Opgave 5 - Oefening 2 - stap 1 - Robbert Van Hees

*Unverified author*

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

Title produced by software: Central Tendency

Date of computation: Tue, 18 Aug 2009 11:06:21 -0600

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2009/Aug/18/t1250615239mefdy03rhyok3uv.htm/, Retrieved Tue, 18 Aug 2009 19:07:19 +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/2009/Aug/18/t1250615239mefdy03rhyok3uv.htm/}, year = {2009}, } @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 = {2009}, 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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12,11 11,42 11,71 12,04 12,21 12 12,36 12,32 12,96 12,79 13,19 12,34 13,25 12,54 12,77 12,96 13 13,61 13,8 14,16 14,27 14,69 15,01 15,09 15,14 14,2 13,83 14,31 14,04 14,9 14,92 15,36 15,5 15,65 16,18 15,44 15,58 15,24 15,33 16,07 15,82 15,87 15,72 17,07 16,83 17,52 17,76 17,36 17,95 16,71 17,14 16,72 17,26 17,24 17,69 18,13 18,08 18,18 18,18 17,64 17,89 16,82 16,61 16,66 17,02 16,91 17,18 18,06 17,58 17,48 17,54 17,44 17,79 16,79 16,19 16,62 16,39 16,54 17,26 18 17,29 18,16 17,82 17,48 18,31 17,04 17,03 16,97 17,11 17,12 17,69 18,5 18,27 18,45 18,35 18,03 18,49 18,07 17,8 17,88 18,12 18,68 18,8 19,64 19,56 19,3 20,07 19,82 20,29 19,36 18,74 18,87 18,87 18,91 19,31 20,06 20,72 20,42 20,58 20,58 21,18 19,87 19,83 19,48 19,49 19,4 19,89 20,44 20,07 19,75 19,54 19,07

