Maatstaven voor centrale tendentie

*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: Thu, 30 Sep 2010 12:22:26 +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/Sep/30/t12858494452my3bwktq3td1t9.htm/, Retrieved Thu, 30 Sep 2010 14:24:08 +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/2010/Sep/30/t12858494452my3bwktq3td1t9.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:

Gebaseerd op de gegevens zonder outliers

Dataseries X:

» Textbox « » Textfile « » CSV «

426,113 383,703 232,444 70,939 226,731 611,281 158,047 33,999 37,028 388,3 506,652 392,25 180,818 198,296 217,465 275,562 57,47 136,452 556,277 213,361 274,482 220,553 236,71 260,642 213,923 169,861 403,064 449,594 406,167 206,893 156,187 257,102 62,156 251,422 171,328 350,089 221,588 4,813 183,186 190,379 223,166 232,669 356,725 109,215 475,834 315,955 8,95 278,741 308,16 207,533 192,797 601,162 289,714 293,671 386,688 85,094 131,812 197,549 308,174 86,58 242,205 238,502 187,881 140,321 440,31 421,403 218,761 137,55 262,517 348,821 150,034 64,016 261,596 259,7 171,26 203,077 249,148 211,655 252,64 438,555 239,89 401,915 216,886 184,641 380,155 313,906 366,936 236,302 229,641 235,577 103,898 263,906 241,171 216,548 295,281 193,299 204,386 257,567 136,813 240,755 59,609 213,511 380,531 242,344 250,407 183,613 191,835 266,793 246,542 330,563 403,556 208,108 324,04 308,532 199,297 200,156 262,875 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 1 seconds R Server 'Gwilym Jenkins' @ 72.249.127.135 Central Tendency - Ungrouped Data Measure Value S.E. Value/S.E. Arithmetic Mean 253.705310077519 11.0655854156507 22.9274187083396 Geometric Mean 214.254357438035 Harmonic Mean 129.070236045895 Quadratic Mean 282.912748877081 Winsorized Mean ( 1 / 43 ) 252.61196124031 10.7121356136886 23.5818486948118 Winsorized Mean ( 2 / 43 ) 252.843434108527 10.6056619871436 23.8404198073660 Winsorized Mean ( 3 / 43 ) 251.87003875969 10.3401370567336 24.3584816504603 Winsorized Mean ( 4 / 43 ) 250.39388372093 9.99849573350173 25.0431555300805 Winsorized Mean ( 5 / 43 ) 249.913457364341 9.65492683219579 25.8845521781654 Winsorized Mean ( 6 / 43 ) 248.792480620155 9.42614694589744 26.393868252652 Winsorized Mean ( 7 / 43 ) 248.488062015504 9.33194397849273 26.6276847126593 Winsorized Mean ( 8 / 43 ) 248.533519379845 9.30273680468188 26.7161723047741 Winsorized Mean ( 9 / 43 ) 248.89407751938 9.2091405737598 27.0268518029326 Winsorized Mean ( 10 / 43 ) 248.840279069767 9.15460895784989 27.1819670523875 Winsorized Mean ( 11 / 43 ) 249.045527131783 8.86817957668025 28.0830496246008 Winsorized Mean ( 12 / 43 ) 248.745620155039 8.78039438034222 28.3296637235267 Winsorized Mean ( 13 / 43 ) 248.955434108527 8.30358733005351 29.9816722836734 Winsorized Mean ( 14 / 43 ) 249.249108527132 8.18380733214324 30.4563754266508 Winsorized Mean ( 15 / 43 ) 251.819457364341 7.84219715510894 32.1108297054594 Winsorized Mean ( 16 / 43 ) 252.252449612403 7.75272939437294 32.5372442117601 Winsorized Mean ( 17 / 43 ) 252.235054263566 7.73738894530507 32.5995056015141 Winsorized Mean ( 18 / 43 ) 251.05807751938 7.53524352688895 33.3178452194011 Winsorized