Measures of central tendency

*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: Mon, 04 Oct 2010 21:05:35 +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/Oct/04/t1286226278bdvtee3sc19z2sc.htm/, Retrieved Mon, 04 Oct 2010 23:04:40 +0200

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/Oct/04/t1286226278bdvtee3sc19z2sc.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:

IsPrivate?

No (this computation is public)

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Dataseries X:

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4813 33999 37028 39047 59609 62156 64016 70939 72844 85094 103898 109215 131812 136452 136813 140321 150034 156187 158047 169861 171328 180818 183186 183613 184641 187881 190157 190379 191835 192797 193299 197549 198296 199297 199746 200156 203077 204386 206771 206893 207533 208108 211655 213361 213511 213923 216046 216548 216886 217465 218761 220553 221588 223166 226731 229641 232444 232669 235577 236302 238502 240755 241171 242205 242344 246542 249148 250407 251422 257102 257567 260642 261596 262517 262875 263906 265777 266793 274482 275562 278741 287069 289714 293671 295281 308174 308532 313906 315955 330563 348821 350089 356725 366936 380155 380531 383703 386688 401422 401915 403064 403556 406167 421403 426113 435956 438555 441437 449594 475834 506652 556277 601162 611281 645285 653641 662883 699645 947293 1030944 1305923 2763544 4202361 137.55 171.26 236.71 239.89 252.64 259.7 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 'Gwilym Jenkins' @ 72.249.127.135 Central Tendency - Ungrouped Data Measure Value S.E. Value/S.E. Arithmetic Mean 299165.389496403 37548.9478942142 7.96734412743693 Geometric Mean 108624.265070935 Harmonic Mean 742.104352826059 Quadratic Mean 532981.586559374 Winsorized Mean ( 1 / 46 ) 288814.537122302 30520.8468696585 9.4628611832334 Winsorized Mean ( 2 / 46 ) 267841.991942446 19941.1758445972 13.4316047373412 Winsorized Mean ( 3 / 46 ) 261908.293453237 17886.5814789557 14.6427249813713 Winsorized Mean ( 4 / 46 ) 259502.040503597 17161.4033984792 15.1212598689099 Winsorized Mean ( 5 / 46 ) 250596.193381295 14870.0901479355 16.8523654455509 Winsorized Mean ( 6 / 46 ) 249009.481726619 14532.5986149574 17.1345461554501 Winsorized Mean ( 7 / 46 ) 248544.699352518 14437.1748819419 17.2156049493726 Winsorized Mean ( 8 / 46 ) 248064.184820144 14339.9628947483 17.2988024195650 Winsorized Mean ( 9 / 46 ) 245865.624676259 13908.8449254636 17.6769261569766 Winsorized Mean ( 10 / 46 ) 245138.781510791 13771.2066579205 17.8008207704733 Winsorized Mean ( 11 / 46 ) 241591.816474820 13128.7671605911 18.4017138486554 Winsorized Mean ( 12 / 46 ) 237307.984820144 12419.0304467469 19.1084147701969 Winsorized Mean ( 13 / 46 ) 234430.220647482 11981.2158896144 19.5664799639152 Winsorized Mean ( 14 / 46 ) 231812.982086331 11604.7034101108 19.9757782593874 Winsorized Mean ( 15 / 46 ) 230939.376690647 11485.4294759058 20.1071607444121 Winsorized Mean ( 16 / 46 ) 231074.575539568 11373.9117555152 20.3161920460232 Winsorized Mean ( 17 / 46 ) 234326.223021583 10834.6383029223 21.6275076721649 Winsorized Mean ( 18 / 46 ) 233443.834532374 10612.2463517601 21.9975890866552 Winsorized Mean ( 19 / 46 ) 233076 10491.0189370035 22.2167171177153 Winsorized Mean ( 20 / 46 ) 233842.330935252 9820.24155463958 