*Unverified author*

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

Title produced by software: Central Tendency

Date of computation: Mon, 15 Mar 2010 12:44:33 -0600

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2010/Mar/15/t12686788580jml99ntvik5672.htm/, Retrieved Mon, 15 Mar 2010 19:47:40 +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/Mar/15/t12686788580jml99ntvik5672.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:

KDGP1W52

Dataseries X:

» Textbox « » Textfile « » CSV «

182900 191400 189300 192200 187900 193900 189100 193100 194800 200200 211500 202100 200300 199200 204900 207300 200000 197700 202200 200200 208300 215100 210700 208100 209000 211000 210200 205500 211400 211700 209300 207500 203300 207100 206900 228700 226900 226500 227100 228100 226500 225200 217800 221300 215300 231300 227100 237800 230200 233400 231100 237200 243700 239700 248400 241000 254500 242800 268300 253900 262100 264100 261000 269300 260400 263200 279200 272200 269200 289600 283200 284300 283000 289100 289600 289100 287400 279600 289300 295000 299600 293600 294400 290200 301000 307900 298800 310300 293900 305000 311300 317300 296200 306800 291800 301900 314600 321500 329400 311700 309700 306500 307100 301300 292200 310100 316800 284400 284600 301200 287600 314300 298200 299400 301900 265500 287100 274000 290100 263100 245200 258600 259800 269800 274600 274800 271100 257800 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 'Gwilym Jenkins' @ 72.249.127.135 Central Tendency - Ungrouped Data Measure Value S.E. Value/S.E. Arithmetic Mean 255425 3562.12199864643 71.7058540097895 Geometric Mean 252077.682334149 Harmonic Mean 248674.934074592 Quadratic Mean 258658.369370594 Winsorized Mean ( 1 / 44 ) 255403.030303030 3547.42593835348 71.9967195204008 Winsorized Mean ( 2 / 44 ) 255357.575757576 3536.02427022442 72.2160133084632 Winsorized Mean ( 3 / 44 ) 255350.757575758 3533.86093943567 72.2582925451886 Winsorized Mean ( 4 / 44 ) 255347.727272727 3516.19077667376 72.6205554507143 Winsorized Mean ( 5 / 44 ) 255366.666666667 3510.54715416459 72.7426966373955 Winsorized Mean ( 6 / 44 ) 255289.393939394 3490.0912674019 73.1469106048441 Winsorized Mean ( 7 / 44 ) 255310.606060606 3481.73936021133 73.328465932358 Winsorized Mean ( 8 / 44 ) 255304.545454545 3467.04485510902 73.6375086345739 Winsorized Mean ( 9 / 44 ) 255488.636363636 3439.54104089082 74.279862727693 Winsorized Mean ( 10 / 44 ) 255571.969696970 3421.44120300409 74.6971683957545 Winsorized Mean ( 11 / 44 ) 255488.636363636 3395.19391435676 75.250086683794 Winsorized Mean ( 12 / 44 ) 255434.090909091 3384.40447489912 75.4738663193338 Winsorized Mean ( 13 / 44 ) 255404.545454545 3380.96870945853 75.5418246670047 Winsorized Mean ( 14 / 44 ) 255383.333333333 3375.96229316747 75.6475668730653 Winsorized Mean ( 15 / 44 ) 255417.424242424 3331.19122059934 76.6745009001524 Winsorized Mean ( 16 / 44 ) 255053.787878788 3287.91983574582 77.5729946654653 Winsorized Mean ( 17 / 44 ) 255195.454545455 3270.64800971697 78.0259611512086 Winsorized Mean ( 18 / 44 ) 255331.818181818 3235.55729993367 78.9143243382067 Winsorized Mean ( 19 / 44 ) 255403.787878788 