central tendency werkloosheid

*The author of this computation has been verified*

R Software Module: /rwasp_centraltendency.wasp (opens new window with default values)

Title produced by software: Central Tendency

Date of computation: Fri, 17 Dec 2010 14:34:23 +0000

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2010/Dec/17/t1292596460rgr9ufggzgugl9b.htm/, Retrieved Fri, 17 Dec 2010 15:34:21 +0100

BibTeX entries for LaTeX users:

@Manual{KEY, author = {{YOUR NAME}}, publisher = {Office for Research Development and Education}, title = {Statistical Computations at FreeStatistics.org, URL http://www.freestatistics.org/blog/date/2010/Dec/17/t1292596460rgr9ufggzgugl9b.htm/}, year = {2010}, } @Manual{R, title = {R: A Language and Environment for Statistical Computing}, author = {{R Development Core Team}}, organization = {R Foundation for Statistical Computing}, address = {Vienna, Austria}, year = {2010}, note = {{ISBN} 3-900051-07-0}, url = {http://www.R-project.org}, }

Original text written by user:

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Dataseries X:

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206010 198112 194519 185705 180173 176142 203401 221902 197378 185001 176356 180449 180144 173666 165688 161570 156145 153730 182698 200765 176512 166618 158644 159585 163095 159044 155511 153745 150569 150605 179612 194690 189917 184128 175335 179566 181140 177876 175041 169292 166070 166972 206348 215706 202108 195411 193111 195198 198770 194163 190420 189733 186029 191531 232571 243477 227247 217859 208679 213188 216234 213586 209465 204045 200237 203666 241476 260307 243324 244460 233575 237217 235243 230354 227184 221678 217142 219452 256446 265845 248624 241114 229245 231805 219277 219313 212610 214771 211142 211457 240048 240636 230580 208795 197922 194596 194581 185686 178106 172608 167302 168053 202300 202388 182516 173476 166444 171297 169701 164182 161914 159612 151001 158114 186530 187069 174330 169362 166827 178037 186413 189226 191563 188906 186005 195309 223532 226899 etc...

Output produced by software:

Summary of computational transaction Raw Input view raw input (R code) Raw Output view raw output of R engine Computing time 2 seconds R Server 'RServer@AstonUniversity' @ vre.aston.ac.uk Central Tendency - Ungrouped Data Measure Value S.E. Value/S.E. Arithmetic Mean 197005.174825175 2200.56176092777 89.5249469126995 Geometric Mean 195277.577130976 Harmonic Mean 193570.878649083 Quadratic Mean 198742.722988634 Winsorized Mean ( 1 / 47 ) 196966.699300699 2192.31804704219 89.844034977699 Winsorized Mean ( 2 / 47 ) 196918.237762238 2180.81057551357 90.2958927168006 Winsorized Mean ( 3 / 47 ) 196811.391608392 2142.75176581791 91.8498328868563 Winsorized Mean ( 4 / 47 ) 196695.335664336 2123.54718548123 92.6258370942493 Winsorized Mean ( 5 / 47 ) 196722.713286713 2109.49687101341 93.2557502169733 Winsorized Mean ( 6 / 47 ) 196742.895104895 2104.85909480747 93.4708150252172 Winsorized Mean ( 7 / 47 ) 196748.818181818 2078.09605132347 94.6774419096344 Winsorized Mean ( 8 / 47 ) 196758.216783217 2071.17183386684 94.9984996734303 Winsorized Mean ( 9 / 47 ) 196753.307692308 2063.39916775763 95.3539725937403 Winsorized Mean ( 10 / 47 ) 196750.020979021 2052.41880660214 95.8625112701773 Winsorized Mean ( 11 / 47 ) 196534.328671329 2020.53155856486 97.2686260891283 Winsorized Mean ( 12 / 47 ) 196532.986013986 1976.55100159631 99.4322867739116 Winsorized Mean ( 13 / 47 ) 196412.622377622 1952.03357468738 100.619489810301 Winsorized Mean ( 14 / 47 ) 196429.951048951 1924.69759169969 102.057565768285 Winsorized Mean ( 15 / 47 ) 196463.622377622 1900.34871233798 103.382932354513 Winsorized Mean ( 16 / 47 ) 196495.062937063 1862.64567211639 105.492454028468 Winsorized Mean ( 17 / 47 ) 196513.608391608 1853.91711964156 105.999133569468 Winsorized Mean ( 18 / 47 ) 196456.587412587 1835.18788127304 107.049850000267 Winsorized Mean ( 19 / 47 ) 196442.237762238 1827.78311016364 107.475682792938 Winsorized Mean ( 20 / 47 ) 196456.643356643 1822.55745262484 107.791742352872 Winsorized Mean ( 21 / 47 ) 196200.090909091 1785.55115212724 109.882089166331 Winsorized Mean ( 22 / 47 ) 196241.167832168 1778.52895292204 110.339034689176 Winsorized Mean ( 23 / 47 ) 196316.118881119 1759.16053180657 111.596477599183 Winsorized Mean ( 24 / 47 ) 195958.972027972 1668.1649250809 117.469783162159 Winsorized Mean ( 25 / 47 ) 195686.244755245 1634.09431876185 119.752111312348 Winsorized Mean ( 26 / 47 ) 195707.153846154 1622.52335434326 120.619005774107 Winsorized Mean ( 27 / 47 ) 195762.475524476 1561.35735401701 125.379673667162 Winsorized Mean ( 28 / 47 ) 195838.447552448 1513.35264940902 129.407014041919 Winsorized Mean ( 29 / 47 ) 195986.286713287 1491.38065183164 131.412652076843 Winsorized Mean ( 30 / 47 ) 196018.594405594 1486.31938572539 131.881879687607 Winsorized Mean ( 31 / 47 ) 195855.13986014 1437.59663167608 136.237895627088 Winsorized Mean ( 32 / 47 ) 195853.797202797 1403.68443780699 139.528366866262 Winsorized Mean ( 33 / 47 ) 195712.104895105 1374.39220909523 142.3990208908 Winsorized Mean ( 34 / 47 ) 195778.440559441 1341.31513600014 145.960062109834 Winsorized Mean ( 35 / 47 ) 195601.972027972 1312.16481105704 149.068143254354 Winsorized Mean ( 36 / 47 ) 195527.706293706 1296.47287293499 150.815115669228 Winsorized Mean ( 37 / 47 ) 195830.433566434 1255.32746633129 155.999481265833 Winsorized Mean ( 38 / 47 ) 195729.72027972 1236.35515360001 158.311889354605 Winsorized Mean ( 39 / 47 ) 195639.993006993 1223.45516347476 159.907775002847 Winsorized Mean ( 40 / 47 ) 195886.706293706 1166.38583106429 167.943317791306 Winsorized Mean ( 41 / 47 ) 195893.587412587 1164.44983284414 168.228447363956 Winsorized Mean ( 42 / 47 ) 195838.370629371 1127.84088951644 173.640069667394 Winsorized Mean ( 43 / 47 ) 195723.503496503 1114.65769914251 175.59068012276 Winsorized Mean ( 44 / 47 ) 195711.503496503 1096.70546392636 178.454024288188 Winsorized Mean ( 45 / 47 ) 195401.223776224 1023.68959125293 190.879369533361 Winsorized Mean ( 46 / 47 ) 195628.328671329 959.835547949377 203.81442330332 Winsorized Mean ( 47 / 47 ) 195650.020979021 950.405819766736 