23.8122789173931 Winsorized Mean ( 21 / 46 ) 233832.661870504 9720.84767191595 24.0547604244493 Winsorized Mean ( 22 / 46 ) 234049.179856115 9673.40602550719 24.195115891855 Winsorized Mean ( 23 / 46 ) 235004.589928058 9504.66413935938 24.725186127818 Winsorized Mean ( 24 / 46 ) 235248.388489209 9452.7799413888 24.886688354944 Winsorized Mean ( 25 / 46 ) 234801.625899281 8846.71431740454 26.5411109113521 Winsorized Mean ( 26 / 46 ) 237760.575539568 8356.54283410624 28.4520261858979 Winsorized Mean ( 27 / 46 ) 238177.230215827 8159.51143426677 29.1901337640849 Winsorized Mean ( 28 / 46 ) 242653.402877698 7649.45320675889 31.7216664144431 Winsorized Mean ( 29 / 46 ) 240863.539568345 7192.81893940003 33.4866679667091 Winsorized Mean ( 30 / 46 ) 238737.64028777 6908.15434555398 34.5588167759192 Winsorized Mean ( 31 / 46 ) 238040.028776978 6642.57131015258 35.8355247783573 Winsorized Mean ( 32 / 46 ) 239984.201438849 6373.03753386952 37.6561726121104 Winsorized Mean ( 33 / 46 ) 237110.352517986 5696.74068515798 41.6221073807593 Winsorized Mean ( 34 / 46 ) 233992.136690647 5233.90093554979 44.7070243728387 Winsorized Mean ( 35 / 46 ) 236450.949640288 4870.85231158794 48.5440605698025 Winsorized Mean ( 36 / 46 ) 235439.064748201 4674.07453764535 50.3712687617533 Winsorized Mean ( 37 / 46 ) 237869.884892086 4419.28060720207 53.8254765955417 Winsorized Mean ( 38 / 46 ) 234992.54676259 3960.28658777181 59.337257936882 Winsorized Mean ( 39 / 46 ) 234660.625899281 3899.23911433519 60.1811325282855 Winsorized Mean ( 40 / 46 ) 233817.748201439 3747.14113168070 62.3989703042129 Winsorized Mean ( 41 / 46 ) 233993.251798561 3572.82752408348 65.4924566666807 Winsorized Mean ( 42 / 46 ) 232164.589928058 3241.73432322201 71.6174019150668 Winsorized Mean ( 43 / 46 ) 231249.834532374 3133.67131299425 73.7951787009253 Winsorized Mean ( 44 / 46 ) 231368.856115108 3055.28718941051 75.7273675996883 Winsorized Mean ( 45 / 46 ) 229191.050359712 2776.23598654351 82.5545996343997 Winsorized Mean ( 46 / 46 ) 229020.949640288 2727.54481858533 83.9659711839572 Trimmed Mean ( 1 / 46 ) 272858.534233577 24979.5008916898 10.9232980841643 Trimmed Mean ( 2 / 46 ) 256429.760888889 17135.2684731460 14.9650273230769 Trimmed Mean ( 3 / 46 ) 250466.226616541 15355.700115423 16.3109610590127 Trimmed Mean ( 4 / 46 ) 246419.286946565 14265.5502499102 17.2737316563108 Trimmed Mean ( 5 / 46 ) 242895.056821705 13280.4827676504 18.289625540825 Trimmed Mean ( 6 / 46 ) 241209.296220472 12855.0734870728 18.7637430826853 Trimmed Mean ( 7 / 46 ) 239763.66184 12464.7656604106 19.2353124296203 Trimmed Mean ( 8 / 46 ) 238346.049512195 12051.1752859746 19.7778261336541 Trimmed Mean ( 9 / 46 ) 236950.573471074 11608.9097377555 20.4110962031554 Trimmed Mean ( 10 / 46 ) 235793.531344538 11197.1479611454 21.0583563031186 Trimmed Mean ( 11 / 46 ) 234683.283675214 10760.3893016025 21.8099250033885 Trimmed Mean ( 12 / 46 ) 233924.164260870 10381.9665735551 22.5317778287517 Trimmed Mean ( 13 / 46 ) 233577.297699115 10072.9526899746 23.1885629654143 Trimmed Mean ( 14 / 46 ) 233495.138108108 9793.49107420719 23.8418697008932 Trimmed Mean ( 15 / 46 ) 233648.362018349 9534.6800924591 24.5051076441610 Trimmed Mean ( 16 / 46 ) 233882.971962617 9261.06661953612 25.254431435494 Trimmed Mean ( 17 / 46 ) 234115.333333333 8968.8307404814 