Centrummaten Australische chocoladeproductie

*Unverified author*

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

Title produced by software: Central Tendency

Date of computation: Mon, 04 Apr 2011 18:28:33 +0000

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2011/Apr/04/t1301941593g16wulby00u2556.htm/, Retrieved Mon, 04 Apr 2011 20:26:36 +0200

Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords:

KDGP1W52

Dataseries X:

» Textbox « » Textfile « » CSV «

7992 6114 5965 8460 8323 6333 5675 10090 9035 6976 6459 10896 9978 7466 7199 10977 9412 6341 7784 11911 10079 7721 8197 12038 11963 8033 8618 13625 11734 8895 8727 13974 12583 9525 9662 15490 13839 10047 9788 14978 13045 9489 8741 13149 14106 9998 10034 15081 13266 9997 9027 14324 13149 11209 10332 15354 13800 11786 10550 16114 13255 11403 10269 14009 15847 12967 11328 15814 18626 13219 13818 18062 15722 12111 11702 15589 14852 13612 12380 15501 16322 12157 11124 14621 14035 11159 10944 15824 14378 11816 12233 17344 16812 12181 13275 18458 17375 14609 13323 18327 16053 15070 13806 18245 17461 14999 16022 20564 16372 15854 15115 18207 19488 16644 18631 21093 22212 19762 19403 21227 23176 20823 20647 21336 23458 22003 21647 26416 25226 24723 19945 24040 25034 24885 21168 23541 26019 24657 20599 24534 28717 26138 22968 26577 28660 30430 27356 25454 30194

