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Opgave 5 oefening 2

*Unverified author*
R Software Module: /rwasp_centraltendency.wasp (opens new window with default values)
Title produced by software: Central Tendency
Date of computation: Fri, 12 Mar 2010 12:04:36 -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/12/t1268420717a1zxhz91mpenub4.htm/, Retrieved Fri, 12 Mar 2010 20:05:20 +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/12/t1268420717a1zxhz91mpenub4.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 «
562674 599000 668516 597798 579889 668233 499232 215187 555813 586935 546136 571111 634712 639283 712182 621557 621000 675989 501322 220286 560727 602530 626379 605508 646783 658442 712906 687714 723916 707183 629000 237530 613296 730444 734925 651812 676155 748183 810681 729363 701108 790079 594621 230716 617189 691389 701067 705777 747636 773392 813788 766713 728875 749197 680954 241424 680234 708326 694238 772071 795337 788421 889968 797393 751000 821255 691605 290655 727147 868355 812390 799556 843038 847000 941952 804309 840307 871528 656330 370508 742000 847152 731675 898527 778139 856075 938833 813023 783417 828110 657311 310032 780000 860000 780000 807993 895217 856075 893268 875000 835088 934595 832500 300000 791443 900000 781729 880000 875024 992968 976804 968697 871675 1006852 832037 345587 849528 913871 868746 993733
 
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 Mean713749.215888.567401316944.9221872540152
Geometric Mean684331.46912366
Harmonic Mean641271.210635585
Quadratic Mean734492.384449639
Winsorized Mean ( 1 / 40 )713682.36666666715860.826523234244.9965432520939
Winsorized Mean ( 2 / 40 )713843.4515813.899446372545.1402547752856
Winsorized Mean ( 3 / 40 )713609.715711.928370971545.4183396939632
Winsorized Mean ( 4 / 40 )713469.26666666715641.395451349945.6141697130413
Winsorized Mean ( 5 / 40 )714406.18333333314989.690120885347.659836699222
Winsorized Mean ( 6 / 40 )714717.48333333314859.565380127148.0981418399479
Winsorized Mean ( 7 / 40 )715055.46666666714691.964300117648.6698342073255
Winsorized Mean ( 8 / 40 )716044.213984.331864183551.2033186107319
Winsorized Mean ( 9 / 40 )716872.9513452.597390893153.2888132432549
Winsorized Mean ( 10 / 40 )727477.211349.451000466464.0980079098189
Winsorized Mean ( 11 / 40 )727365.36666666711278.942997700164.488788250369
Winsorized Mean ( 12 / 40 )731651.86666666710544.008313425069.3902968319078
Winsorized Mean ( 13 / 40 )732342.70833333310345.413052248070.7891221582687
Winsorized Mean ( 14 / 40 )731753.07510117.510508675572.3254079521378
Winsorized Mean ( 15 / 40 )731374.4510007.172930736573.0850216202043
Winsorized Mean ( 16 / 40 )732496.1833333339849.6417523256874.3677995354884
Winsorized Mean ( 17 / 40 )733268.6916666679623.627891494476.1946222291853
Winsorized Mean ( 18 / 40 )734303.5416666679481.141376909777.448854781871
Winsorized Mean ( 19 / 40 )735080.0083333339270.6995329997679.2906733431237
Winsorized Mean ( 20 / 40 )735544.3416666679195.7623516150379.9873151938822
Winsorized Mean ( 21 / 40 )734292.5666666678994.6127120403981.6369298128564
Winsorized Mean ( 22 / 40 )734220.158829.162848036683.158523932229
Winsorized Mean ( 23 / 40 )734790.9333333338757.9883288601283.8995104517305
Winsorized Mean ( 24 / 40 )735039.1333333338415.6025105726787.3424252642506
Winsorized Mean ( 25 / 40 )735355.1758261.1135461402389.0140500905684
Winsorized Mean ( 26 / 40 )736147.9583333338158.7658214798290.2278573059733
Winsorized Mean ( 27 / 40 )735381.8333333338042.8498181108291.43299327527
Winsorized Mean ( 28 / 40 )735869.7333333337838.3841999170293.8802838142487
