Central Tendancy Niet-werkende Werkzoekende

*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: Fri, 12 Nov 2010 11:33:12 +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/12/t1289561521njtralvnxg8zygp.htm/, Retrieved Fri, 12 Nov 2010 12:32:06 +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/12/t1289561521njtralvnxg8zygp.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:

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Dataseries X:

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586111 604378 600991 544686 537034 551531 563250 574761 580112 575093 557560 564478 580523 596594 586570 536214 523597 536535 536322 532638 528222 516141 501866 506174 517945 533590 528379 477580 469357 490243 492622 507561 516922 514258 509846 527070 541657 564591 555362 498662 511038 525919 531673 548854 560576 557274 565742 587625 619916 625809 619567 572942 572775 574205 579799 590072 593408 597141 595404 612117 628232 628884 620735 569028 567456 573100 584428 589379 590865 595454 594167 611324 612613 610763 593530 542722 536662 543599 555332 560854 562325 554788 547344 565464 577992 579714 569323 506971 500857 509127 509933 517009 519164 512238 509239 518585 522975 525192 516847 455626 454724 461251 470439 474605 476049 471067 470984 502831 512927 509673 484015 431328 436087 442867 447988 460070 467037 460170 464196 485025 501492 520564 488180 439148 441977 456608 461935 480961 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 535393.682170543 4410.47336922001 121.391432925765 Geometric Mean 533034.327082557 Harmonic Mean 530644.371858561 Quadratic Mean 537713.944539035 Winsorized Mean ( 1 / 43 ) 535425.519379845 4402.98706303906 121.605063043333 Winsorized Mean ( 2 / 43 ) 535435.410852713 4388.62214658769 122.005356799522 Winsorized Mean ( 3 / 43 ) 535383.201550388 4358.95709052934 122.823691637986 Winsorized Mean ( 4 / 43 ) 535385.403100775 4350.48463546428 123.063393612845 Winsorized Mean ( 5 / 43 ) 535570.364341085 4316.20504057321 124.083624226980 Winsorized Mean ( 6 / 43 ) 535560.224806202 4220.24146336598 126.902744654579 Winsorized Mean ( 7 / 43 ) 535582.255813953 4209.11602987382 127.243405031533 Winsorized Mean ( 8 / 43 ) 535593.976744186 4193.15347102257 127.730592368128 Winsorized Mean ( 9 / 43 ) 535796.372093023 4152.65162465557 129.025119495176 Winsorized Mean ( 10 / 43 ) 535309.162790698 4083.92094194145 131.077258938372 Winsorized Mean ( 11 / 43 ) 535112.527131783 4033.18966674884 132.677253327175 Winsorized Mean ( 12 / 43 ) 534818.015503876 3979.31777997976 134.399423487761 Winsorized Mean ( 13 / 43 ) 534990.744186047 3940.28421202652 135.774658729731 Winsorized Mean ( 14 / 43 ) 535175.348837209 3882.44396728591 137.844963983172 Winsorized Mean ( 15 / 43 ) 535439.302325581 3845.13090786198 139.251254419138 Winsorized Mean ( 16 / 43 ) 535420.07751938 3808.58575425398 140.582387286763 Winsorized Mean ( 17 / 43 ) 535407.953488372 3788.94043936875 141.308094454389 Winsorized Mean ( 18 / 43 ) 535402.511627907 3785.36329229003 141.440192205173 Winsorized Mean ( 19 / 43 ) 535549.062015504 3672.5129397795 145.826324044935 Winsorized Mean ( 20 / 43 ) 535649.992248062 3629.20231862827 147.594414755726 Winsorized Mean ( 21 / 43 ) 535786.410852713 3584.20473434689 149.48543695575 Winsorized Mean ( 22 / 43 ) 536063.88372093 3477.1188867015 154.168983341682 Winsorized Mean ( 23 / 43 ) 536420.294573643 3388.73847137462 158.294981777112 Winsorized Mean ( 24 / 43 ) 536522.80620155 3356.25922771813 159.857379838423 Winsorized Mean ( 25 / 43 ) 536808.07751938 3246.30424185632 165.359756056758 Winsorized Mean ( 26 / 43 ) 536436.821705426 3109.11261610500 172.536954411596 Winsorized Mean ( 27 / 43 ) 536848.72868217 3042.38957212813 176.456274239281 Winsorized Mean ( 28 / 43 ) 536833.534883721 3028.86529592652 177.239158045655 Winsorized Mean ( 29 / 43 ) 538117.627906977 2883.06050369798 186.648052379323 Winsorized Mean ( 30 / 43 ) 538227.627906977 2784.08083969923 193.323275758445 Winsorized Mean ( 31 / 43 ) 537683.565891473 2691.35247259889 199.78192056437 Winsorized Mean ( 32 / 43 ) 537693.984496124 2672.68759099491 201.181008325768 Winsorized Mean ( 33 / 43 ) 537798.612403101 2631.55461820824 204.365362087477 Winsorized Mean ( 34 / 43 ) 538388.472868217 2510.14132407349 214.485323079146 Winsorized Mean ( 35 / 43 ) 538561.84496124 2483.9240829991 216.818963448746 Winsorized Mean ( 36 / 43 ) 538679.891472868 2462.57613464035 218.746492299431 Winsorized Mean ( 37 / 43 ) 538138.945736434 2312.64527524796 232.694115044831 Winsorized Mean ( 38 / 43 ) 538085.03875969 2300.26892311079 233.922665890737 Winsorized Mean ( 39 / 43 ) 537740.992248062 