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: Fri, 01 Oct 2010 15:01:39 +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/01/t1285945348rrcdwbpb8wrezxe.htm/, Retrieved Fri, 01 Oct 2010 17:02:30 +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/01/t1285945348rrcdwbpb8wrezxe.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)

User-defined keywords:

Dataseries X:

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426113 383703 232444 70939 226731 947293 611281 158047 33999 37028 3883 506652 39225 180818 198296 217465 275562 1030944 5747 136452 556277 213361 274482 220553 23671 260642 2763544 213923 169861 403064 449594 406167 206893 156187 257102 62156 662883 251422 171328 350089 221588 4813 183186 190379 223166 232669 356725 109215 475834 315955 69487 895 278741 30816 207533 192797 601162 289714 293671 386688 699645 85094 131812 645285 197549 308174 8658 242205 238502 187881 140321 44031 421403 218761 1305923 13755 262517 348821 150034 64016 261596 2597 17126 203077 249148 211655 25264 438555 23989 401915 216886 184641 380155 653641 313906 366936 236302 229641 235577 103898 263906 241171 216548 295281 193299 204386 257567 136813 240755 59609 213511 380531 242344 250407 183613 191835 266793 246542 330563 403556 208108 32404 308532 199297 200156 262875 287069 190157 199746 265777 435956 728 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 'George Udny Yule' @ 72.249.76.132 Central Tendency - Ungrouped Data Measure Value S.E. Value/S.E. Arithmetic Mean 302132.575539568 37389.2320524534 8.0807376603966 Geometric Mean 178547.670868766 Harmonic Mean 42547.0800247063 Quadratic Mean 533105.84140613 Winsorized Mean ( 1 / 46 ) 291793.618705036 30330.6511543456 9.62042051851002 Winsorized Mean ( 2 / 46 ) 270839.158273381 19670.0832728121 13.7690905786725 Winsorized Mean ( 3 / 46 ) 264924.431654676 17589.1343035118 15.0618232303668 Winsorized Mean ( 4 / 46 ) 262544.086330935 16851.4177113202 15.5799405621859 Winsorized Mean ( 5 / 46 ) 253740.597122302 14512.1783049585 17.4846664498055 Winsorized Mean ( 6 / 46 ) 252373.762589928 14141.5816417569 17.8462189720509 Winsorized Mean ( 7 / 46 ) 252078.100719424 14023.6562226079 17.9752053756881 Winsorized Mean ( 8 / 46 ) 251973.870503597 13879.0608503445 18.1549654706891 Winsorized Mean ( 9 / 46 ) 249792.762589928 13435.7082606263 18.5917078388753 Winsorized Mean ( 10 / 46 ) 249156.503597122 13283.6548527441 18.7566228089441 Winsorized Mean ( 11 / 46 ) 246043.820143885 12570.2711844053 19.5734695405082 Winsorized Mean ( 12 / 46 ) 241896.741007194 11821.1431943297 20.4630581857114 Winsorized Mean ( 13 / 46 ) 239163.654676259 11349.8218211558 21.0720184373699 Winsorized Mean ( 14 / 46 ) 236825.856115108 10923.1804668165 21.6810348263091 Winsorized Mean ( 15 / 46 ) 236163.482014388 10771.3823616978 21.9250857581815 Winsorized Mean ( 16 / 46 ) 235852.230215827 10723.0348018178 21.9949141800644 Winsorized Mean ( 17 / 46 ) 236122.151079137 10601.9158324430 22.2716492764994 Winsorized Mean ( 18 / 46 ) 236864.812949640 10168.9591818638 23.2929259242269 Winsorized Mean ( 19 / 46 ) 236569.151079137 10038.6911165205 23.5657366416842 Winsorized Mean ( 20 / 46 ) 234644.54676259 9718.29177751977 24.1446287201797 Winsorized Mean ( 21 / 46 ) 235076.633093525 9563.44744945899 24.580741864883 Winsorized Mean ( 22 / 46 ) 235228.575539568 9524.72572781347 24.6966245812905 Winsorized Mean ( 23 / 46 ) 235353.669064748 9461.14351447211 24.8758164068374 Winsorized Mean ( 24 / 46 ) 235752.345323741 9390.2760455054 25.1060079790287 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 ) 275862.569343066 24755.6708081096 11.1434091801179 Trimmed Mean ( 2 / 46 ) 259459.488888889 16821.7313537567 15.4240656584344 Trimmed Mean ( 3 / 46 ) 253512.969924812 15007.0818229125 16.8928891650176 Trimmed Mean ( 4 / 46 ) 249476.854961832 13889.6033941236 17.9614095437297 Trimmed Mean ( 5 / 46 ) 245956.806201550 12875.8796213457 19.1021361984312 Trimmed Mean ( 6 / 46 ) 244252.952755906 12436.5245421308 19.6399687009388 Trimmed Mean ( 7 / 46 ) 242747.896 12038.4331986583 20.1644094371895 Trimmed Mean ( 8 / 46 ) 241241.62601626 11620.3625784800 20.7602494661416 Trimmed Mean ( 9 / 46 ) 239700.52892562 11181.6555661191 21.4369444227851 Trimmed Mean ( 10 / 46 ) 238390.705882353 10776.1055050804 22.1221577470603 Trimmed Mean ( 11 / 46 ) 237111.692307692 10348.3466804074 22.9130023984041 Trimmed Mean ( 12 / 46 ) 236130.217391304 9991.86143966228 23.6322549924477 Trimmed Mean ( 13 / 46 ) 235539.106194690 9713.58579665493 24.2484198035089 Trimmed Mean ( 14 / 46 ) 235189.963963964 9473.30170744514 24.826609689748 Trimmed Mean ( 15 / 46 ) 235040.954128440 9265.0763873008 25.3684852993333 Trimmed Mean ( 16 / 46 ) 234943.738317757 9052.8037300968 25.9525938397037 Trimmed Mean ( 17 / 46 ) 234868.571428571 8821.3332969392 26.6250648878742 Trimmed Mean ( 18 / 46 ) 234769.058252427 8577.1140939161 27.3715676020857 Trimmed Mean ( 19 / 46 ) 234608.821782178 8358.29796324914 28.0689708375721 Trimmed Mean ( 20 / 46 ) 234463.959595960 8128.04305877813 28.8462989061977 Trimmed Mean ( 21 / 46 ) 234451.020618557 7908.60722454777 29.6450454500809 Trimmed Mean ( 22 / 46 ) 234407.431578947 7679.31723419139 30.5245146710793 Trimmed Mean ( 23 / 46 ) 234351.645161290 7423.06597691139 31.570734503804 Trimmed Mean ( 24 / 46 ) 234285.098901099 7138.00238136346 32.8222220144941 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 2101628 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/01/t1285945348rrcdwbpb8wrezxe/1xe3i1285945297.png (open in new window) http://www.freestatistics.org/blog/date/2010/Oct/01/t1285945348rrcdwbpb8wrezxe/1xe3i1285945297.ps (open in new window) http://www.freestatistics.org/blog/date/2010/Oct/01/t1285945348rrcdwbpb8wrezxe/2qokl1285945297.png (open in new window) http://www.freestatistics.org/blog/date/2010/Oct/01/t1285945348rrcdwbpb8wrezxe/2qokl1285945297.ps (open in new window)

Parameters (Session):

par1 = 100 ; par2 = grey ; par3 = FALSE ; par4 = Unknown ;

Parameters (R input):

par1 = 100 ; par2 = grey ; par3 = FALSE ; par4 = Unknown ;

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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