*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: Sat, 18 Dec 2010 12:50:20 +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/18/t12926764800cqjl1ob0q0cboc.htm/, Retrieved Sat, 18 Dec 2010 13:48:02 +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/18/t12926764800cqjl1ob0q0cboc.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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26 23 25 23 19 29 25 21 22 25 24 18 22 15 22 28 20 12 24 20 21 20 21 23 28 24 24 24 23 23 29 24 18 25 21 26 22 22 22 23 30 23 17 23 23 25 24 24 23 21 24 24 28 16 20 29 27 22 28 16 25 24 29 24 23 30 24 21 25 25 22 23 26 23 25 21 25 24 29 22 27 26 22 24 27 24 25 29 22 21 24 24 23 20 27 26 25 21 21 19 21 21 18 22 29 15 17 15 21 21 19 24 20 17 23 24 14 23 24 13 22 16 19 25 25 23 24 26 26 25 18 21 26 23 23 22 20 13 24 15 14 22 10 24 22 24 19 20 13 20 22 24 29 12 20 20 24 22 18

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 3 seconds R Server 'George Udny Yule' @ 72.249.76.132 Central Tendency - Ungrouped Data Measure Value S.E. Value/S.E. Arithmetic Mean 22.3647798742138 0.309782826415634 72.195028152423 Geometric Mean 21.9772656325261 Harmonic Mean 21.5253286772979 Quadratic Mean 22.7012315073365 Winsorized Mean ( 1 / 53 ) 22.3773584905660 0.306846645552585 72.9268473841967 Winsorized Mean ( 2 / 53 ) 22.3647798742138 0.304991432984204 73.3292068415972 Winsorized Mean ( 3 / 53 ) 22.3836477987421 0.301100434059273 74.3394736997815 Winsorized Mean ( 4 / 53 ) 22.3836477987421 0.301100434059273 74.3394736997815 Winsorized Mean ( 5 / 53 ) 22.3836477987421 0.301100434059273 74.3394736997815 Winsorized Mean ( 6 / 53 ) 22.4213836477987 0.293954104966516 76.2751166558901 Winsorized Mean ( 7 / 53 ) 22.4213836477987 0.293954104966516 76.2751166558901 Winsorized Mean ( 8 / 53 ) 22.4716981132075 0.285215581223828 78.7884659624276 Winsorized Mean ( 9 / 53 ) 22.4716981132075 0.285215581223828 78.7884659624276 Winsorized Mean ( 10 / 53 ) 22.4088050314465 0.276629122475921 81.0066735956084 Winsorized Mean ( 11 / 53 ) 22.4088050314465 0.276629122475921 81.0066735956084 Winsorized Mean ( 12 / 53 ) 22.4842767295597 0.264362208478953 85.0510247244732 Winsorized Mean ( 13 / 53 ) 22.4842767295597 0.264362208478953 85.0510247244732 Winsorized Mean ( 14 / 53 ) 22.3962264150943 0.253471851090023 88.3578445447977 Winsorized Mean ( 15 / 53 ) 22.4905660377358 0.239061789774803 94.0784642285245 Winsorized Mean ( 16 / 53 ) 22.4905660377358 0.239061789774803 94.0784642285245 Winsorized Mean ( 17 / 53 ) 22.4905660377358 0.239061789774803 94.0784642285245 Winsorized Mean ( 18 / 53 ) 22.4905660377358 0.210365104032325 106.912057212112 Winsorized Mean ( 19 / 53 ) 22.4905660377358 0.210365104032325 106.912057212112 Winsorized Mean ( 20 / 53 ) 22.4905660377358 0.210365104032325 106.912057212112 Winsorized Mean ( 21 / 53 ) 22.4905660377358 0.210365104032325 106.912057212112 Winsorized Mean ( 22 / 53 ) 22.4905660377358 0.210365104032325 106.912057212112 Winsorized Mean ( 23 / 53 ) 22.6352201257862 0.191869898859495 117.971710311693 Winsorized Mean ( 24 / 53 ) 22.6352201257862 0.191869898859495 117.971710311693 Winsorized Mean ( 25 / 53 ) 22.6352201257862 0.191869898859495 117.971710311693 Winsorized Mean ( 26 / 53 ) 22.4716981132075 0.175257000945585 128.221400525875 Winsorized Mean ( 27 / 53 ) 22.4716981132075 0.175257000945585 128.221400525875 Winsorized Mean ( 28 / 53 ) 22.6477987421384 0.154578343234452 146.513400701856 Winsorized Mean ( 29 / 53 ) 22.6477987421384 0.154578343234452 146.513400701856 