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 16.8674242424242 0.207214310105319 81.4008657696043 Geometric Mean 16.6889329127468 Harmonic Mean 16.4984231063723 Quadratic Mean 17.0333451936150 Winsorized Mean ( 1 / 44 ) 16.8661363636364 0.206258812546358 81.7717127109206 Winsorized Mean ( 2 / 44 ) 16.8684090909091 0.205143744550309 82.2272652177914 Winsorized Mean ( 3 / 44 ) 16.8693181818182 0.204979651026568 82.2975261072705 Winsorized Mean ( 4 / 44 ) 16.8671969696970 0.204023412929235 82.6728497848788 Winsorized Mean ( 5 / 44 ) 16.8702272727273 0.203253676976808 83.0008466447187 Winsorized Mean ( 6 / 44 ) 16.8693181818182 0.201608848045530 83.673501165031 Winsorized Mean ( 7 / 44 ) 16.8587121212121 0.199955188286016 84.3124515333774 Winsorized Mean ( 8 / 44 ) 16.8599242424242 0.199746412684184 84.4066434829106 Winsorized Mean ( 9 / 44 ) 16.8715151515152 0.197580246461809 85.3906979753478 Winsorized Mean ( 10 / 44 ) 16.8760606060606 0.193147372344602 87.3740108457254 Winsorized Mean ( 11 / 44 ) 16.8760606060606 0.192679126700367 87.5863457296251 Winsorized Mean ( 12 / 44 ) 16.8878787878788 0.189776279353392 88.9883543160367 Winsorized Mean ( 13 / 44 ) 16.8868939393939 0.189659871014735 89.0377803646295 Winsorized Mean ( 14 / 44 ) 16.8837121212121 0.188120302648594 89.7495479408762 Winsorized Mean ( 15 / 44 ) 16.8928030303030 0.183311839666835 92.15336587645 Winsorized Mean ( 16 / 44 ) 16.8903787878788 0.181092771197662 93.2692049283567 Winsorized Mean ( 17 / 44 ) 16.9341666666667 0.173856165396669 97.403313986765 Winsorized Mean ( 18 / 44 ) 16.9532575757576 0.169343464799296 100.111673018208 Winsorized Mean ( 19 / 44 ) 16.9561363636364 0.168566353115958 100.590278250679 Winsorized Mean ( 20 / 44 ) 16.9758333333333 0.162740312944172 104.312404383522 Winsorized Mean ( 21 / 44 ) 16.9885606060606 0.159409516920558 106.571809100500 Winsorized Mean ( 22 / 44 ) 16.9868939393939 0.157565811994852 107.808246753102 Winsorized Mean ( 23 / 44 ) 16.9973484848485 0.155730682809951 109.145790528586 Winsorized Mean ( 24 / 44 ) 16.9628030303030 0.150152028532350 112.970854913548 Winsorized Mean ( 25 / 44 ) 17.0044696969697 0.137435254429987 123.727130767835 Winsorized Mean ( 26 / 44 ) 17.0379545454545 0.131368917516408 129.695477952968 Winsorized Mean ( 27 / 44 ) 17.0420454545455 0.130861605802444 130.229530273938 Winsorized Mean ( 28 / 44 ) 17.0462878787879 0.126936146011579 134.290258641010 Winsorized Mean ( 29 / 44 ) 17.0506818181818 0.123410185737686 138.162678520101 Winsorized Mean ( 30 / 44 ) 17.0484090909091 0.120618242658442 141.341879264362 Winsorized Mean ( 31 / 44 ) 17.0296212121212 0.113511314301589 150.025760135902 Winsorized Mean ( 32 / 44 ) 17.0490151515151 0.110664243685754 154.060738895285 Winsorized Mean ( 33 / 44 ) 17.0465151515152 0.108786334758627 156.697210080086 Winsorized Mean ( 34 / 44 ) 17.0413636363636 0.103846158654104 164.102012604297 Winsorized Mean ( 35 / 44 ) 17.0466666666667 0.100962787515748 168.841085771406 Winsorized Mean ( 36 / 44 ) 17.0575757575758 0.0973838995231262 175.158068644859 Winsorized Mean ( 37 / 44 ) 17.0519696969697 0.0927448799767445 183.858879339166 Winsorized Mean ( 38 / 44 ) 17.0721212121212 0.090432048933123 188.783969992171 Winsorized Mean ( 39 / 44 ) 17.0957575757576 0.0865291299024563 197.572281092269 Winsorized Mean ( 40 / 44 ) 17.1018181818182 0.0839765244135355 203.649987913309 Winsorized Mean ( 41 / 44 ) 17.1608333333333 0.0768343449163 223.348469386023 Winsorized Mean ( 42 / 44 ) 17.1831060606061 0.0718591816777234 239.121927907132 Winsorized Mean ( 43 / 44 ) 17.1831060606061 0.0712021401872314 241.328505230626 Winsorized Mean ( 44 / 44 ) 17.2464393939394 0.0639158172725233 269.830538509807 Trimmed Mean ( 1 / 44 ) 16.8761538461538 0.203458070519055 82.946593384573 Trimmed Mean ( 2 / 44 ) 16.886484375 0.200380929979516 84.2719133838048 Trimmed Mean ( 3 / 44 ) 16.8959523809524 0.197634942562144 85.4907141516215 Trimmed Mean ( 4 / 44 ) 16.9054032258065 0.194674824841678 86.8391854958904 Trimmed Mean ( 5 / 44 ) 16.9157377049180 