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 'George Udny Yule' @ 216.218.223.82 Central Tendency - Ungrouped Data Measure Value S.E. Value/S.E. Arithmetic Mean 15157.4161073826 478.891792203249 31.651025041894 Geometric Mean 14074.2193958265 Harmonic Mean 13039.6950037437 Quadratic Mean 16238.5094959792 Winsorized Mean ( 1 / 49 ) 15157.7785234899 478.296343252368 31.6911863060013 Winsorized Mean ( 2 / 49 ) 15139.9530201342 474.012943848127 31.9399569497517 Winsorized Mean ( 3 / 49 ) 15143.2147651007 473.23015305279 31.9996827493184 Winsorized Mean ( 4 / 49 ) 15108.4228187919 466.719593208852 32.3715203703289 Winsorized Mean ( 5 / 49 ) 15086.2416107383 461.702210741013 32.6752639683606 Winsorized Mean ( 6 / 49 ) 15100.5771812081 458.05398960157 32.9668063678323 Winsorized Mean ( 7 / 49 ) 15097.9932885906 454.649773767995 33.2079639311446 Winsorized Mean ( 8 / 49 ) 15105.9395973154 451.944195948375 33.4243469276481 Winsorized Mean ( 9 / 49 ) 15087.2147651007 444.730125986005 33.924427160519 Winsorized Mean ( 10 / 49 ) 15076.1409395973 441.865201448012 34.1193216623353 Winsorized Mean ( 11 / 49 ) 15077.322147651 437.981106957316 34.424594824179 Winsorized Mean ( 12 / 49 ) 15068.6241610738 435.785702426932 34.5780599894747 Winsorized Mean ( 13 / 49 ) 15068.7986577181 432.093891057566 34.8738988668335 Winsorized Mean ( 14 / 49 ) 15074.4362416107 429.89455892173 35.0654269256646 Winsorized Mean ( 15 / 49 ) 15075.8456375839 426.580112089378 35.3411826063405 Winsorized Mean ( 16 / 49 ) 15039.7651006711 416.965258275624 36.0695880584121 Winsorized Mean ( 17 / 49 ) 14995.2684563758 407.485077733241 36.7995523659212 Winsorized Mean ( 18 / 49 ) 14986.932885906 405.891871982848 36.9234614447745 Winsorized Mean ( 19 / 49 ) 14970.610738255 398.825040357547 37.5367873713092 Winsorized Mean ( 20 / 49 ) 14960.4093959732 393.147848319044 38.0528838195055 Winsorized Mean ( 21 / 49 ) 14854.9865771812 378.700643633402 39.226198388935 Winsorized Mean ( 22 / 49 ) 14879.7919463087 368.984403161506 40.3263439289486 Winsorized Mean ( 23 / 49 ) 14836.7248322148 360.703940951905 41.1326940123259 Winsorized Mean ( 24 / 49 ) 14792.4295302013 353.795870240589 41.8106336858657 Winsorized Mean ( 25 / 49 ) 14797.1275167785 349.217266327264 42.3722677644226 Winsorized Mean ( 26 / 49 ) 14808.8187919463 345.766264194845 42.8289868776824 Winsorized Mean ( 27 / 49 ) 14829.6577181208 340.732372515457 43.522890439323 Winsorized Mean ( 28 / 49 ) 14782.4899328859 334.137657843879 44.2407181168212 Winsorized Mean ( 29 / 49 ) 14748.4295302013 329.95772273078 44.6979370815786 Winsorized Mean ( 30 / 49 ) 14746.0134228188 328.087328633858 44.9453914731196 Winsorized Mean ( 31 / 49 ) 14741.4362416107 326.94790620005 45.0880276706555 Winsorized Mean ( 32 / 49 ) 14615.3691275168 310.562298665126 47.0609896640296 Winsorized Mean ( 33 / 49 ) 14577.2751677852 305.648519530684 47.6929356313203 Winsorized Mean ( 34 / 49 ) 14555.5973154362 294.491981864535 49.4261243490553 Winsorized Mean ( 35 / 49 ) 14550.4295302013 290.783470606692 50.0387092149469 Winsorized Mean ( 36 / 49 ) 14416.5771812081 265.048315378467 54.3922611265133 Winsorized Mean ( 37 / 49 ) 14501.255033557 256.598861293498 56.5133257429795 Winsorized Mean ( 38 / 49 ) 14470.6510067114 250.807971875354 57.6961366040749 Winsorized Mean ( 39 / 49 ) 14445 246.319403240675 58.6433703961437 Winsorized Mean ( 40 / 49 ) 14462.4496644295 240.246414334538 60.1983996493321 Winsorized Mean ( 41 / 49 ) 14461.6241610738 238.231662468288 60.704039132493 Winsorized Mean ( 42 / 49 ) 14434.8456375839 232.58672449611 62.0622078446498 Winsorized Mean ( 43 / 49 ) 14295.744966443 211.422097895509 67.6170802803609 Winsorized Mean ( 44 / 49 ) 14292.4966442953 206.76244476155 69.1252062761118 Winsorized Mean ( 45 / 49 ) 14373.4362416107 197.420358528135 72.8062513348253 Winsorized Mean ( 46 / 49 ) 14219.0738255034 180.15705205218 78.9259907593568 Winsorized Mean ( 47 / 49 ) 14182.4832214765 173.510050906705 81.7386839976339 Winsorized Mean ( 48 / 49 ) 14104.5234899329 164.316709733853 85.8374264721969 Winsorized Mean ( 49 / 49 ) 14119.322147651 159.856480465629 88.3249906824192 Trimmed Mean ( 1 / 49 ) 15118.0272108844 469.652662729338 32.189804105501 Trimmed Mean ( 2 / 49 ) 15077.1793103448 460.230988322136 32.7600263626569 Trimmed Mean ( 3 / 49 ) 15044.4755244755 452.409097513596 33.254140129274 Trimmed Mean ( 4 / 49 ) 15009.695035461 444.182661494533 33.7917175446654 Trimmed Mean ( 5 / 49 ) 