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Datareeks-Inschrijving nieuwe personenwagens Centrummaten

*Unverified author*
R Software Module: /rwasp_centraltendency.wasp (opens new window with default values)
Title produced by software: Central Tendency
Date of computation: Thu, 11 Mar 2010 09:42:49 -0700
 
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/11/t1268325846n8scx857rb4by6y.htm/, Retrieved Thu, 11 Mar 2010 17:44:08 +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/11/t1268325846n8scx857rb4by6y.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 «
14538 18730 22485 20036 16971 19028 22759 20516 26195 27786 24090 25447 11509 15572 22518 20520 17789 20205 26835 25826 31934 30019 30111 31566 12738 19814 24776 20424 18688 20418 25778 25100 25859 30651 26551 31124 9367 17382 20995 18205 17328 18157 23691 26736 27165 34506 29506 31956 10698 18479 19785 19684 18730 17970 27044 22405 26482 29096 25591 29743 13807 19169 22782 20366 17537 18004 24319 22679 32034 36438 29383 28029 15548 17704 25316 20764 18089 21705 23843 22397 26105 29462 27071 31514 11514 17409 24561 21382 17351 22780 23970 26887 34777 35022 35338 36845 13971 22228 28806 20506 22414 25814 28352 29965 30212 32609 30364 37702 13253 21790 27192 21725 22205 24693 29133 35953 37863 43129 39690 41086
 
Output produced by software:


Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135


Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean24318.025621.57181636067439.123435715575
Geometric Mean23340.8604743187
Harmonic Mean22310.8389704114
Quadratic Mean25245.6366749781
Winsorized Mean ( 1 / 40 )24312.0916666667615.30318982236639.5123770993051
Winsorized Mean ( 2 / 40 )24302.3416666667607.70909468834139.9900904545948
Winsorized Mean ( 3 / 40 )24256.7916666667598.46051821499640.5319831941736
Winsorized Mean ( 4 / 40 )24292.225590.42884268306141.1433575799073
Winsorized Mean ( 5 / 40 )24277.975580.29288273823641.837450918645
Winsorized Mean ( 6 / 40 )24285.325572.28241570756142.4359098470185
Winsorized Mean ( 7 / 40 )24266.6565.83520522126242.8863382413805
Winsorized Mean ( 8 / 40 )24263.4553.14360024590143.86455884008
Winsorized Mean ( 9 / 40 )24315.45538.38481297463945.1636996698594
Winsorized Mean ( 10 / 40 )24297.0333333333534.72354907956245.4384950413286
Winsorized Mean ( 11 / 40 )24400.4333333333514.02619781046347.4692407454503
Winsorized Mean ( 12 / 40 )24246.4333333333480.08144598659450.5048331611849
Winsorized Mean ( 13 / 40 )24186.6333333333470.85556729932551.3674150059646
Winsorized Mean ( 14 / 40 )24181.15469.14383155368751.5431481213727
Winsorized Mean ( 15 / 40 )24181.775468.35050729536351.6317899165846
Winsorized Mean ( 16 / 40 )24149.775459.54123565100852.551921626333
Winsorized Mean ( 17 / 40 )24166.0666666667455.70250439477753.0303573792334
Winsorized Mean ( 18 / 40 )24120.3166666667446.36178863810654.0375930033351
Winsorized Mean ( 19 / 40 )24074.0833333333433.24039079494155.5674951939741
Winsorized Mean ( 20 / 40 )24031.9166666667426.53324626074956.3424231929049
Winsorized Mean ( 21 / 40 )24020.1916666667421.46917264114556.9915742974596
Winsorized Mean ( 22 / 40 )24014.1416666667417.71898587672757.4887483657577
Winsorized Mean ( 23 / 40 )24005.7083333333414.47967235430857.9176976206752
Winsorized Mean ( 24 / 40 )24049.7083333333406.7852253010559.1213909392477
Winsorized Mean ( 25 / 40 )24047396.18466289704660.6964434820864
Winsorized Mean ( 26 / 40 )24004.75388.9953257821961.7096103962981
Winsorized Mean ( 27 / 40 )23994.85387.82066259746361.8709942871336
Winsorized Mean ( 28 / 40 )24045.95377.78683592253363.6495179650219
Winsorized Mean ( 29 / 40 )24019.6083333333366.86695706630765.4722587321814
Winsorized Mean ( 30 / 40 )24139.1083333333351.76757983575868.6223225704996
Winsorized Mean ( 31 / 40 )24090.2833333333340.19147355737670.8138951321197
Winsorized Mean ( 32 / 40 )23976.95325.47085367147173.66850127908
Winsorized Mean ( 33 / 40 )23949.175308.99362549571977.5070196402216
Winsorized Mean ( 34 / 40 )23928.2083333333296.33063828144880.7483440527904
Winsorized Mean ( 35 / 40 )23801.9166666667272.82732084684487.2416904318327
Winsorized Mean ( 36 / 40 )23809.4166666667270.33419393822888.0740106155685
Winsorized Mean ( 37 / 40 )23782.2833333333267.12801334916889.029536944323
Winsorized Mean ( 38 / 40 )23799.7263.50801751392290.3186939985329
Winsorized Mean ( 39 / 40 )23751.925257.9201177450292.0902378909472
Winsorized Mean ( 40 / 40 )23735.925256.01258179934492.713900360583
Trimmed Mean ( 1 / 40 )24285.3135593220598.15179354005940.6005863755646
Trimmed Mean ( 2 / 40 )24257.6120689655579.0327186965141.8933357057491
Trimmed Mean ( 3 / 40 )24234.0701754386562.21882658021443.104337723527
Trimmed Mean ( 4 / 40 )24225.9553571429547.33443565848544.2617050542365
Trimmed Mean ( 5 / 40 )24207.8818181818533.35010396530645.3883511753408
Trimmed Mean ( 6 / 40 )24192.3055555556520.51800281329446.4773656718904
Trimmed Mean ( 7 / 40 )24174.7547169811508.07732002985447.5808578024318
Trimmed Mean ( 8 / 40 )24159.6153846154495.52320123542348.7557703138448
Trimmed Mean ( 9 / 40 )24144.3529411765483.93966747557449.8912458801388
Trimmed Mean ( 10 / 40 )24121.54473.58840340787950.9335529046417
Trimmed Mean ( 11 / 40 )24100.0510204082462.54089779369952.103611021997
Trimmed Mean ( 12 / 40 )24065.9166666667453.36624066257453.0827276232466
Trimmed Mean ( 13 / 40 )24046.7127659574448.19919645523853.6518426542048
Trimmed Mean ( 14 / 40 )24032.6739130435443.6023333192754.1761665977231
Trimmed Mean ( 15 / 40 )24018.5333333333438.53674698015354.7697165601959
Trimmed Mean ( 16 / 40 )24003.6931818182432.79833676031655.4616114320038
Trimmed Mean ( 17 / 40 )23990.9534883721427.35762516074456.1378856393361
Trimmed Mean ( 18 / 40 )23976.2380952381421.54373754990256.877225207028
Trimmed Mean ( 19 / 40 )23964.5243902439416.01749183861457.6046076436144
Trimmed Mean ( 20 / 40 )23955.875411.25105377688158.251218519666
Trimmed Mean ( 21 / 40 )23950.0256410256406.48952416783758.919170647893
Trimmed Mean ( 22 / 40 )23944.75401.49451990972959.6390456472075
Trimmed Mean ( 23 / 40 )23939.6351351351396.04325816477860.4470209796497
Trimmed Mean ( 24 / 40 )23934.8472222222389.98082627104461.3744205095536
Trimmed Mean ( 25 / 40 )23926.6428571429383.76068340385062.3478222024212
Trimmed Mean ( 26 / 40 )23918.1470588235377.72908861127163.3209032080613
Trimmed Mean ( 27 / 40 )23912.0909090909371.44690863360364.375528112627
Trimmed Mean ( 28 / 40 )23906.34375364.00742487817965.6754288954425
Trimmed Mean ( 29 / 40 )23896.6935483871356.42026066860567.0463949034758
Trimmed Mean ( 30 / 40 )23888.2166666667348.79679714915268.4874885948326
Trimmed Mean ( 31 / 40 )23870.9137931034341.63576590037669.872408499713
Trimmed Mean ( 32 / 40 )23855.75334.58499905242271.2995205031961
Trimmed Mean ( 33 / 40 )23847.3333333333328.17885882891772.6656598734936
Trimmed Mean ( 34 / 40 )23840.2115384615322.73463097967773.869393768166
Trimmed Mean ( 35 / 40 )23834317.79863217491274.9971761580211
Trimmed Mean ( 36 / 40 )23836.2916666667315.20052150557775.6226276302177
Trimmed Mean ( 37 / 40 )23838.2391304348311.89888765521976.4293816808548
Trimmed Mean ( 38 / 40 )23842.3636363636307.81142481429177.4576955704234
Trimmed Mean ( 39 / 40 )23845.5714285714302.79452051277978.7516609884131
Trimmed Mean ( 40 / 40 )23852.775296.93124579195880.3309700074886
Median23906.5
Midrange26248
Midmean - Weighted Average at Xnp23810.8524590164
Midmean - Weighted Average at X(n+1)p23888.2166666667
Midmean - Empirical Distribution Function23810.8524590164
Midmean - Empirical Distribution Function - Averaging23888.2166666667
Midmean - Empirical Distribution Function - Interpolation23888.2166666667
Midmean - Closest Observation23810.8524590164
Midmean - True Basic - Statistics Graphics Toolkit23888.2166666667
Midmean - MS Excel (old versions)23896.6935483871
Number of observations120
 
Charts produced by software:
http://www.freestatistics.org/blog/date/2010/Mar/11/t1268325846n8scx857rb4by6y/1j25x1268325766.png (open in new window)
http://www.freestatistics.org/blog/date/2010/Mar/11/t1268325846n8scx857rb4by6y/1j25x1268325766.ps (open in new window)


http://www.freestatistics.org/blog/date/2010/Mar/11/t1268325846n8scx857rb4by6y/2zdfo1268325766.png (open in new window)
http://www.freestatistics.org/blog/date/2010/Mar/11/t1268325846n8scx857rb4by6y/2zdfo1268325766.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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