Gemiddelde - Happiness

*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 12:06:57 +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/t1292674009fs14mea9113y5hf.htm/, Retrieved Sat, 18 Dec 2010 13:06:49 +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/t1292674009fs14mea9113y5hf.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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14 18 11 12 16 18 14 14 15 15 17 19 10 18 14 14 17 14 16 18 14 12 17 9 16 14 11 16 13 17 15 14 16 9 15 17 13 15 16 16 12 11 15 17 13 16 14 11 12 12 15 16 15 12 12 8 13 11 14 15 10 11 12 15 15 14 16 15 15 13 17 13 15 13 15 16 15 16 15 14 15 7 17 13 15 14 13 16 12 14 17 15 17 12 16 11 15 9 16 10 10 15 11 13 14 18 16 14 14 14 14 12 14 15 15 13 17 17 19 15 13 9 15 15 16 11 14 11 15 13 16 14 15 16 16 11 13 16 12 9 13 13 14 19 13

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 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 Central Tendency - Ungrouped Data Measure Value S.E. Value/S.E. Arithmetic Mean 14.0965517241379 0.197281364004389 71.4540463326495 Geometric Mean 13.8786134193073 Harmonic Mean 13.6370746606735 Quadratic Mean 14.2939582124515 Winsorized Mean ( 1 / 48 ) 14.1034482758621 0.195672564953257 72.0767792829372 Winsorized Mean ( 2 / 48 ) 14.1172413793103 0.19290664574551 73.1817264498723 Winsorized Mean ( 3 / 48 ) 14.0965517241379 0.189606402646189 74.3463908781737 Winsorized Mean ( 4 / 48 ) 14.0965517241379 0.189606402646189 74.3463908781737 Winsorized Mean ( 5 / 48 ) 14.0965517241379 0.189606402646189 74.3463908781737 Winsorized Mean ( 6 / 48 ) 14.0965517241379 0.189606402646189 74.3463908781737 Winsorized Mean ( 7 / 48 ) 14.1448275862069 0.181252377536217 78.039404384533 Winsorized Mean ( 8 / 48 ) 14.0896551724138 0.173954799194415 80.996070460045 Winsorized Mean ( 9 / 48 ) 14.0896551724138 0.173954799194415 80.996070460045 Winsorized Mean ( 10 / 48 ) 14.0896551724138 0.173954799194415 80.996070460045 Winsorized Mean ( 11 / 48 ) 14.1655172413793 0.162597979039368 87.1198850383596 Winsorized Mean ( 12 / 48 ) 14.1655172413793 0.162597979039368 87.1198850383596 Winsorized Mean ( 13 / 48 ) 14.1655172413793 0.162597979039368 87.1198850383596 Winsorized Mean ( 14 / 48 ) 14.1655172413793 0.162597979039368 87.1198850383596 Winsorized Mean ( 15 / 48 ) 14.1655172413793 0.162597979039368 87.1198850383596 Winsorized Mean ( 16 / 48 ) 14.1655172413793 0.162597979039368 87.1198850383596 Winsorized Mean ( 17 / 48 ) 14.1655172413793 0.162597979039368 87.1198850383596 Winsorized Mean ( 18 / 48 ) 14.1655172413793 0.162597979039368 87.1198850383596 Winsorized Mean ( 19 / 48 ) 14.1655172413793 0.162597979039368 87.1198850383596 Winsorized Mean ( 20 / 48 ) 14.0275862068966 0.147762633117461 94.933244697566 Winsorized Mean ( 21 / 48 ) 14.0275862068966 0.147762633117461 94.933244697566 Winsorized Mean ( 22 / 48 ) 14.1793103448276 0.12785774149827 110.899114740107 Winsorized Mean ( 23 / 48 ) 14.1793103448276 0.12785774149827 110.899114740107 Winsorized Mean ( 24 / 48 ) 14.1793103448276 0.12785774149827 110.899114740107 Winsorized Mean ( 25 / 48 ) 14.1793103448276 0.12785774149827 110.899114740107 Winsorized Mean ( 26 / 48 ) 14.1793103448276 0.12785774149827 110.899114740107 Winsorized