Mean ( 19 / 43 ) 250.884426356589 7.40264245949297 33.8911986806632 Winsorized Mean ( 20 / 43 ) 252.140395348837 7.194865457522 35.0444906631621 Winsorized Mean ( 21 / 43 ) 252.65611627907 7.01454716231031 36.0188776884430 Winsorized Mean ( 22 / 43 ) 252.432364341085 6.90186065491555 36.5745379343904 Winsorized Mean ( 23 / 43 ) 254.471697674419 6.67511795766493 38.1224270924250 Winsorized Mean ( 24 / 43 ) 252.272627906977 6.29304984217845 40.0874987857475 Winsorized Mean ( 25 / 43 ) 250.306930232558 6.01399136915321 41.6207664541099 Winsorized Mean ( 26 / 43 ) 250.88215503876 5.63846873210988 44.494731984597 Winsorized Mean ( 27 / 43 ) 251.112387596899 5.5542535670687 45.2108252827618 Winsorized Mean ( 28 / 43 ) 247.242093023256 5.01494419925465 49.3010656150476 Winsorized Mean ( 29 / 43 ) 246.006782945736 4.80369267939134 51.2120152900596 Winsorized Mean ( 30 / 43 ) 244.88003875969 4.49314994385083 54.5007493228274 Winsorized Mean ( 31 / 43 ) 244.934589147287 4.37858853647835 55.9391655796653 Winsorized Mean ( 32 / 43 ) 243.656573643411 4.21088710703225 57.8634780392237 Winsorized Mean ( 33 / 43 ) 243.937457364341 4.16323787512728 58.5932067013786 Winsorized Mean ( 34 / 43 ) 244.187317829457 4.13809723225635 59.0095650546885 Winsorized Mean ( 35 / 43 ) 240.829217054264 3.71290887898211 64.8626790755734 Winsorized Mean ( 36 / 43 ) 241.56596124031 3.54448645425124 68.1525982277565 Winsorized Mean ( 37 / 43 ) 240.645263565891 3.39436710070604 70.8954737146245 Winsorized Mean ( 38 / 43 ) 240.160984496124 3.2780808718142 73.2626783436282 Winsorized Mean ( 39 / 43 ) 237.77896124031 2.98893539582849 79.5530614586606 Winsorized Mean ( 40 / 43 ) 236.920356589147 2.87165659979668 82.5030251200377 Winsorized Mean ( 41 / 43 ) 237.505480620155 2.74358672504915 86.5675134129032 Winsorized Mean ( 42 / 43 ) 235.428271317829 2.44390574251811 96.3327951737014 Winsorized Mean ( 43 / 43 ) 235.884604651163 2.33173213550494 101.162822718520 Trimmed Mean ( 1 / 43 ) 251.706393700787 10.3272014415120 24.3731465030796 Trimmed Mean ( 2 / 43 ) 250.771848 9.89720390576375 25.3376459036031 Trimmed Mean ( 3 / 43 ) 249.685528455285 9.47927206392797 26.3401584817285 Trimmed Mean ( 4 / 43 ) 248.909214876033 9.12528970631251 27.2768561751905 Trimmed Mean ( 5 / 43 ) 248.506857142857 8.84515582932859 28.0952491892639 Trimmed Mean ( 6 / 43 ) 248.196683760684 8.62836244257356 28.7652130300005 Trimmed Mean ( 7 / 43 ) 248.085295652174 8.44188325417004 29.3874350287452 Trimmed Mean ( 8 / 43 ) 248.019610619469 8.25447733408087 30.0466765588479 Trimmed Mean ( 9 / 43 ) 247.944954954955 8.0513334990905 30.7955141819629 Trimmed Mean ( 10 / 43 ) 247.820146788991 7.84142278657664 31.6039771778691 Trimmed Mean ( 11 / 43 ) 247.697158878505 7.61569393225958 32.5245684873542 Trimmed Mean ( 12 / 43 ) 247.546561904762 7.40970023911241 33.4084448650267 Trimmed Mean ( 13 / 43 ) 247.421417475728 7.19192464115654 34.402671026311 Trimmed Mean ( 14 / 43 ) 247.270702970297 7.019129502367 35.2281152366418 Trimmed Mean ( 15 / 43 ) 247.086565656566 6.84155861710688 36.1155373336628 Trimmed Mean ( 16 / 43 ) 246.666948453608 6.68773395817706 36.8834869921836 