205.859451730883 Trimmed Mean ( 1 / 47 ) 196846.283687943 2152.17001444039 91.4640954790587 Trimmed Mean ( 2 / 47 ) 196722.402877698 2108.32670715171 93.3073618099084 Trimmed Mean ( 3 / 47 ) 196620.197080292 2067.01279123169 95.122873895294 Trimmed Mean ( 4 / 47 ) 196552.688888889 2036.99098102275 96.491683429154 Trimmed Mean ( 5 / 47 ) 196514.345864662 2010.07963986092 97.7644576700746 Trimmed Mean ( 6 / 47 ) 196468.854961832 1984.17964805685 99.0176747121854 Trimmed Mean ( 7 / 47 ) 196418.224806202 1956.78900706578 100.37782514975 Trimmed Mean ( 8 / 47 ) 196365.047244094 1931.96128566442 101.640259927135 Trimmed Mean ( 9 / 47 ) 196308.824 1905.87062804561 103.002177121176 Trimmed Mean ( 10 / 47 ) 196251.406504065 1878.40663997698 104.477594109479 Trimmed Mean ( 11 / 47 ) 196192.479338843 1849.80744877253 106.061027848617 Trimmed Mean ( 12 / 47 ) 196155.134453782 1822.93869420407 107.603802079272 Trimmed Mean ( 13 / 47 ) 196116.64957265 1799.29582176388 108.996334677415 Trimmed Mean ( 14 / 47 ) 196088.339130435 1776.31333692031 110.390624815329 Trimmed Mean ( 15 / 47 ) 196057.460176991 1754.22073191198 111.763278480526 Trimmed Mean ( 16 / 47 ) 196022.576576577 1732.57370974896 113.139530787974 Trimmed Mean ( 17 / 47 ) 195983.834862385 1712.8552622521 114.419378672254 Trimmed Mean ( 18 / 47 ) 195942.186915888 1691.75558909082 115.821805572512 Trimmed Mean ( 19 / 47 ) 195903.266666667 1670.22463439888 117.291568230984 Trimmed Mean ( 20 / 47 ) 195863.883495146 1646.8512842243 118.932344026074 Trimmed Mean ( 21 / 47 ) 195821.920792079 1621.11598235724 120.794516199475 Trimmed Mean ( 22 / 47 ) 195795.909090909 1596.32164105898 122.654422551724 Trimmed Mean ( 23 / 47 ) 195766.072164948 1569.06610082154 124.765981536692 Trimmed Mean ( 24 / 47 ) 195730.073684211 1540.36591013963 127.067258757024 Trimmed Mean ( 25 / 47 ) 195715.408602151 1518.02765381458 128.927432982098 Trimmed Mean ( 26 / 47 ) 195717.241758242 1496.282510505 130.802332035671 Trimmed Mean ( 27 / 47 ) 195717.865168539 1472.65978495873 132.900936908537 Trimmed Mean ( 28 / 47 ) 195715.149425287 1452.31221744465 134.761070708095 Trimmed Mean ( 29 / 47 ) 195707.741176471 1434.06592923707 136.470532620901 Trimmed Mean ( 30 / 47 ) 195691.192771084 1415.26513814281 138.27175381984 Trimmed Mean ( 31 / 47 ) 195691.192771084 1393.92537713831 140.388571713095 Trimmed Mean ( 32 / 47 ) 195661.227848101 1374.58902193022 142.341619732529 Trimmed Mean ( 33 / 47 ) 195650.051948052 1355.75789614709 144.310464651593 Trimmed Mean ( 34 / 47 ) 195646.466666667 1336.93476622052 146.339575879049 Trimmed Mean ( 35 / 47 ) 195638.863013699 1318.49812949108 148.380083852839 Trimmed Mean ( 36 / 47 ) 195640.985915493 1300.0045464234 150.492539778991 Trimmed Mean ( 37 / 47 ) 195647.507246377 1279.76348395346 152.877863526767 Trimmed Mean ( 38 / 47 ) 195636.955223881 1260.61692241195 155.19143979883 Trimmed Mean ( 39 / 47 ) 195631.584615385 1239.89327760581 157.7809865968 Trimmed Mean ( 40 / 47 ) 195631.095238095 1216.4537154955 160.820829223584 Trimmed Mean ( 41 / 47 ) 195616.114754098 1195.79831123256 163.586210915843 Trimmed Mean ( 42 / 47 ) 195599.711864407 1170.62284271641 167.090291361922 Trimmed Mean ( 43 / 47 ) 195585.456140351 1145.14020496025 170.796078325745 Trimmed Mean ( 44 / 47 ) 195577.109090909 1115.60150847224 175.310904122693 Trimmed Mean ( 45 / 47 ) 195568.867924528 1081.78514208752 180.783466435062 Trimmed Mean ( 46 / 47 ) 195579.31372549 1052.34263058624 185.851364414018 Trimmed Mean ( 47 / 47 ) 195579.31372549 1026.56649377384 190.517920574737 Median 195309 Midrange 208207 Midmean - Weighted Average at Xnp 195373.138888889 Midmean - Weighted Average at X(n+1)p 195638.863013699 Midmean - Empirical Distribution Function 195638.863013699 Midmean - Empirical Distribution Function - Averaging 195638.863013699 Midmean - Empirical Distribution Function - Interpolation 195640.985915493 Midmean - Closest Observation 195373.138888889 Midmean - True Basic - Statistics Graphics Toolkit 195638.863013699 Midmean - MS Excel (old versions) 195638.863013699 Number of observations 143