2237.78393529686 240.300675934885 Winsorized Mean ( 40 / 43 ) 537263.162790698 2177.79595038769 246.700414102181 Winsorized Mean ( 41 / 43 ) 537202.457364341 2166.05966187886 248.009076951448 Winsorized Mean ( 42 / 43 ) 537277.992248062 2101.90612209762 255.614647390569 Winsorized Mean ( 43 / 43 ) 537640.325581395 2059.29408694497 261.079915195116 Trimmed Mean ( 1 / 43 ) 535476.952755905 4341.56715414354 123.337249832668 Trimmed Mean ( 2 / 43 ) 535530.032 4274.02333986013 125.298808503354 Trimmed Mean ( 3 / 43 ) 535579.650406504 4207.90082934179 127.279532509867 Trimmed Mean ( 4 / 43 ) 535649.462809917 4146.83323669772 129.170726729410 Trimmed Mean ( 5 / 43 ) 535721.025210084 4082.01034065703 131.239507130660 Trimmed Mean ( 6 / 43 ) 535754.247863248 4019.29288062313 133.295647711094 Trimmed Mean ( 7 / 43 ) 535790.52173913 3971.47029500357 134.90986509787 Trimmed Mean ( 8 / 43 ) 535824.486725664 3920.49486146493 136.672666502475 Trimmed Mean ( 9 / 43 ) 535857.972972973 3866.64171265761 138.584852901891 Trimmed Mean ( 10 / 43 ) 535866.073394495 3813.48318977364 140.518797835924 Trimmed Mean ( 11 / 43 ) 535933.214953271 3764.95854359045 142.347706820214 Trimmed Mean ( 12 / 43 ) 536024.876190476 3718.10034801773 144.166328505968 Trimmed Mean ( 13 / 43 ) 536150.834951456 3672.98971177765 145.971232435598 Trimmed Mean ( 14 / 43 ) 536264.811881188 3627.49019311304 147.833566276571 Trimmed Mean ( 15 / 43 ) 536366.212121212 3583.75724397886 149.665888509154 Trimmed Mean ( 16 / 43 ) 536448.391752577 3539.01763189644 151.581158262021 Trimmed Mean ( 17 / 43 ) 536535.663157895 3492.75526943146 153.613872650525 Trimmed Mean ( 18 / 43 ) 536627.677419355 3442.47351705899 155.884329904101 Trimmed Mean ( 19 / 43 ) 536724.164835165 3385.50533094425 158.535908931937 Trimmed Mean ( 20 / 43 ) 536813.808988764 3334.44254869393 160.990570732439 Trimmed Mean ( 21 / 43 ) 536900.091954023 3281.14796681297 163.631782956598 Trimmed Mean ( 22 / 43 ) 536980.576470588 3225.36436103737 166.486795401274 Trimmed Mean ( 23 / 43 ) 537045.337349398 3174.19261832334 169.191161950680 Trimmed Mean ( 24 / 43 ) 537088.617283951 3125.67977962285 171.830979227423 Trimmed Mean ( 25 / 43 ) 537127.11392405 3073.13359153182 174.781569992314 Trimmed Mean ( 26 / 43 ) 537148.493506494 3025.34361547064 177.549581726746 Trimmed Mean ( 27 / 43 ) 537195.573333333 2985.85205628886 179.913660558594 Trimmed Mean ( 28 / 43 ) 537218.273972603 2947.12806990961 182.285350764916 Trimmed Mean ( 29 / 43 ) 537243.23943662 2902.53993596386 185.094176579594 Trimmed Mean ( 30 / 43 ) 537186.869565217 2867.43375803878 187.340637969134 Trimmed Mean ( 31 / 43 ) 537120.074626866 2837.09813654990 189.320231016062 Trimmed Mean ( 32 / 43 ) 537084 2811.45694743983 191.034047485265 Trimmed Mean ( 33 / 43 ) 537044.968253968 2781.59995805663 193.070526442334 Trimmed Mean ( 34 / 43 ) 536996.672131148 2749.57927220960 195.301396674994 Trimmed Mean ( 35 / 43 ) 536907.169491525 2725.31272444599 197.007545106836 Trimmed Mean ( 36 / 43 ) 536800.175438597 2697.17349443811 199.023228036884 Trimmed Mean ( 37 / 43 ) 536677.709090909 2663.57417384566 201.487803253497 Trimmed Mean ( 38 / 43 ) 536581.58490566 2642.58121759893 203.052069443376 Trimmed Mean ( 39 / 43 ) 536481.509803922 2615.55673575231 205.111784604288 Trimmed Mean ( 40 / 43 ) 536396.489795918 2589.09523225832 207.175264591581 Trimmed Mean ( 41 / 43 ) 536337.021276596 2562.82542402213 209.275675295456 Trimmed Mean ( 42 / 43 ) 536276.511111111 2528.07052281088 212.128778161949 Trimmed Mean ( 43 / 43 ) 536204.976744186 2492.01888416495 215.168905882454 Median 536214 Midrange 530106 Midmean - Weighted Average at Xnp 536495.296875 Midmean - Weighted Average at X(n+1)p 537084 Midmean - Empirical Distribution Function 537084 Midmean - Empirical Distribution Function - Averaging 537084 Midmean - Empirical Distribution Function - Interpolation 537084 Midmean - Closest Observation 536544.727272727 Midmean - True Basic - Statistics Graphics Toolkit 537084 Midmean - MS Excel (old versions) 537084 Number of observations 129

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Nov/12/t1289561521njtralvnxg8zygp/11vjs1289561590.png (open in new window) http://www.freestatistics.org/blog/date/2010/Nov/12/t1289561521njtralvnxg8zygp/11vjs1289561590.ps (open in new window) http://www.freestatistics.org/blog/date/2010/Nov/12/t1289561521njtralvnxg8zygp/21vjs1289561590.png (open in new window) http://www.freestatistics.org/blog/date/2010/Nov/12/t1289561521njtralvnxg8zygp/21vjs1289561590.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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