W6

*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: Tue, 16 Nov 2010 13:47:51 +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/Nov/16/t12899151628jygcrhv83qiy3f.htm/, Retrieved Tue, 16 Nov 2010 14:46:04 +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/Nov/16/t12899151628jygcrhv83qiy3f.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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72 70 90 81 80 40 49 80 90 86 100 40 100 75 83 100 77 55 97 60 40 100 100 59 65 91 100 85 62 68 75 80 80 34 42 94 85 95 90 80 61 65 73 81 40 90 95 67 90 90 90 85 91 100 60 100 90 85 81 80 45 90 93 75 80 85 70 80 96 62 82 50 75 59 78 95 70 80 75 95 70 90 59 16 60 87 80 70 80 100 100 81 49 75 70 91 75 85 84 100 90 87 86 60 100 78 80 90 81 71 92 50 81 90 90 85 80 95 100 79 80 50 70 81 91 100 57 79 95 90 81 70 90 40 60 100 80 81 100 87 100 88 100 93 60 85 100

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 1 seconds R Server 'George Udny Yule' @ 72.249.76.132 Central Tendency - Ungrouped Data Measure Value S.E. Value/S.E. Arithmetic Mean 78.8707482993197 1.39775210287469 56.4268500380789 Geometric Mean 76.5219370332731 Harmonic Mean 73.162338294083 Quadratic Mean 80.6587672525057 Winsorized Mean ( 1 / 49 ) 78.9931972789116 1.36500782106352 57.8701426174728 Winsorized Mean ( 2 / 49 ) 79.0748299319728 1.34768007470774 58.6747785442486 Winsorized Mean ( 3 / 49 ) 79.0748299319728 1.34768007470774 58.6747785442486 Winsorized Mean ( 4 / 49 ) 79.0748299319728 1.34768007470774 58.6747785442486 Winsorized Mean ( 5 / 49 ) 79.0748299319728 1.34768007470774 58.6747785442486 Winsorized Mean ( 6 / 49 ) 79.0748299319728 1.34768007470774 58.6747785442486 Winsorized Mean ( 7 / 49 ) 79.1700680272109 1.32909963441196 59.5666915988872 Winsorized Mean ( 8 / 49 ) 79.3333333333333 1.29867115345828 61.0880846333376 Winsorized Mean ( 9 / 49 ) 79.578231292517 1.25605142868738 63.3558702096135 Winsorized Mean ( 10 / 49 ) 79.578231292517 1.25605142868738 63.3558702096135 Winsorized Mean ( 11 / 49 ) 79.6530612244898 1.24370198176303 64.045134921773 Winsorized Mean ( 12 / 49 ) 79.6530612244898 1.24370198176303 64.045134921773 Winsorized Mean ( 13 / 49 ) 79.6530612244898 1.24370198176303 64.045134921773 Winsorized Mean ( 14 / 49 ) 80.1292517006803 1.16966567861269 68.506115179612 Winsorized Mean ( 15 / 49 ) 80.3333333333333 1.14034023787017 70.446811105581 Winsorized Mean ( 16 / 49 ) 80.5510204081633 1.11060927253711 72.5286762860806 Winsorized Mean ( 17 / 49 ) 80.5510204081633 1.11060927253711 72.5286762860806 Winsorized Mean ( 18 / 49 ) 80.5510204081633 1.11060927253711 72.5286762860806 Winsorized Mean ( 19 / 49 ) 80.2925170068027 1.0489914608457 76.5425839997502 Winsorized Mean ( 20 / 49 ) 80.156462585034 1.03443194701828 77.4883865643193 Winsorized Mean ( 21 / 49 ) 80.0136054421769 1.01974662493487 78.4642022691543 Winsorized Mean ( 22 / 49 ) 80.0136054421769 1.01974662493487 78.4642022691543 Winsorized Mean ( 23 / 49 ) 80.0136054421769 1.01974662493487 78.4642022691543 Winsorized Mean ( 24 / 49 ) 80.0136054421769 1.01974662493487 78.4642022691543 Winsorized Mean ( 25 / 49 ) 80.1836734693878 0.997107942134622 80.4162418942622 Winsorized Mean ( 26 / 49 ) 80.3605442176871 0.974033649563933 82.502841923032 Winsorized Mean ( 27 / 49 ) 80.1768707482993 0.95547608670087 83.913006159201 Winsorized Mean ( 28 / 49 ) 80.5578231292517 0.864079846511964 93.2296054056115 Winsorized Mean ( 29 / 49 ) 80.5578231292517 0.864079846511964 93.2296054056115 Winsorized Mean ( 30 / 49 ) 80.7619047619048 0.794711185498527 101.624220516341 Winsorized Mean ( 31 / 49 ) 80.7619047619048 0.749822663054741 107.708007161166 Winsorized Mean ( 32 / 49 ) 81.1972789115646 0.700562193918884 115.903027049396 Winsorized Mean ( 33 / 49 ) 81.1972789115646 0.700562193918884 115.903027049396 Winsorized Mean ( 34 / 49 ) 81.1972789115646 0.700562193918884 115.903027049396 Winsorized Mean ( 35 / 49 ) 80.9591836734694 0.678275422169976 119.360338038581 Winsorized Mean ( 36 / 49 ) 80.9591836734694 0.678275422169976 119.360338038581 Winsorized Mean ( 37 / 49 ) 80.9591836734694 0.678275422169976 119.360338038581 Winsorized Mean ( 38 / 49 ) 80.9591836734694 0.678275422169976 119.360338038581 Winsorized Mean ( 39 / 49 ) 80.9591836734694 0.678275422169976 119.360338038581 Winsorized Mean ( 40 / 49 ) 81.2312925170068 0.648508753463287 125.258590702439 Winsorized Mean ( 41 / 49 ) 81.5102040816327 0.618749038356078 131.733867899323 Winsorized Mean ( 42 / 49 ) 81.795918367347 0.58908934643652 138.851464318853 Winsorized Mean ( 43 / 49 ) 82.3809523809524 0.53122895806165 155.076170323139 Winsorized Mean ( 44 / 49 ) 82.3809523809524 0.53122895806165 155.076170323139 Winsorized Mean ( 45 / 49 ) 82.3809523809524 0.53122895806165 155.076170323139 Winsorized Mean ( 46 / 49 ) 82.3809523809524 0.53122895806165 155.076170323139 Winsorized Mean ( 47 / 49 ) 82.3809523809524 0.53122895806165 155.076170323139 Winsorized Mean ( 48 / 49 ) 82.3809523809524 0.53122895806165 155.076170323139 Winsorized Mean ( 49 / 49 ) 82.3809523809524 0.53122895806165 155.076170323139 Trimmed Mean ( 1 / 49 ) 79.1586206896552 1.34048641104856 59.0521619892705 Trimmed Mean ( 2 / 49 ) 79.3286713286713 1.31364941973447 60.3880077415985 Trimmed Mean ( 3 / 49 ) 79.3286713286713 1.29422839007786 61.2941826472366 Trimmed Mean ( 4 / 49 ) 79.5971223021583 1.27296829378201 62.5287547937849 Trimmed Mean ( 5 / 49 ) 79.7372262773723 1.2496573198376 63.8072734113498 Trimmed Mean ( 6 / 49 ) 79.7372262773723 1.22404741685163 65.142269147109 Trimmed Mean ( 7 / 49 ) 80.03007518797 1.19584512012870 66.9234450522799 Trimmed Mean ( 8 / 49 ) 80.1679389312977 1.16864259061964 68.5991932647182 Trimmed Mean ( 9 / 49 ) 80.2868217054264 1.14443768765986 70.1539477169758 Trimmed Mean ( 10 / 49 ) 80.3779527559055 1.12514794449226 71.4376746181385 Trimmed Mean ( 11 / 49 ) 80.472 1.10386862238396 72.8999795521038 Trimmed Mean ( 12 / 49 ) 80.472 1.08225890238692 74.3555907209627 Trimmed Mean ( 13 / 49 ) 80.6528925619835 1.05833376133709 76.2074267196084 Trimmed Mean ( 14 / 49 ) 80.7478991596639 1.03177121624480 78.2614380865862 Trimmed Mean ( 15 / 49 ) 80.8034188034188 1.01253849564521 79.802811597725 Trimmed Mean ( 16 / 49 ) 80.8434782608696 0.994998269710735 81.2498681875822 Trimmed Mean ( 17 / 49 ) 80.8672566371681 0.97920092625515 82.584947040886 Trimmed Mean ( 18 / 49 ) 80.8918918918919 0.961618155018315 84.1205955500614 Trimmed Mean ( 19 / 49 ) 80.9174311926605 0.94200937268919 85.8987538114006 Trimmed Mean ( 20 / 49 ) 80.96261682243 