3223.75565374291 79.225541669777 Winsorized Mean ( 20 / 44 ) 255585.606060606 3195.60027686687 79.9804681176192 Winsorized Mean ( 21 / 44 ) 255394.696969697 3167.95418894069 80.6181787164974 Winsorized Mean ( 22 / 44 ) 255394.696969697 3160.53187502495 80.8075055302774 Winsorized Mean ( 23 / 44 ) 255325 3145.41428341990 81.1737268905622 Winsorized Mean ( 24 / 44 ) 255325 3121.30890039372 81.800618954373 Winsorized Mean ( 25 / 44 ) 254984.090909091 3077.70459766675 82.84878643077 Winsorized Mean ( 26 / 44 ) 254885.606060606 3037.7772465714 83.9052983059518 Winsorized Mean ( 27 / 44 ) 254824.242424242 3018.37941568484 84.4241917036878 Winsorized Mean ( 28 / 44 ) 254909.090909091 2985.88445217979 85.37138492516 Winsorized Mean ( 29 / 44 ) 254953.030303030 2966.79059734996 85.935633789174 Winsorized Mean ( 30 / 44 ) 254703.030303030 2927.64822838997 86.9991919907336 Winsorized Mean ( 31 / 44 ) 254703.030303030 2907.78982393547 87.593342615908 Winsorized Mean ( 32 / 44 ) 254436.363636364 2876.90703986746 88.4409402564796 Winsorized Mean ( 33 / 44 ) 254411.363636364 2864.02738161103 88.8299341234846 Winsorized Mean ( 34 / 44 ) 255261.363636364 2763.09756040190 92.3823202244205 Winsorized Mean ( 35 / 44 ) 255287.878787879 2754.6587523495 92.6749560431538 Winsorized Mean ( 36 / 44 ) 255833.333333333 2666.58577543284 95.9404102768104 Winsorized Mean ( 37 / 44 ) 256814.393939394 2561.22624273996 100.270093150638 Winsorized Mean ( 38 / 44 ) 257850.757575758 2435.84214751882 105.856924201105 Winsorized Mean ( 39 / 44 ) 258175.757575758 2390.93851890228 107.980926960134 Winsorized Mean ( 40 / 44 ) 258175.757575758 2390.93851890228 107.980926960134 Winsorized Mean ( 41 / 44 ) 257834.090909091 2332.67203284095 110.531650947551 Winsorized Mean ( 42 / 44 ) 257834.090909091 2320.03883304658 111.133523817148 Winsorized Mean ( 43 / 44 ) 257736.363636364 2310.54499488898 111.547866069039 Winsorized Mean ( 44 / 44 ) 257236.363636364 2196.73944887738 117.099168846730 Trimmed Mean ( 1 / 44 ) 255413.846153846 3527.56447082421 72.4051532626331 Trimmed Mean ( 2 / 44 ) 255425 3505.44009166046 72.8653160005967 Trimmed Mean ( 3 / 44 ) 255460.317460317 3487.19054233617 73.2567705604 Trimmed Mean ( 4 / 44 ) 255499.193548387 3467.54377281315 73.6830477964251 Trimmed Mean ( 5 / 44 ) 255540.163934426 3450.79894494034 74.052463795118 Trimmed Mean ( 6 / 44 ) 255578.333333333 3433.24926809596 74.4421139788299 Trimmed Mean ( 7 / 44 ) 255632.203389831 3417.74580033734 74.7955577517202 Trimmed Mean ( 8 / 44 ) 255684.482758621 3401.62246398372 75.1654498598244 Trimmed Mean ( 9 / 44 ) 255739.473684211 3385.71815681506 75.5347792814463 Trimmed Mean ( 10 / 44 ) 255772.321428571 3371.84625752679 75.855273904504 Trimmed Mean ( 11 / 44 ) 255796.363636364 3358.42011967007 76.1656834230415 Trimmed Mean ( 12 / 44 ) 255830.555555556 3346.377504008 76.4499986176527 Trimmed Mean ( 13 / 44 ) 255871.698113208 3333.55877621738 76.7563181842402 Trimmed Mean ( 14 / 44 ) 255917.307692308 3318.84975685335 77.110241933623 Trimmed Mean ( 15 / 44 ) 255966.666666667 3302.1939999381 77.5141214209294 Trimmed Mean ( 16 / 44 ) 256015 3288.05440461024 77.8621544829177 Trimmed