Mean ( 27 / 48 ) 14.1793103448276 0.12785774149827 110.899114740107 Winsorized Mean ( 28 / 48 ) 14.1793103448276 0.12785774149827 110.899114740107 Winsorized Mean ( 29 / 48 ) 14.1793103448276 0.12785774149827 110.899114740107 Winsorized Mean ( 30 / 48 ) 14.1793103448276 0.12785774149827 110.899114740107 Winsorized Mean ( 31 / 48 ) 14.1793103448276 0.12785774149827 110.899114740107 Winsorized Mean ( 32 / 48 ) 14.1793103448276 0.12785774149827 110.899114740107 Winsorized Mean ( 33 / 48 ) 14.1793103448276 0.12785774149827 110.899114740107 Winsorized Mean ( 34 / 48 ) 14.4137931034483 0.102453712049376 140.685904054913 Winsorized Mean ( 35 / 48 ) 14.4137931034483 0.102453712049376 140.685904054913 Winsorized Mean ( 36 / 48 ) 14.4137931034483 0.102453712049376 140.685904054913 Winsorized Mean ( 37 / 48 ) 14.4137931034483 0.102453712049376 140.685904054913 Winsorized Mean ( 38 / 48 ) 14.4137931034483 0.102453712049376 140.685904054913 Winsorized Mean ( 39 / 48 ) 14.4137931034483 0.102453712049376 140.685904054913 Winsorized Mean ( 40 / 48 ) 14.4137931034483 0.102453712049376 140.685904054913 Winsorized Mean ( 41 / 48 ) 14.1310344827586 0.0753377913019491 187.569004062282 Winsorized Mean ( 42 / 48 ) 14.1310344827586 0.0753377913019491 187.569004062282 Winsorized Mean ( 43 / 48 ) 14.1310344827586 0.0753377913019491 187.569004062282 Winsorized Mean ( 44 / 48 ) 14.1310344827586 0.0753377913019491 187.569004062282 Winsorized Mean ( 45 / 48 ) 14.1310344827586 0.0753377913019491 187.569004062282 Winsorized Mean ( 46 / 48 ) 14.1310344827586 0.0753377913019491 187.569004062282 Winsorized Mean ( 47 / 48 ) 14.1310344827586 0.0753377913019491 187.569004062282 Winsorized Mean ( 48 / 48 ) 14.1310344827586 0.0753377913019491 187.569004062282 Trimmed Mean ( 1 / 48 ) 14.1118881118881 0.190667955335589 74.012898953315 Trimmed Mean ( 2 / 48 ) 14.1205673758865 0.185184586383256 76.2513103907187 Trimmed Mean ( 3 / 48 ) 14.1223021582734 0.180783761418802 78.1170944084839 Trimmed Mean ( 4 / 48 ) 14.1313868613139 0.177289815398607 79.7078322268078 Trimmed Mean ( 5 / 48 ) 14.1407407407407 0.1734643474003 81.5195799751776 Trimmed Mean ( 6 / 48 ) 14.1503759398496 0.169265309833271 83.59879501469 Trimmed Mean ( 7 / 48 ) 14.1603053435114 0.164642281639559 86.0064936084387 Trimmed Mean ( 8 / 48 ) 14.1627906976744 0.161295738087815 87.8063541267515 Trimmed Mean ( 9 / 48 ) 14.1732283464567 0.158929713055522 89.1792231544852 Trimmed Mean ( 10 / 48 ) 14.184 0.156322247812940 90.7356451077455 Trimmed Mean ( 11 / 48 ) 14.1951219512195 0.153443975193900 92.5101290766341 Trimmed Mean ( 12 / 48 ) 14.1983471074380 0.151947792030214 93.4422732816987 Trimmed Mean ( 13 / 48 ) 14.2016806722689 0.150288064057288 94.4963977103023 Trimmed Mean ( 14 / 48 ) 14.2051282051282 0.148446350977541 95.6919999150223 Trimmed Mean ( 15 / 48 ) 14.2086956521739 0.146401354325261 97.0530342267626 Trimmed Mean ( 16 / 48 ) 14.2123893805310 0.144128296238074 98.60929291119 Trimmed Mean ( 17 / 48 ) 14.2162162162162 0.141598112471286 100.39834548712 Trimmed Mean ( 18 / 48 ) 14.2201834862385 0.138776385524563 102.468322924591 Trimmed Mean ( 19 / 48 ) 14.2242990654206 0.135621905381665 104.882017586987 Trimmed Mean ( 20 / 48 ) 14.2285714285714 0.132084681778959 