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 11:10:23 +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/t1285845146zc7uo2en8ggfx1h.htm/, Retrieved Thu, 30 Sep 2010 13:12:28 +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/t1285845146zc7uo2en8ggfx1h.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 alle waarden tussen 0 en 700

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 62,156 662,883 251,422 171,328 350,089 221,588 4,813 183,186 190,379 223,166 232,669 356,725 109,215 475,834 315,955 694,87 8,95 278,741 308,16 207,533 192,797 601,162 289,714 293,671 386,688 699,645 85,094 131,812 645,285 197,549 308,174 86,58 242,205 238,502 187,881 140,321 440,31 421,403 218,761 137,55 262,517 348,821 150,034 64,016 261,596 259,7 171,26 203,077 249,148 211,655 252,64 438,555 239,89 401,915 216,886 184,641 380,155 653,641 313,906 366,936 236,302 229,641 235,577 103,898 263,906 241,171 216,548 295,281 193,299 204,386 257,567 136,813 240,755 59,609 213,511 380,531 242,344 250,407 183,613 191,835 266,793 246,542 330,563 403,556 208,108 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 265.62292481203 12.2264875206998 21.7252031184199 Geometric Mean 221.537366938462 Harmonic Mean 132.260603087443 Quadratic Mean 300.479320090556 Winsorized Mean ( 1 / 44 ) 265.618127819549 12.2118899597752 21.7507796659215 Winsorized Mean ( 2 / 44 ) 265.513796992481 12.0301690717093 22.0706621336582 Winsorized Mean ( 3 / 44 ) 265.373654135338 11.9685503083683 22.1725812481895 Winsorized Mean ( 4 / 44 ) 265.183067669173 11.8984985782746 22.287103362215 Winsorized Mean ( 5 / 44 ) 264.597315789474 11.5005416309807 23.0073786330801 Winsorized Mean ( 6 / 44 ) 264.237315789474 11.3840820918148 23.2111217802497 Winsorized Mean ( 7 / 44 ) 262.009 10.8577285210551 24.1311061970206 Winsorized Mean ( 8 / 44 ) 259.135917293233 10.2617711012769 25.2525528717931 Winsorized Mean ( 9 / 44 ) 257.518962406015 9.82800845033424 26.2025580978471 Winsorized Mean ( 10 / 44 ) 255.689263157895 9.4882907818726 26.9478738622123 Winsorized Mean ( 11 / 44 ) 256.027781954887 9.23978441719566 27.7092809090229 Winsorized Mean ( 12 / 44 ) 256.060172932331 9.20560096671633 27.8156932782704 Winsorized Mean ( 13 / 44 ) 257.581368421053 8.95121712142774 28.7761278636003 Winsorized Mean ( 14 / 44 ) 257.867473684210 8.83731824027784 29.1793807434622 Winsorized Mean ( 15 / 44 ) 259.305894736842 8.358592092498 31.022676052056 Winsorized Mean ( 16 / 44 ) 259.297473684211 8.20948015815513 31.5851270347039 Winsorized Mean ( 17 / 44 ) 257.396157894737 7.91984616154783 32.5001461700655 Winsorized Mean ( 18 / 44 ) 257.142533834586 7.85826054542537 32.7225767519607 Winsorized Mean ( 19 / 44 ) 257.468105263158 7.80300010190756 32.9960402281958 Winsorized Mean ( 20 / 44 ) 258.75592481203 7.61640111503859 33.97351595639 Winsorized Mean ( 21 / 44 ) 259.649609022556 7.50198972654841 34.6107657417466 Winsorized Mean ( 22 / 44 ) 258.440105263158 7.25515181514614 35.6215985341104 Winsorized Mean ( 23 / 44 ) 259.800045112782 6.95226248279126 