE' par2 <- 'grey' par1 <- '' par1 <- as.numeric(par1) if (par3 == 'TRUE') par3 <- TRUE if (par3 == 'FALSE') par3 <- FALSE if (par4 == 'Unknown') par1 <- as.numeric(par1) if (par4 == 'Interval/Ratio') par1 <- as.numeric(par1) if (par4 == '3-point Likert') par1 <- c(1:3 - 0.5, 3.5) if (par4 == '4-point Likert') par1 <- c(1:4 - 0.5, 4.5) if (par4 == '5-point Likert') par1 <- c(1:5 - 0.5, 5.5) if (par4 == '6-point Likert') par1 <- c(1:6 - 0.5, 6.5) if (par4 == '7-point Likert') par1 <- c(1:7 - 0.5, 7.5) if (par4 == '8-point Likert') par1 <- c(1:8 - 0.5, 8.5) if (par4 == '9-point Likert') par1 <- c(1:9 - 0.5, 9.5) if (par4 == '10-point Likert') par1 <- c(1:10 - 0.5, 10.5) bitmap(file='test1.png') if(is.numeric(x[1])) { if (is.na(par1)) { myhist<-hist(x,col=par2,main=main,xlab=xlab,right=par3) } else { if (par1 < 0) par1 <- 3 if (par1 > 50) par1 <- 50 myhist<-hist(x,breaks=par1,col=par2,main=main,xlab=xlab,right=par3) } } else { plot(mytab <- table(x),col=par2,main='Frequency Plot',xlab=xlab,ylab='Absolute Frequency') } dev.off() if(is.numeric(x[1])) { myhist n <- length(x) load(file='createtable') a<-table.start() a<-table.row.start(a) a<-table.element(a,hyperlink('http://www.xycoon.com/histogram.htm','Frequency Table (Histogram)',''),6,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Bins',header=TRUE) a<-table.element(a,'Midpoint',header=TRUE) a<-table.element(a,'Abs. Frequency',header=TRUE) a<-table.element(a,'Rel. Frequency',header=TRUE) a<-table.element(a,'Cumul. Rel. Freq.',header=TRUE) a<-table.element(a,'Density',header=TRUE) a<-table.row.end(a) crf <- 0 if (par3 == FALSE) mybracket <- '[' else mybracket <- ']' mynumrows <- (length(myhist$breaks)-1) for (i in 1:mynumrows) { a<-table.row.start(a) if (i == 1) dum <- paste('[',myhist$breaks[i],sep='') else dum <- paste(mybracket,myhist$breaks[i],sep='') dum <- paste(dum,myhist$breaks[i+1],sep=',') if (i==mynumrows) dum <- paste(dum,']',sep='') else dum <- paste(dum,mybracket,sep='') a<-table.element(a,dum,header=TRUE) a<-table.element(a,myhist$mids[i]) a<-table.element(a,myhist$counts[i]) rf <- myhist$counts[i]/n crf <- crf + rf a<-table.element(a,round(rf,6)) a<-table.element(a,round(crf,6)) a<-table.element(a,round(myhist$density[i],6)) a<-table.row.end(a) } a<-table.end(a) table.save(a,file='mytable.tab') } else { mytab reltab <- mytab / sum(mytab) n <- length(mytab) load(file='createtable') a<-table.start() a<-table.row.start(a) a<-table.element(a,'Frequency Table (Categorical Data)',3,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Category',header=TRUE) a<-table.element(a,'Abs. Frequency',header=TRUE) a<-table.element(a,'Rel. Frequency',header=TRUE) a<-table.row.end(a) for (i in 1:n) { a<-table.row.start(a) a<-table.element(a,labels(mytab)$x[i],header=TRUE) a<-table.element(a,mytab[i]) a<-table.element(a,round(reltab[i],4)) a<-table.row.end(a) } a<-table.end(a) table.save(a,file='mytable1.tab') }
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Computing time
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R Server
Big Analytics Cloud Computing Center
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