0.92715886685513 87.323348475381 Trimmed Mean ( 21 / 49 ) 81.0190476190476 0.912066139758085 88.8302329045315 Trimmed Mean ( 22 / 49 ) 81.0873786407767 0.896628071793122 90.4359133867112 Trimmed Mean ( 23 / 49 ) 81.1584158415842 0.879213495656217 92.3079732539934 Trimmed Mean ( 24 / 49 ) 81.1584158415842 0.859523903398237 94.4225233535845 Trimmed Mean ( 25 / 49 ) 81.3092783505155 0.837193912977003 97.12120106247 Trimmed Mean ( 26 / 49 ) 81.378947368421 0.814644646988113 99.8950249894768 Trimmed Mean ( 27 / 49 ) 81.4408602150538 0.791856395501503 102.848017238625 Trimmed Mean ( 28 / 49 ) 81.5164835164835 0.767846303391442 106.162500433276 Trimmed Mean ( 29 / 49 ) 81.5730337078652 0.751553997899888 108.539152124544 Trimmed Mean ( 30 / 49 ) 81.632183908046 0.732838939783032 111.391711707097 Trimmed Mean ( 31 / 49 ) 81.6823529411765 0.719518155899012 113.523685638088 Trimmed Mean ( 32 / 49 ) 81.7349397590361 0.709095506725132 115.266475367357 Trimmed Mean ( 33 / 49 ) 81.7654320987654 0.702568393256607 116.380743687827 Trimmed Mean ( 34 / 49 ) 81.7974683544304 0.694808435729871 117.726648307753 Trimmed Mean ( 35 / 49 ) 81.8311688311688 0.68561097214626 119.355103922858 Trimmed Mean ( 36 / 49 ) 81.88 0.677025822228343 120.940734181309 Trimmed Mean ( 37 / 49 ) 81.931506849315 0.666760486298889 122.879967443943 Trimmed Mean ( 38 / 49 ) 81.9859154929577 0.654497813153818 125.265377278945 Trimmed Mean ( 39 / 49 ) 82.0434782608696 0.639837862630479 128.225419364173 Trimmed Mean ( 40 / 49 ) 82.1044776119403 0.622266733801166 131.944185912685 Trimmed Mean ( 41 / 49 ) 82.1538461538462 0.605753968061692 135.622464705802 Trimmed Mean ( 42 / 49 ) 82.1904761904762 0.590441503366478 139.201725694851 Trimmed Mean ( 43 / 49 ) 82.2131147540984 0.576457408934992 142.617847354911 Trimmed Mean ( 44 / 49 ) 82.2033898305085 0.567881654874744 144.754438050371 Trimmed Mean ( 45 / 49 ) 82.1929824561404 0.557158133541498 147.521821019990 Trimmed Mean ( 46 / 49 ) 82.1818181818182 0.543768437725041 151.133851250436 Trimmed Mean ( 47 / 49 ) 82.1698113207547 0.52701741010052 155.914794740998 Trimmed Mean ( 48 / 49 ) 82.1698113207547 0.505943148801622 162.409178808691 Trimmed Mean ( 49 / 49 ) 82.1428571428571 0.479157423749955 171.431878274984 Median 81 Midrange 58 Midmean - Weighted Average at Xnp 81.3875 Midmean - Weighted Average at X(n+1)p 81.3875 Midmean - Empirical Distribution Function 81.3875 Midmean - Empirical Distribution Function - Averaging 81.3875 Midmean - Empirical Distribution Function - Interpolation 81.3875 Midmean - Closest Observation 81.3875 Midmean - True Basic - Statistics Graphics Toolkit 81.3875 Midmean - MS Excel (old versions) 81.3875 Number of observations 147

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Nov/16/t12899151628jygcrhv83qiy3f/1cz9m1289915269.png (open in new window) http://www.freestatistics.org/blog/date/2010/Nov/16/t12899151628jygcrhv83qiy3f/1cz9m1289915269.ps (open in new window) http://www.freestatistics.org/blog/date/2010/Nov/16/t12899151628jygcrhv83qiy3f/2nqrp1289915269.png (open in new window) http://www.freestatistics.org/blog/date/2010/Nov/16/t12899151628jygcrhv83qiy3f/2nqrp1289915269.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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