Winsorized Mean ( 30 / 53 ) 22.6477987421384 0.154578343234452 146.513400701856 Winsorized Mean ( 31 / 53 ) 22.6477987421384 0.154578343234452 146.513400701856 Winsorized Mean ( 32 / 53 ) 22.6477987421384 0.154578343234452 146.513400701856 Winsorized Mean ( 33 / 53 ) 22.6477987421384 0.154578343234452 146.513400701856 Winsorized Mean ( 34 / 53 ) 22.6477987421384 0.154578343234452 146.513400701856 Winsorized Mean ( 35 / 53 ) 22.6477987421384 0.154578343234452 146.513400701856 Winsorized Mean ( 36 / 53 ) 22.6477987421384 0.154578343234452 146.513400701856 Winsorized Mean ( 37 / 53 ) 22.6477987421384 0.154578343234452 146.513400701856 Winsorized Mean ( 38 / 53 ) 22.6477987421384 0.154578343234452 146.513400701856 Winsorized Mean ( 39 / 53 ) 22.8930817610063 0.129788641840173 176.387405218384 Winsorized Mean ( 40 / 53 ) 22.8930817610063 0.129788641840173 176.387405218384 Winsorized Mean ( 41 / 53 ) 22.6352201257862 0.105731529869525 214.082025992801 Winsorized Mean ( 42 / 53 ) 22.6352201257862 0.105731529869525 214.082025992801 Winsorized Mean ( 43 / 53 ) 22.6352201257862 0.105731529869525 214.082025992801 Winsorized Mean ( 44 / 53 ) 22.6352201257862 0.105731529869525 214.082025992801 Winsorized Mean ( 45 / 53 ) 22.6352201257862 0.105731529869525 214.082025992801 Winsorized Mean ( 46 / 53 ) 22.6352201257862 0.105731529869525 214.082025992801 Winsorized Mean ( 47 / 53 ) 22.6352201257862 0.105731529869525 214.082025992801 Winsorized Mean ( 48 / 53 ) 22.6352201257862 0.105731529869525 214.082025992801 Winsorized Mean ( 49 / 53 ) 22.6352201257862 0.105731529869525 214.082025992801 Winsorized Mean ( 50 / 53 ) 22.6352201257862 0.105731529869525 214.082025992801 Winsorized Mean ( 51 / 53 ) 22.6352201257862 0.105731529869525 214.082025992801 Winsorized Mean ( 52 / 53 ) 22.6352201257862 0.105731529869525 214.082025992801 Winsorized Mean ( 53 / 53 ) 22.6352201257862 0.105731529869525 214.082025992801 Trimmed Mean ( 1 / 53 ) 22.3949044585987 0.299675631951259 74.7304821308968 Trimmed Mean ( 2 / 53 ) 22.4129032258065 0.291879639697418 76.7881694284711 Trimmed Mean ( 3 / 53 ) 22.4379084967320 0.284448129427860 78.8822501377096 Trimmed Mean ( 4 / 53 ) 22.4569536423841 0.277919596951671 80.8037788220069 Trimmed Mean ( 5 / 53 ) 22.4765100671141 0.270803048366643 82.9994721354944 Trimmed Mean ( 6 / 53 ) 22.4965986394558 0.263021544078277 85.5313914238167 Trimmed Mean ( 7 / 53 ) 22.4965986394558 0.256172318639424 87.8182262585557 Trimmed Mean ( 8 / 53 ) 22.5244755244755 0.248670683867807 90.5795374594678 Trimmed Mean ( 9 / 53 ) 22.5319148936170 0.242110191088923 93.0647107099323 Trimmed Mean ( 10 / 53 ) 22.5395683453237 0.234911960395226 95.9490027983344 Trimmed Mean ( 11 / 53 ) 22.5547445255474 0.228384968557827 98.757570027366 Trimmed Mean ( 12 / 53 ) 22.5703703703704 0.221193491343156 102.039034843729 Trimmed Mean ( 13 / 53 ) 22.5789473684211 0.215118518551750 104.960500474018 Trimmed Mean ( 14 / 53 ) 22.5789473684211 0.208416626483283 108.335634010620 Trimmed Mean ( 15 / 53 ) 22.6046511627907 0.202461417468533 111.649179608771 Trimmed Mean ( 16 / 53 ) 22.6141732283465 0.197802969542841 114.326763044114 Trimmed Mean ( 17 / 53 ) 22.624 0.192660155413285 117.429574119611 Trimmed Mean ( 18 / 53 ) 22.6341463414634 0.186962893755954 121.062238002200 Trimmed Mean ( 19 / 53 ) 22.6446280991736 0.184024306744406 123.052375524637 Trimmed Mean ( 20 / 53 ) 22.6554621848740 0.180772438884618 125.325864521496 Trimmed Mean ( 21 / 53 ) 22.6666666666667 0.177167017466026 127.939539711523 