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Dec/17/t1292596460rgr9ufggzgugl9b/1sk6c1292596458.png (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/17/t1292596460rgr9ufggzgugl9b/1sk6c1292596458.ps (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/17/t1292596460rgr9ufggzgugl9b/2sk6c1292596458.png (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/17/t1292596460rgr9ufggzgugl9b/2sk6c1292596458.ps (open in new window)

Parameters (Session):

Parameters (R input):

R code (references can be found in the software module):

geomean <- function(x) { return(exp(mean(log(x)))) } harmean <- function(x) { return(1/mean(1/x)) } quamean <- function(x) { return(sqrt(mean(x*x))) } winmean <- function(x) { x <-sort(x[!is.na(x)]) n<-length(x) denom <- 3 nodenom <- n/denom if (nodenom>40) denom <- n/40 sqrtn = sqrt(n) roundnodenom = floor(nodenom) win <- array(NA,dim=c(roundnodenom,2)) for (j in 1:roundnodenom) { win[j,1] <- (j*x[j+1]+sum(x[(j+1):(n-j)])+j*x[n-j])/n win[j,2] <- sd(c(rep(x[j+1],j),x[(j+1):(n-j)],rep(x[n-j],j)))/sqrtn } return(win) } trimean <- function(x) { x <-sort(x[!is.na(x)]) n<-length(x) denom <- 3 nodenom <- n/denom if (nodenom>40) denom <- n/40 sqrtn = sqrt(n) roundnodenom = floor(nodenom) tri <- array(NA,dim=c(roundnodenom,2)) for (j in 1:roundnodenom) { tri[j,1] <- mean(x,trim=j/n) tri[j,2] <- sd(x[(j+1):(n-j)]) / sqrt(n-j*2) } return(tri) } midrange <- function(x) { return((max(x)+min(x))/2) } q1 <- function(data,n,p,i,f) { np <- n*p; i <<- floor(np) f <<- np - i qvalue <- (1-f)*data[i] + f*data[i+1] } q2 <- function(data,n,p,i,f) { np <- (n+1)*p i <<- floor(np) f <<- np - i qvalue <- (1-f)*data[i] + f*data[i+1] } q3 <- function(data,n,p,i,f) { np <- n*p i <<- floor(np) f <<- np - i if (f==0) { qvalue <- data[i] } else { qvalue <- data[i+1] } } q4 <- function(data,n,p,i,f) { np <- n*p i <<- floor(np) f <<- np - i if (f==0) { qvalue <- (data[i]+data[i+1])/2 } else { qvalue <- data[i+1] } } q5 <- function(data,n,p,i,f) { np <- (n-1)*p i <<- floor(np) f <<- np - i if (f==0) { qvalue <- data[i+1] } else { qvalue <- data[i+1] + f*(data[i+2]-data[i+1]) } } q6 <- function(data,n,p,i,f) { np <- n*p+0.5 i <<- floor(np) f <<- np - i qvalue <- data[i] } q7 <- function(data,n,p,i,f) { np <- (n+1)*p i <<- floor(np) f <<- np - i if (f==0) { qvalue <- data[i] } else { qvalue <- f*data[i] + (1-f)*data[i+1] } } q8 <- function(data,n,p,i,f) { np <- (n+1)*p i <<- floor(np) f <<- np - i if (f==0) { qvalue <- data[i] } else { if (f == 0.5) { qvalue <- (data[i]+data[i+1])/2 } else { if (f < 0.5) { qvalue <- data[i] } else { qvalue <- data[i+1] } } } } midmean <- function(x,def) { x <-sort(x[!is.na(x)]) n<-length(x) if (def==1) { qvalue1 <- q1(x,n,0.25,i,f) qvalue3 <- q1(x,n,0.75,i,f) } if (def==2) { qvalue1 <- q2(x,n,0.25,i,f) qvalue3 <- q2(x,n,0.75,i,f) } if (def==3) { qvalue1 <- q3(x,n,0.25,i,f) qvalue3 <- q3(x,n,0.75,i,f) } if (def==4) { qvalue1 <- q4(x,n,0.25,i,f) qvalue3 <- q4(x,n,0.75,i,f) } if (def==5) { qvalue1 <- q5(x,n,0.25,i,f) qvalue3 <- q5(x,n,0.75,i,f) } if (def==6) { qvalue1 <- q6(x,n,0.25,i,f) qvalue3 <- q6(x,n,0.75,i,f) } if (def==7) { qvalue1 <- q7(x,n,0.25,i,f) qvalue3 <- q7(x,n,0.75,i,f) } if (def==8) { qvalue1 <- q8(x,n,0.25,i,f) qvalue3 <- q8(x,n,0.75,i,f) } midm <- 0 myn <- 0 roundno4 <- round(n/4) round3no4 <- round(3*n/4) for (i in 1:n) { if ((x[i]>=qvalue1) & (x[i]<=qvalue3)){ midm = midm + x[i] myn = myn + 1 } } midm = midm / myn return(midm) } (arm <- mean(x)) sqrtn <- sqrt(length(x)) (armse <- sd(x) / sqrtn) (armose <- arm / armse) (geo <- geomean(x)) (har <- harmean(x)) (qua <- quamean(x)) (win <- winmean(x)) (tri <- trimean(x)) (midr <- midrange(x)) midm <- array(NA,dim=8) for (j in 1:8) midm[j] <- midmean(x,j) midm bitmap(file='test1.png') lb <- win[,1] - 2*win[,2] ub <- win[,1] + 2*win[,2] if ((ylimmin == '') | (ylimmax == '')) plot(win[,1],type='b',main=main, xlab='j', pch=19, ylab='Winsorized Mean(j/n)', ylim=c(min(lb),max(ub))) else plot(win[,1],type='l',main=main, xlab='j', pch=19, ylab='Winsorized Mean(j/n)', ylim=c(ylimmin,ylimmax)) lines(ub,lty=3) lines(lb,lty=3) grid() dev.off() bitmap(file='test2.png') lb <- tri[,1] - 2*tri[,2] ub <- tri[,1] + 2*tri[,2] if ((ylimmin == '') | (ylimmax == '')) plot(tri[,1],type='b',main=main, xlab='j', pch=19, ylab='Trimmed Mean(j/n)', ylim=c(min(lb),max(ub))) else plot(tri[,1],type='l',main=main, xlab='j', pch=19, ylab='Trimmed Mean(j/n)', ylim=c(ylimmin,ylimmax)) lines(ub,lty=3) lines(lb,lty=3) grid() dev.off() load(file='createtable') a<-table.start() a<-table.row.start(a) a<-table.element(a,'Central Tendency - Ungrouped Data',4,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Measure',header=TRUE) a<-table.element(a,'Value',header=TRUE) a<-table.element(a,'S.E.',header=TRUE) a<-table.element(a,'Value/S.E.',header=TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,hyperlink('http://www.xycoon.com/arithmetic_mean.htm', 'Arithmetic Mean', 'click to view the definition of the Arithmetic Mean'),header=TRUE) a<-table.element(a,arm) a<-table.element(a,hyperlink('http://www.xycoon.com/arithmetic_mean_standard_error.htm', armse, 'click to view the definition of the Standard Error of the Arithmetic Mean')) a<-table.element(a,armose) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,hyperlink('http://www.xycoon.com/geometric_mean.htm', 'Geometric Mean', 'click to view the definition of the Geometric Mean'),header=TRUE) a<-table.element(a,geo) a<-table.element(a,'') a<-table.element(a,'') a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,hyperlink('http://www.xycoon.com/harmonic_mean.htm', 'Harmonic Mean', 'click to view the definition of the Harmonic Mean'),header=TRUE) a<-table.element(a,har) a<-table.element(a,'') a<-table.element(a,'') a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,hyperlink('http://www.xycoon.com/quadratic_mean.htm', 'Quadratic Mean', 'click to view the definition of the Quadratic Mean'),header=TRUE) a<-table.element(a,qua) a<-table.element(a,'') a<-table.element(a,'') a<-table.row.end(a) for (j in 1:length(win[,1])) { a<-table.row.start(a) mylabel <- paste('Winsorized Mean (',j) mylabel <- paste(mylabel,'/') mylabel <- paste(mylabel,length(win[,1])) mylabel <- paste(mylabel,')') a<-table.element(a,hyperlink('http://www.xycoon.com/winsorized_mean.htm', mylabel, 'click to view the definition of the Winsorized Mean'),header=TRUE) a<-table.element(a,win[j,1]) a<-table.element(a,win[j,2]) a<-table.element(a,win[j,1]/win[j,2]) a<-table.row.end(a) } for (j in 1:length(tri[,1])) { a<-table.row.start(a) mylabel <- paste('Trimmed Mean (',j) mylabel <- paste(mylabel,'/') mylabel <- paste(mylabel,length(tri[,1])) mylabel <- paste(mylabel,')') a<-table.element(a,hyperlink('http://www.xycoon.com/arithmetic_mean.htm', mylabel, 'click to view the definition of the Trimmed Mean'),header=TRUE) a<-table.element(a,tri[j,1]) a<-table.element(a,tri[j,2]) a<-table.element(a,tri[j,1]/tri[j,2]) a<-table.row.end(a) } a<-table.row.start(a) a<-table.element(a,hyperlink('http://www.xycoon.com/median_1.htm', 'Median', 'click to view the definition of the Median'),header=TRUE) a<-table.element(a,median(x)) a<-table.element(a,'') a<-table.element(a,'') a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,hyperlink('http://www.xycoon.com/midrange.htm', 