107.723100339392 Trimmed Mean ( 21 / 48 ) 14.2427184466019 0.129773059260605 109.750964705242 Trimmed Mean ( 22 / 48 ) 14.2574257425743 0.127157394747289 112.124236037624 Trimmed Mean ( 23 / 48 ) 14.2626262626263 0.126466543230046 112.777861229924 Trimmed Mean ( 24 / 48 ) 14.2680412371134 0.125655894260298 113.548523299328 Trimmed Mean ( 25 / 48 ) 14.2736842105263 0.124709835907357 114.455159905188 Trimmed Mean ( 26 / 48 ) 14.2795698924731 0.123610171021842 115.520994546233 Trimmed Mean ( 27 / 48 ) 14.2857142857143 0.122335548368239 116.774841624228 Trimmed Mean ( 28 / 48 ) 14.2921348314607 0.120860727374969 118.252927496618 Trimmed Mean ( 29 / 48 ) 14.2988505747126 0.119155612618011 120.001485960647 Trimmed Mean ( 30 / 48 ) 14.3058823529412 0.117183962502218 122.080547947595 Trimmed Mean ( 31 / 48 ) 14.3132530120482 0.114901625050015 124.56963081086 Trimmed Mean ( 32 / 48 ) 14.320987654321 0.112254066568021 127.576559960463 Trimmed Mean ( 33 / 48 ) 14.3291139240506 0.109172805183078 131.251678474519 Trimmed Mean ( 34 / 48 ) 14.3376623376623 0.105570075677084 135.811803162082 Trimmed Mean ( 35 / 48 ) 14.3333333333333 0.104551092442551 137.094056106675 Trimmed Mean ( 36 / 48 ) 14.3287671232877 0.103321538803514 138.681317460212 Trimmed Mean ( 37 / 48 ) 14.3239436619718 0.101843466678823 140.646662265968 Trimmed Mean ( 38 / 48 ) 14.3188405797101 0.100069783032691 143.088554264502 Trimmed Mean ( 39 / 48 ) 14.3134328358209 0.0979411651630992 146.143174955955 Trimmed Mean ( 40 / 48 ) 14.3076923076923 0.0953815135972096 150.004877969465 Trimmed Mean ( 41 / 48 ) 14.3015873015873 0.0922909773111485 154.961922803907 Trimmed Mean ( 42 / 48 ) 14.3114754098361 0.0921538971970833 155.299730615072 Trimmed Mean ( 43 / 48 ) 14.3220338983051 0.091868957209251 155.896336840785 Trimmed Mean ( 44 / 48 ) 14.3333333333333 0.0914014161845136 156.81740974777 Trimmed Mean ( 45 / 48 ) 14.3454545454545 0.0907068457399743 158.151839901677 Trimmed Mean ( 46 / 48 ) 14.3584905660377 0.0897276140265529 160.023095697036 Trimmed Mean ( 47 / 48 ) 14.3725490196078 0.0883876679967423 162.608080350503 Trimmed Mean ( 48 / 48 ) 14.3877551020408 0.086584503818761 166.170093578839 Median 14 Midrange 13 Midmean - Weighted Average at Xnp 14.5934065934066 Midmean - Weighted Average at X(n+1)p 14.5934065934066 Midmean - Empirical Distribution Function 14.5934065934066 Midmean - Empirical Distribution Function - Averaging 14.5934065934066 Midmean - Empirical Distribution Function - Interpolation 14.5934065934066 Midmean - Closest Observation 14.5934065934066 Midmean - True Basic - Statistics Graphics Toolkit 14.5934065934066 Midmean - MS Excel (old versions) 14.5934065934066 Number of observations 145

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Dec/18/t1292674009fs14mea9113y5hf/10l4z1292674013.png (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/18/t1292674009fs14mea9113y5hf/10l4z1292674013.ps (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/18/t1292674009fs14mea9113y5hf/20l4z1292674013.png (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/18/t1292674009fs14mea9113y5hf/20l4z1292674013.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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