Trimmed Mean ( 22 / 53 ) 22.6782608695652 0.173160078620654 130.967028025247 Trimmed Mean ( 23 / 53 ) 22.6902654867257 0.168693783546091 134.505640988995 Trimmed Mean ( 24 / 53 ) 22.6936936936937 0.165784459295636 136.886737092920 Trimmed Mean ( 25 / 53 ) 22.6972477064220 0.162540455852212 139.640605702861 Trimmed Mean ( 26 / 53 ) 22.7009345794393 0.158914804943716 142.849714898995 Trimmed Mean ( 27 / 53 ) 22.7142857142857 0.156492159287190 145.146477738869 Trimmed Mean ( 28 / 53 ) 22.7142857142857 0.153761254137061 147.724378561835 Trimmed Mean ( 29 / 53 ) 22.7281553398058 0.152789954252812 148.754251880977 Trimmed Mean ( 30 / 53 ) 22.7373737373737 0.151666247755651 149.917163995551 Trimmed Mean ( 31 / 53 ) 22.7422680412371 0.150370640678503 151.241412144148 Trimmed Mean ( 32 / 53 ) 22.7473684210526 0.148880421328705 152.789522074430 Trimmed Mean ( 33 / 53 ) 22.752688172043 0.147168946859398 154.602507238028 Trimmed Mean ( 34 / 53 ) 22.7582417582418 0.145204717882716 156.732109604207 Trimmed Mean ( 35 / 53 ) 22.7640449438202 0.142950158022937 159.244629447473 Trimmed Mean ( 36 / 53 ) 22.7701149425287 0.140359973139377 162.226555286657 Trimmed Mean ( 37 / 53 ) 22.7764705882353 0.137378895573831 165.793082649981 Trimmed Mean ( 38 / 53 ) 22.7831325301205 0.133938500160257 170.101445834175 Trimmed Mean ( 39 / 53 ) 22.7901234567901 0.129952566587069 175.372630609189 Trimmed Mean ( 40 / 53 ) 22.7848101265823 0.128242920653769 177.669145481307 Trimmed Mean ( 41 / 53 ) 22.7792207792208 0.126230615781946 180.457178617985 Trimmed Mean ( 42 / 53 ) 22.7866666666667 0.126339073771979 180.361197738340 Trimmed Mean ( 43 / 53 ) 22.7945205479452 0.126357023762755 180.397732307652 Trimmed Mean ( 44 / 53 ) 22.8028169014085 0.126267765544645 180.590959244827 Trimmed Mean ( 45 / 53 ) 22.8115942028986 0.126051185016951 180.970882581000 Trimmed Mean ( 46 / 53 ) 22.8208955223881 0.125682889301595 181.575198097379 Trimmed Mean ( 47 / 53 ) 22.8307692307692 0.125133065269211 182.451929724978 Trimmed Mean ( 48 / 53 ) 22.8412698412698 0.124364949477950 183.663242233051 Trimmed Mean ( 49 / 53 ) 22.8524590163934 0.123332740156092 185.291099406946 Trimmed Mean ( 50 / 53 ) 22.8644067796610 0.121978687426258 187.445915857094 Trimmed Mean ( 51 / 53 ) 22.8771929824561 0.120228936375474 190.280257583007 Trimmed Mean ( 52 / 53 ) 22.8909090909091 0.117987408084435 194.011458193299 Trimmed Mean ( 53 / 53 ) 22.9056603773585 0.115126455820331 198.960874927876 Median 23 Midrange 20 Midmean - Weighted Average at Xnp 23.0957446808511 Midmean - Weighted Average at X(n+1)p 23.0957446808511 Midmean - Empirical Distribution Function 23.0957446808511 Midmean - Empirical Distribution Function - Averaging 23.0957446808511 Midmean - Empirical Distribution Function - Interpolation 23.0957446808511 Midmean - Closest Observation 23.0957446808511 Midmean - True Basic - Statistics Graphics Toolkit 23.0957446808511 Midmean - MS Excel (old versions) 23.0957446808511 Number of observations 159

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Dec/18/t12926764800cqjl1ob0q0cboc/1h5es1292676617.png (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/18/t12926764800cqjl1ob0q0cboc/1h5es1292676617.ps (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/18/t12926764800cqjl1ob0q0cboc/2h5es1292676617.png (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/18/t12926764800cqjl1ob0q0cboc/2h5es1292676617.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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