Trimmed Mean ( 17 / 43 ) 246.192915789474 6.52513337958889 37.7299438138052 Trimmed Mean ( 18 / 43 ) 245.699913978495 6.34202459102744 38.741558070605 Trimmed Mean ( 19 / 43 ) 245.277934065934 6.16167703300393 39.8070091554858 Trimmed Mean ( 20 / 43 ) 244.850235955056 5.97338486711597 40.9901992592138 Trimmed Mean ( 21 / 43 ) 244.309758620690 5.78417250799422 42.2376335220004 Trimmed Mean ( 22 / 43 ) 243.706576470588 5.58980220831799 43.5984257382018 Trimmed Mean ( 23 / 43 ) 243.090132530120 5.38013699938663 45.1828889409014 Trimmed Mean ( 24 / 43 ) 242.302037037037 5.16406784913268 46.9207694623401 Trimmed Mean ( 25 / 43 ) 241.623658227848 4.96970823384345 48.6192844445885 Trimmed Mean ( 26 / 43 ) 241.041766233766 4.78472315916055 50.3773694351118 Trimmed Mean ( 27 / 43 ) 240.390786666667 4.61925505406663 52.0410290951644 Trimmed Mean ( 28 / 43 ) 239.689068493151 4.43449224751558 54.0510739707429 Trimmed Mean ( 29 / 43 ) 239.198957746479 4.30100181294362 55.6147074913159 Trimmed Mean ( 30 / 43 ) 238.760072463768 4.17412615663343 57.2000134888917 Trimmed Mean ( 31 / 43 ) 238.367298507463 4.06839389803273 58.5900245850642 Trimmed Mean ( 32 / 43 ) 237.946861538462 3.95741663931818 60.1268158561787 Trimmed Mean ( 33 / 43 ) 237.581507936508 3.8500103601295 61.7093165246747 Trimmed Mean ( 34 / 43 ) 237.174196721311 3.7259551026116 63.6546040383232 Trimmed Mean ( 35 / 43 ) 236.723203389831 3.57725596186567 66.1745220116624 Trimmed Mean ( 36 / 43 ) 236.457701754386 3.47168182773286 68.1104183757535 Trimmed Mean ( 37 / 43 ) 236.124890909091 3.36742555439999 70.1203002396185 Trimmed Mean ( 38 / 43 ) 235.827528301887 3.2645217516148 72.2395334585332 Trimmed Mean ( 39 / 43 ) 235.539078431373 3.15647871302173 74.6208353820604 Trimmed Mean ( 40 / 43 ) 235.387877551020 3.07626224323340 76.517493938881 Trimmed Mean ( 41 / 43 ) 235.282723404255 2.99568969072711 78.5404189668081 Trimmed Mean ( 42 / 43 ) 235.127311111111 2.91523757592119 80.6545967481957 Trimmed Mean ( 43 / 43 ) 235.105813953488 2.87035137323297 81.908374056895 Median 236.302 Midrange 380.6365 Midmean - Weighted Average at Xnp 236.84396875 Midmean - Weighted Average at X(n+1)p 237.946861538462 Midmean - Empirical Distribution Function 237.946861538462 Midmean - Empirical Distribution Function - Averaging 237.946861538462 Midmean - Empirical Distribution Function - Interpolation 237.946861538462 Midmean - Closest Observation 237.222772727273 Midmean - True Basic - Statistics Graphics Toolkit 237.946861538462 Midmean - MS Excel (old versions) 237.946861538462 Number of observations 129

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Sep/30/t12858494452my3bwktq3td1t9/10cwz1285849344.png (open in new window) http://www.freestatistics.org/blog/date/2010/Sep/30/t12858494452my3bwktq3td1t9/10cwz1285849344.ps (open in new window) http://www.freestatistics.org/blog/date/2010/Sep/30/t12858494452my3bwktq3td1t9/2606w1285849344.png (open in new window) http://www.freestatistics.org/blog/date/2010/Sep/30/t12858494452my3bwktq3td1t9/2606w1285849344.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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