Mean ( 17 / 44 ) 256095.918367347 3276.15562886425 78.1696437467862 Trimmed Mean ( 18 / 44 ) 256168.75 3263.69963912579 78.490295776304 Trimmed Mean ( 19 / 44 ) 256234.042553191 3252.475801681 78.7812294931635 Trimmed Mean ( 20 / 44 ) 256296.739130435 3239.92556344767 79.1057492252089 Trimmed Mean ( 21 / 44 ) 256348.888888889 3227.59645673088 79.4240830058835 Trimmed Mean ( 22 / 44 ) 256417.045454545 3215.2548410299 79.750146763611 Trimmed Mean ( 23 / 44 ) 256488.372093023 3200.68025370696 80.1355811146596 Trimmed Mean ( 24 / 44 ) 256567.857142857 3184.32502690559 80.572132233681 Trimmed Mean ( 25 / 44 ) 256651.219512195 3166.85980673897 81.0428105993356 Trimmed Mean ( 26 / 44 ) 256761.25 3149.9876902261 81.5118264736998 Trimmed Mean ( 27 / 44 ) 256883.333333333 3133.32363556927 81.984296297137 Trimmed Mean ( 28 / 44 ) 257015.789473684 3114.54429244223 82.5211540890139 Trimmed Mean ( 29 / 44 ) 257150 3094.78502847203 83.0913933065525 Trimmed Mean ( 30 / 44 ) 257288.888888889 3072.26191158033 83.7457535502052 Trimmed Mean ( 31 / 44 ) 257451.428571429 3048.53135930792 84.4509694103573 Trimmed Mean ( 32 / 44 ) 257623.529411765 3021.18806733748 85.2722583532523 Trimmed Mean ( 33 / 44 ) 257822.727272727 2990.57555830834 86.211741601529 Trimmed Mean ( 34 / 44 ) 258035.9375 2953.96253844043 87.3524745632801 Trimmed Mean ( 35 / 44 ) 258209.677419355 2922.53748116377 88.3511944957278 Trimmed Mean ( 36 / 44 ) 258393.333333333 2883.94431983779 89.5971990707042 Trimmed Mean ( 37 / 44 ) 258555.172413793 2848.22056548964 90.7777914205688 Trimmed Mean ( 38 / 44 ) 258666.071428571 2818.48291695266 91.7749296519564 Trimmed Mean ( 39 / 44 ) 258718.518518519 2798.15262266892 92.4604742509539 Trimmed Mean ( 40 / 44 ) 258753.846153846 2776.71781996712 93.1869433376238 Trimmed Mean ( 41 / 44 ) 258792 2746.87776746395 94.2131474015056 Trimmed Mean ( 42 / 44 ) 258856.25 2715.76678671144 95.3160820975548 Trimmed Mean ( 43 / 44 ) 258926.086956522 2675.29841178559 96.7840020447309 Trimmed Mean ( 44 / 44 ) 259009.090909091 2622.12052515394 98.7784842170382 Median 262150 Midrange 256150 Midmean - Weighted Average at Xnp 257131.343283582 Midmean - Weighted Average at X(n+1)p 257822.727272727 Midmean - Empirical Distribution Function 257131.343283582 Midmean - Empirical Distribution Function - Averaging 257822.727272727 Midmean - Empirical Distribution Function - Interpolation 257822.727272727 Midmean - Closest Observation 257131.343283582 Midmean - True Basic - Statistics Graphics Toolkit 257822.727272727 Midmean - MS Excel (old versions) 257623.529411765 Number of observations 132

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Mar/15/t12686788580jml99ntvik5672/1je3j1268678671.png (open in new window) http://www.freestatistics.org/blog/date/2010/Mar/15/t12686788580jml99ntvik5672/1je3j1268678671.ps (open in new window) http://www.freestatistics.org/blog/date/2010/Mar/15/t12686788580jml99ntvik5672/2npcr1268678671.png (open in new window) http://www.freestatistics.org/blog/date/2010/Mar/15/t12686788580jml99ntvik5672/2npcr1268678671.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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