14983.2374100719 437.228094343726 34.2686977435921 Trimmed Mean ( 6 / 49 ) 14960.8321167883 430.92195771132 34.718193977042 Trimmed Mean ( 7 / 49 ) 14935.1259259259 424.822534460539 35.1561527801045 Trimmed Mean ( 8 / 49 ) 14909.0601503759 418.808731204669 35.5987328809771 Trimmed Mean ( 9 / 49 ) 14881.0687022901 412.688013088457 36.0588828130087 Trimmed Mean ( 10 / 49 ) 14854.6124031008 407.15346204567 36.4840626147852 Trimmed Mean ( 11 / 49 ) 14828.6220472441 401.50434963185 36.9326560492827 Trimmed Mean ( 12 / 49 ) 14801.672 395.835936000209 37.3934518163409 Trimmed Mean ( 13 / 49 ) 14774.7235772358 389.884133282126 37.8951650400828 Trimmed Mean ( 14 / 49 ) 14746.867768595 383.790727048401 38.4242419873143 Trimmed Mean ( 15 / 49 ) 14746.867768595 377.318512308913 39.0833401689067 Trimmed Mean ( 16 / 49 ) 14687.1538461538 370.548679056813 39.6362331759979 Trimmed Mean ( 17 / 49 ) 14658.6 364.219414595053 40.2466189681232 Trimmed Mean ( 18 / 49 ) 14632.4867256637 358.321622473387 40.8361812626881 Trimmed Mean ( 19 / 49 ) 14606.0540540541 351.931895782546 41.5025015609239 Trimmed Mean ( 20 / 49 ) 14579.8256880734 345.613179583978 42.1853868698626 Trimmed Mean ( 21 / 49 ) 14553.3271028037 339.187588516725 42.9064258112915 Trimmed Mean ( 22 / 49 ) 14532.9428571429 333.661845398646 43.5559026528175 Trimmed Mean ( 23 / 49 ) 14510.1359223301 328.488495985435 44.1724325194434 Trimmed Mean ( 24 / 49 ) 14489.1881188119 323.571611953142 44.7789224504346 Trimmed Mean ( 25 / 49 ) 14470.1717171717 318.775800420784 45.3929429337833 Trimmed Mean ( 26 / 49 ) 14450.0824742268 313.822040534157 46.0454672005551 Trimmed Mean ( 27 / 49 ) 14428.4421052632 308.552164526874 46.7617594820226 Trimmed Mean ( 28 / 49 ) 14404.6344086022 303.073733418156 47.5284817530784 Trimmed Mean ( 29 / 49 ) 14382.5384615385 297.575277845429 48.3324373102299 Trimmed Mean ( 30 / 49 ) 14382.5384615385 291.767731761918 49.2944794638037 Trimmed Mean ( 31 / 49 ) 14339.4597701149 285.310360518024 50.2591624926606 Trimmed Mean ( 32 / 49 ) 14316.7294117647 278.007050264385 51.4977206446723 Trimmed Mean ( 33 / 49 ) 14299.9759036145 271.632852749607 52.6445006885683 Trimmed Mean ( 34 / 49 ) 14284.5185185185 264.866526549025 53.9310070798038 Trimmed Mean ( 35 / 49 ) 14269.4810126582 258.381488236692 55.2264061564139 Trimmed Mean ( 36 / 49 ) 14253.9480519481 251.280347460476 56.725279935352 Trimmed Mean ( 37 / 49 ) 14244.9733333333 246.277523800141 57.8411424377216 Trimmed Mean ( 38 / 49 ) 14230.8356164384 241.364724784939 58.9598816857696 Trimmed Mean ( 39 / 49 ) 14217.5915492958 236.300189820578 60.1674994848338 Trimmed Mean ( 40 / 49 ) 14205 230.88203034279 61.5249267295072 Trimmed Mean ( 41 / 49 ) 14190.6865671642 225.212230385121 63.0102838682322 Trimmed Mean ( 42 / 49 ) 14175.5384615385 218.687878076841 64.8208697537297 Trimmed Mean ( 43 / 49 ) 14160.9365079365 211.685678202071 66.8960537538998 Trimmed Mean ( 44 / 49 ) 14153.2786885246 206.527074041401 68.5298949506608 Trimmed Mean ( 45 / 49 ) 14145.2881355932 200.936057664941 70.3969625958342 Trimmed Mean ( 46 / 49 ) 14132.0350877193 195.462987357292 72.300312600293 Trimmed Mean ( 47 / 49 ) 14126.9090909091 191.589680230591 73.7352297571895 Trimmed Mean ( 48 / 49 ) 14123.5849056604 187.801456616754 75.2048741266279 Trimmed Mean ( 49 / 49 ) 14124.7450980392 184.520622882992 76.5483276468019 Median 14009 Midrange 18052.5 Midmean - Weighted Average at Xnp 14185.7702702703 Midmean - Weighted Average at X(n+1)p 14244.9733333333 Midmean - Empirical Distribution Function 14244.9733333333 Midmean - Empirical Distribution Function - Averaging 14244.9733333333 Midmean - Empirical Distribution Function - Interpolation 14244.9733333333 Midmean - Closest Observation 14196.3552631579 Midmean - True Basic - Statistics Graphics Toolkit 14244.9733333333 Midmean - MS Excel (old versions) 14244.9733333333 Number of observations 149

Charts produced by software:

http://www.freestatistics.org/blog/date/2011/Apr/04/t1301941593g16wulby00u2556/1qw4s1301941710.png (open in new window) http://www.freestatistics.org/blog/date/2011/Apr/04/t1301941593g16wulby00u2556/1qw4s1301941710.ps (open in new window) http://www.freestatistics.org/blog/date/2011/Apr/04/t1301941593g16wulby00u2556/2zal91301941710.png (open in new window) http://www.freestatistics.org/blog/date/2011/Apr/04/t1301941593g16wulby00u2556/2zal91301941710.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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