0.191706231520533 88.2378082900568 Trimmed Mean ( 6 / 44 ) 16.92575 0.188627382399153 89.7311396930884 Trimmed Mean ( 7 / 44 ) 16.9362711864407 0.185592605821215 91.2550966753263 Trimmed Mean ( 8 / 44 ) 16.9488793103448 0.182555972873144 92.8420968297894 Trimmed Mean ( 9 / 44 ) 16.9617543859649 0.179218370797212 94.6429448639358 Trimmed Mean ( 10 / 44 ) 16.9735714285714 0.175885599645138 96.5034742060568 Trimmed Mean ( 11 / 44 ) 16.9852727272727 0.172892418308146 98.2418598425751 Trimmed Mean ( 12 / 44 ) 16.9974074074074 0.169616847266441 100.210608093117 Trimmed Mean ( 13 / 44 ) 17.0087735849057 0.166386127028033 102.224710008665 Trimmed Mean ( 14 / 44 ) 17.0206730769231 0.162773425070919 104.566658037129 Trimmed Mean ( 15 / 44 ) 17.0333333333333 0.158920678480785 107.181352962779 Trimmed Mean ( 16 / 44 ) 17.0457 0.155246253065602 109.797819035265 Trimmed Mean ( 17 / 44 ) 17.0587755102041 0.151386763430407 112.683401927977 Trimmed Mean ( 18 / 44 ) 17.0688541666667 0.148012332774421 115.320486115711 Trimmed Mean ( 19 / 44 ) 17.0778723404255 0.144779818654871 117.957547530406 Trimmed Mean ( 20 / 44 ) 17.0870652173913 0.141199940754502 121.013260530327 Trimmed Mean ( 21 / 44 ) 17.0952222222222 0.137879357765483 123.986813539552 Trimmed Mean ( 22 / 44 ) 17.1028409090909 0.134513126936656 127.146259243121 Trimmed Mean ( 23 / 44 ) 17.1109302325581 0.130882684482395 130.734866114851 Trimmed Mean ( 24 / 44 ) 17.1186904761905 0.126945195298400 134.851031076449 Trimmed Mean ( 25 / 44 ) 17.1291463414634 0.123099243313236 139.149079071729 Trimmed Mean ( 26 / 44 ) 17.137375 0.120338886429223 142.40928687735 Trimmed Mean ( 27 / 44 ) 17.1438461538462 0.117918204656102 145.387611724964 Trimmed Mean ( 28 / 44 ) 17.1503947368421 0.115153054638655 148.935647349167 Trimmed Mean ( 29 / 44 ) 17.1570270270270 0.11242468040658 152.609079829974 Trimmed Mean ( 30 / 44 ) 17.16375 0.109680043546076 156.489270473252 Trimmed Mean ( 31 / 44 ) 17.171 0.106805322019056 160.769142168182 Trimmed Mean ( 32 / 44 ) 17.1798529411765 0.104336713619483 164.657792498925 Trimmed Mean ( 33 / 44 ) 17.1880303030303 0.101795585585103 168.848483991094 Trimmed Mean ( 34 / 44 ) 17.196875 0.0989969223006453 173.711208392666 Trimmed Mean ( 35 / 44 ) 17.2066129032258 0.0963273063553463 178.626534409169 Trimmed Mean ( 36 / 44 ) 17.2166666666667 0.0935141509176316 184.107608289480 Trimmed Mean ( 37 / 44 ) 17.2267241379310 0.0906434576484185 190.049283035394 Trimmed Mean ( 38 / 44 ) 17.2378571428571 0.087833118877788 196.256917243735 Trimmed Mean ( 39 / 44 ) 17.2485185185185 0.0847644029749436 203.487760346961 Trimmed Mean ( 40 / 44 ) 17.2584615384615 0.0816655360290734 211.331026252218 Trimmed Mean ( 41 / 44 ) 17.2688 0.078230762778449 220.741807783539 Trimmed Mean ( 42 / 44 ) 17.2760416666667 0.0754124237178777 229.087474118288 Trimmed Mean ( 43 / 44 ) 17.2823913043478 0.0728324029275025 237.289868378375 Trimmed Mean ( 44 / 44 ) 17.2893181818182 0.06959821093123 248.416129530998 Median 17.26 Midrange 16.3 Midmean - Weighted Average at Xnp 17.1602985074627 Midmean - Weighted Average at X(n+1)p 17.1880303030303 Midmean - Empirical Distribution Function 17.1602985074627 Midmean - Empirical Distribution Function - Averaging 17.1880303030303 Midmean - Empirical Distribution Function - Interpolation 17.1880303030303 Midmean - Closest Observation 17.1602985074627 Midmean - True Basic - Statistics Graphics Toolkit 17.1880303030303 Midmean - MS Excel (old versions) 17.1798529411765 Number of observations 132

Charts produced by software:

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Aug/18/t1250615239mefdy03rhyok3uv/1gs0h1250615176.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Aug/18/t1250615239mefdy03rhyok3uv/1gs0h1250615176.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Aug/18/t1250615239mefdy03rhyok3uv/2tk5v1250615176.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Aug/18/t1250615239mefdy03rhyok3uv/2tk5v1250615176.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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