26.1032168080326 Trimmed Mean ( 18 / 46 ) 234098.592233010 8713.22053876386 26.8670569270615 Trimmed Mean ( 19 / 46 ) 234148.653465347 8454.36874991222 27.6955808756009 Trimmed Mean ( 20 / 46 ) 234227.919191919 8177.46422612714 28.6430992193836 Trimmed Mean ( 21 / 46 ) 234255.546391753 7951.25012257929 29.4614737029255 Trimmed Mean ( 22 / 46 ) 234285.010526316 7707.16721720014 30.398329752527 Trimmed Mean ( 23 / 46 ) 234301.032258065 7434.99098122805 31.5132907154333 Trimmed Mean ( 24 / 46 ) 234254.307692308 7145.66825097824 32.7827012764325 Trimmed Mean ( 25 / 46 ) 234189.617977528 6819.08532491074 34.3432596629950 Trimmed Mean ( 26 / 46 ) 234150.505747126 6526.5482666284 35.87662209508 Trimmed Mean ( 27 / 46 ) 233923.447058824 6255.14881556815 37.3969435349999 Trimmed Mean ( 28 / 46 ) 233659.602409639 5966.82746012148 39.1597719175344 Trimmed Mean ( 29 / 46 ) 233108.395061728 5698.9247407312 40.9039258573924 Trimmed Mean ( 30 / 46 ) 232637.873417722 5452.36965731674 42.667296613966 Trimmed Mean ( 31 / 46 ) 232270.831168831 5205.87115220075 44.6170918138533 Trimmed Mean ( 32 / 46 ) 231925.92 4954.76456661102 46.8086660591087 Trimmed Mean ( 33 / 46 ) 231446.424657534 4695.10375089879 49.2952737441059 Trimmed Mean ( 34 / 46 ) 231110.408450704 4493.84034197321 51.4282642158189 Trimmed Mean ( 35 / 46 ) 230939.666666667 4326.51496056991 53.3777575650047 Trimmed Mean ( 36 / 46 ) 230612.985074627 4178.48950061872 55.1905144288335 Trimmed Mean ( 37 / 46 ) 230326.307692308 4031.59691625481 57.1302916627566 Trimmed Mean ( 38 / 46 ) 229876.476190476 3889.52717335762 59.1013935485727 Trimmed Mean ( 39 / 46 ) 229569.68852459 3792.0005445416 60.5405209804214 Trimmed Mean ( 40 / 46 ) 229262.152542373 3682.35981141454 62.2595738286379 Trimmed Mean ( 41 / 46 ) 228984.421052632 3573.06812340646 64.086217543013 Trimmed Mean ( 42 / 46 ) 228675.672727273 3466.19672621418 65.9730796575517 Trimmed Mean ( 43 / 46 ) 228457.811320755 3390.97147800264 67.3723777397625 Trimmed Mean ( 44 / 46 ) 228280.843137255 3314.84984788417 68.8661187121233 Trimmed Mean ( 45 / 46 ) 228081.755102041 3231.11972211097 70.5890758368525 Trimmed Mean ( 46 / 46 ) 228008.851063830 3176.24249930817 71.7857188528563 Median 223166 Midrange 2101184.975 Midmean - Weighted Average at Xnp 229898.342857143 Midmean - Weighted Average at X(n+1)p 231110.408450704 Midmean - Empirical Distribution Function 231110.408450704 Midmean - Empirical Distribution Function - Averaging 231110.408450704 Midmean - Empirical Distribution Function - Interpolation 230939.666666667 Midmean - Closest Observation 229898.342857143 Midmean - True Basic - Statistics Graphics Toolkit 231110.408450704 Midmean - MS Excel (old versions) 231110.408450704 Number of observations 139

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Oct/04/t1286226278bdvtee3sc19z2sc/1wxip1286226333.png (open in new window) http://www.freestatistics.org/blog/date/2010/Oct/04/t1286226278bdvtee3sc19z2sc/1wxip1286226333.ps (open in new window) http://www.freestatistics.org/blog/date/2010/Oct/04/t1286226278bdvtee3sc19z2sc/26ozs1286226333.png (open in new window) http://www.freestatistics.org/blog/date/2010/Oct/04/t1286226278bdvtee3sc19z2sc/26ozs1286226333.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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