37.3691364150674 Winsorized Mean ( 24 / 44 ) 259.761609022556 6.88692991126946 37.7180561395716 Winsorized Mean ( 25 / 44 ) 259.213300751880 6.80764520942789 38.0767934840223 Winsorized Mean ( 26 / 44 ) 260.448398496241 6.54528652526078 39.7917489923581 Winsorized Mean ( 27 / 44 ) 260.852789473684 6.49072401256921 40.1885504557806 Winsorized Mean ( 28 / 44 ) 258.159736842105 6.10059620803715 42.3171322996261 Winsorized Mean ( 29 / 44 ) 256.157428571429 5.78257877114591 44.2981304205678 Winsorized Mean ( 30 / 44 ) 255.391413533835 5.51853556201952 46.2788380474572 Winsorized Mean ( 31 / 44 ) 255.626360902256 5.43130821699308 47.0653387157206 Winsorized Mean ( 32 / 44 ) 251.286872180451 4.8691086433784 51.6083929493299 Winsorized Mean ( 33 / 44 ) 250.029646616541 4.63710750394016 53.9193120720386 Winsorized Mean ( 34 / 44 ) 248.208729323308 4.36709279072773 56.8361473450503 Winsorized Mean ( 35 / 44 ) 247.801624060150 4.29123841723113 57.7459464999946 Winsorized Mean ( 36 / 44 ) 247.497383458647 4.0129030306491 61.675395983494 Winsorized Mean ( 37 / 44 ) 247.605601503759 3.98188097454696 62.183074553586 Winsorized Mean ( 38 / 44 ) 247.887601503759 3.95469305339993 62.681881540881 Winsorized Mean ( 39 / 44 ) 244.242714285714 3.51598142949784 69.4664403618872 Winsorized Mean ( 40 / 44 ) 243.881812030075 3.45106512236842 70.6685627139664 Winsorized Mean ( 41 / 44 ) 243.562443609023 3.23245894892827 75.3489672899872 Winsorized Mean ( 42 / 44 ) 243.140548872180 3.10332735768149 78.3483406190933 Winsorized Mean ( 43 / 44 ) 241.219127819549 2.74619956173189 87.8374358444018 Winsorized Mean ( 44 / 44 ) 240.207789473684 2.6344369970482 91.1799332239978 Trimmed Mean ( 1 / 44 ) 264.300694656489 11.7913145080829 22.4148626071599 Trimmed Mean ( 2 / 44 ) 262.942410852713 11.3228044086343 23.2223750727518 Trimmed Mean ( 3 / 44 ) 261.595976377953 10.9089985970189 23.9798340838947 Trimmed Mean ( 4 / 44 ) 260.25616 10.4726481036195 24.8510364737694 Trimmed Mean ( 5 / 44 ) 258.924292682927 10.0066107281066 25.8753237952645 Trimmed Mean ( 6 / 44 ) 257.677165289256 9.59818549104118 26.8464456672325 Trimmed Mean ( 7 / 44 ) 256.455176470588 9.16802149732554 27.9727939714583 Trimmed Mean ( 8 / 44 ) 255.553273504274 8.80632223640279 29.0192962106122 Trimmed Mean ( 9 / 44 ) 255.035347826087 8.52491503228687 29.9164680070332 Trimmed Mean ( 10 / 44 ) 254.710548672566 8.29157636738214 30.7191946846875 Trimmed Mean ( 11 / 44 ) 254.593279279279 8.08962132636375 31.4715941585016 Trimmed Mean ( 12 / 44 ) 254.434155963303 7.90383047169168 32.1912466208103 Trimmed Mean ( 13 / 44 ) 254.265728971963 7.70119125536066 33.0164153234051 Trimmed Mean ( 14 / 44 ) 253.942666666667 7.51123286262685 33.8083868934742 Trimmed Mean ( 15 / 44 ) 253.580669902913 7.31392612539075 34.6709367247492 Trimmed Mean ( 16 / 44 ) 253.078059405941 7.15723233336924 35.3597658449639 Trimmed Mean ( 17 / 44 ) 252.555848484848 7.00016508276883 36.0785560767023 Trimmed Mean ( 18 / 44 ) 252.165453608247 6.86151713435877 36.75068482239 Trimmed Mean ( 19 / 44 ) 251.778347368421 6.71231599458386 37.5099067999152 Trimmed Mean ( 20 / 44 ) 251.350086021505 6.54948139496024 38.3770974927750 Trimmed Mean ( 21 / 44 ) 250.80889010989 6.38655361448441 39.2713981984066 Trimmed Mean ( 22 / 44 ) 250.179775280899 6.21357037239172 40.2634492388633 Trimmed Mean ( 23 / 44 ) 249.605781609195 6.0480165973821 41.2706839655893 Trimmed Mean ( 24 / 44 ) 248.912258823529 5.89407162446543 42.230952503246 Trimmed Mean ( 25 / 44 ) 248.187879518072 5.7239436720549 43.3595950165898 Trimmed Mean ( 26 / 44 ) 247.463740740741 5.53711285450384 44.6918362047571 Trimmed Mean ( 27 / 44 ) 246.622962025316 5.35148748447347 46.0849367098131 Trimmed Mean ( 28 / 44 ) 245.712636363636 5.13906192119801 47.8127409498806 Trimmed Mean ( 29 / 44 ) 244.92432 4.94934692116077 49.4861895723725 Trimmed Mean ( 30 / 44 ) 244.218602739726 4.77386591402834 51.1574072539558 Trimmed Mean ( 31 / 44 ) 243.520957746479 4.60439261308014 52.888834252467 Trimmed Mean ( 32 / 44 ) 242.768260869565 4.41339994175551 55.0070838975449 Trimmed Mean ( 33 / 44 ) 242.239820895522 4.27778068028116 56.6274521768145 Trimmed Mean ( 34 / 44 ) 241.756815384615 4.15079060986789 58.2435584223098 Trimmed Mean ( 35 / 44 ) 241.356206349206 4.04025937734581 59.7377999300039 Trimmed Mean ( 36 / 44 ) 240.95468852459 3.91778744870007 61.5027465577643 Trimmed Mean ( 37 / 44 ) 240.545 3.81164141728733 63.1079825371379 Trimmed Mean ( 38 / 44 ) 240.099736842105 3.68508747192904 65.1544199889561 Trimmed Mean ( 39 / 44 ) 239.604145454545 3.53131124981112 67.8513244810583 Trimmed Mean ( 40 / 44 ) 239.305679245283 3.42571316262027 69.8557257672566 Trimmed Mean ( 41 / 44 ) 239.007333333333 3.30479404616713 72.3214003639749 Trimmed Mean ( 42 / 44 ) 238.705775510204 3.19329332714437 74.7522231926212 Trimmed Mean ( 43 / 44 ) 238.406978723404 3.07646815766912 77.4937254361289 Trimmed Mean ( 44 / 44 ) 238.213688888889 3.00111404480427 79.375087161816 Median 238.502 Midrange 352.229 Midmean - Weighted Average at Xnp 241.000424242424 Midmean - Weighted Average at X(n+1)p 242.239820895522 Midmean - Empirical Distribution Function 242.239820895522 Midmean - Empirical Distribution Function - Averaging 242.239820895522 Midmean - Empirical Distribution Function - Interpolation 242.239820895522 Midmean - Closest Observation 241.477161764706 Midmean - True Basic - Statistics Graphics Toolkit 242.239820895522 Midmean - MS Excel (old versions) 242.239820895522 Number of observations 133

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Sep/30/t1285845146zc7uo2en8ggfx1h/1cwgl1285845021.png (open in new window) http://www.freestatistics.org/blog/date/2010/Sep/30/t1285845146zc7uo2en8ggfx1h/1cwgl1285845021.ps (open in new window) http://www.freestatistics.org/blog/date/2010/Sep/30/t1285845146zc7uo2en8ggfx1h/2n6f51285845021.png (open in new window) http://www.freestatistics.org/blog/date/2010/Sep/30/t1285845146zc7uo2en8ggfx1h/2n6f51285845021.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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