'Midrange', 'click to view the definition of the Midrange'),header=TRUE) a<-table.element(a,midr) a<-table.element(a,'') a<-table.element(a,'') a<-table.row.end(a) a<-table.row.start(a) mymid <- hyperlink('http://www.xycoon.com/midmean.htm', 'Midmean', 'click to view the definition of the Midmean') mylabel <- paste(mymid,hyperlink('http://www.xycoon.com/method_1.htm','Weighted Average at Xnp',''),sep=' - ') a<-table.element(a,mylabel,header=TRUE) a<-table.element(a,midm[1]) a<-table.element(a,'') a<-table.element(a,'') a<-table.row.end(a) a<-table.row.start(a) mymid <- hyperlink('http://www.xycoon.com/midmean.htm', 'Midmean', 'click to view the definition of the Midmean') mylabel <- paste(mymid,hyperlink('http://www.xycoon.com/method_2.htm','Weighted Average at X(n+1)p',''),sep=' - ') a<-table.element(a,mylabel,header=TRUE) a<-table.element(a,midm[2]) a<-table.element(a,'') a<-table.element(a,'') a<-table.row.end(a) a<-table.row.start(a) mymid <- hyperlink('http://www.xycoon.com/midmean.htm', 'Midmean', 'click to view the definition of the Midmean') mylabel <- paste(mymid,hyperlink('http://www.xycoon.com/method_3.htm','Empirical Distribution Function',''),sep=' - ') a<-table.element(a,mylabel,header=TRUE) a<-table.element(a,midm[3]) a<-table.element(a,'') a<-table.element(a,'') a<-table.row.end(a) a<-table.row.start(a) mymid <- hyperlink('http://www.xycoon.com/midmean.htm', 'Midmean', 'click to view the definition of the Midmean') mylabel <- paste(mymid,hyperlink('http://www.xycoon.com/method_4.htm','Empirical Distribution Function - Averaging',''),sep=' - ') a<-table.element(a,mylabel,header=TRUE) a<-table.element(a,midm[4]) a<-table.element(a,'') a<-table.element(a,'') a<-table.row.end(a) a<-table.row.start(a) mymid <- hyperlink('http://www.xycoon.com/midmean.htm', 'Midmean', 'click to view the definition of the Midmean') mylabel <- paste(mymid,hyperlink('http://www.xycoon.com/method_5.htm','Empirical Distribution Function - Interpolation',''),sep=' - ') a<-table.element(a,mylabel,header=TRUE) a<-table.element(a,midm[5]) a<-table.element(a,'') a<-table.element(a,'') a<-table.row.end(a) a<-table.row.start(a) mymid <- hyperlink('http://www.xycoon.com/midmean.htm', 'Midmean', 'click to view the definition of the Midmean') mylabel <- paste(mymid,hyperlink('http://www.xycoon.com/method_6.htm','Closest Observation',''),sep=' - ') a<-table.element(a,mylabel,header=TRUE) a<-table.element(a,midm[6]) a<-table.element(a,'') a<-table.element(a,'') a<-table.row.end(a) a<-table.row.start(a) mymid <- hyperlink('http://www.xycoon.com/midmean.htm', 'Midmean', 'click to view the definition of the Midmean') mylabel <- paste(mymid,hyperlink('http://www.xycoon.com/method_7.htm','True Basic - Statistics Graphics Toolkit',''),sep=' - ') a<-table.element(a,mylabel,header=TRUE) a<-table.element(a,midm[7]) a<-table.element(a,'') a<-table.element(a,'') a<-table.row.end(a) a<-table.row.start(a) mymid <- hyperlink('http://www.xycoon.com/midmean.htm', 'Midmean', 'click to view the definition of the Midmean') mylabel <- paste(mymid,hyperlink('http://www.xycoon.com/method_8.htm','MS Excel (old versions)',''),sep=' - ') a<-table.element(a,mylabel,header=TRUE) a<-table.element(a,midm[8]) a<-table.element(a,'') a<-table.element(a,'') a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Number of observations',header=TRUE) a<-table.element(a,length(x)) a<-table.element(a,'') a<-table.element(a,'') a<-table.row.end(a) a<-table.end(a) table.save(a,file='mytable.tab')

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