Winsorized Mean ( 29 / 40 )735241.8833333337624.0942706241996.4366201722134
Winsorized Mean ( 30 / 40 )736022.8833333337387.06814487799.6366716670635
Winsorized Mean ( 31 / 40 )737084.1166666677238.82386814345101.823739614721
Winsorized Mean ( 32 / 40 )738036.9166666676898.90911442739106.978785257983
Winsorized Mean ( 33 / 40 )737534.7666666676541.02903181607112.755158718795
Winsorized Mean ( 34 / 40 )736699.2166666676175.71299638764119.289743078667
Winsorized Mean ( 35 / 40 )736762.2166666676121.08049662019120.364732513071
Winsorized Mean ( 36 / 40 )736911.6166666676064.25658296937121.517222529169
Winsorized Mean ( 37 / 40 )739403.5666666675685.87405126542130.042199317114
Winsorized Mean ( 38 / 40 )738641.9833333335587.20403388351132.202435932866
Winsorized Mean ( 39 / 40 )739873.4083333335209.19349422668142.032237649327
Winsorized Mean ( 40 / 40 )738344.4083333335040.26211558158146.489287938181
Trimmed Mean ( 1 / 40 )715490.38135593215390.295854886346.4897093663583
Trimmed Mean ( 2 / 40 )717360.7413793114863.329612890548.2637982244010
Trimmed Mean ( 3 / 40 )719211.9473684214299.023831041850.2979752930462
Trimmed Mean ( 4 / 40 )721212.7513704.98664336752.6241118482998
Trimmed Mean ( 5 / 40 )723324.60909090913053.826879336155.4109239977674
Trimmed Mean ( 6 / 40 )725306.48148148112507.178967700757.9912131548257
Trimmed Mean ( 7 / 40 )727304.40566037711917.646816209161.0275180055828
Trimmed Mean ( 8 / 40 )729323.46153846211281.282478618464.6489849820496
Trimmed Mean ( 9 / 40 )731276.29411764710709.572196599068.2824935201312
Trimmed Mean ( 10 / 40 )733196.7410163.297877032772.141616714482
Trimmed Mean ( 11 / 40 )733897.0918367359946.603243444173.7836901577887
Trimmed Mean ( 12 / 40 )734639.3333333339712.46225135175.6388353768011
Trimmed Mean ( 13 / 40 )734957.148936179563.8176195288576.847675078561
Trimmed Mean ( 14 / 40 )735219.4673913049423.6297227789578.018713491482
Trimmed Mean ( 15 / 40 )735549.69295.0991146147579.1330561331498
Trimmed Mean ( 16 / 40 )735929.1590909099162.2947445991280.321489278078
Trimmed Mean ( 17 / 40 )736228.5465116289030.9525294682881.5228010676937
Trimmed Mean ( 18 / 40 )736477.2738095248909.218515337482.6646324300682
Trimmed Mean ( 19 / 40 )7366548786.6117399035583.838232734759
Trimmed Mean ( 20 / 40 )736778.26258670.9328992304484.9710487974587
Trimmed Mean ( 21 / 40 )736873.179487188545.0076256992386.234350133407
Trimmed Mean ( 22 / 40 )737067.2105263168422.7026756806487.5095843825157
Trimmed Mean ( 23 / 40 )737277.0675675688299.5404535340788.8334808047864
Trimmed Mean ( 24 / 40 )737457.2222222228162.8596018783490.3429996581746
Trimmed Mean ( 25 / 40 )737629.9428571438045.5000450114891.682299264233
Trimmed Mean ( 26 / 40 )737790.5147058827925.0132985404193.0964386951584
Trimmed Mean ( 27 / 40 )737905.3787878797793.6047692146394.6808826773799
Trimmed Mean ( 28 / 40 )738080.6257650.3449810526296.4767767764698
Trimmed Mean ( 29 / 40 )738233.4516129037505.5958214835998.3577412335242
Trimmed Mean ( 30 / 40 )738439.7666666677359.60429671066100.336884551892
Trimmed Mean ( 31 / 40 )738606.4482758627215.70211867425102.360994970170
Trimmed Mean ( 32 / 40 )738711.6785714297060.41509794321104.627230598188
Trimmed Mean ( 33 / 40 )738758.5370370376921.07044742099106.740502448190
Trimmed Mean ( 34 / 40 )738844.1153846156802.7457928222108.609690540575
Trimmed Mean ( 35 / 40 )738995.526709.76205686817110.137366084921
Trimmed Mean ( 36 / 40 )739155.0416666676595.84182021817112.063791372459
Trimmed Mean ( 37 / 40 )739317.6086956526455.66080591614114.522375156099
Trimmed Mean ( 38 / 40 )739311.2727272736343.02420413919116.555013654974
Trimmed Mean ( 39 / 40 )739361.5952380956209.34574339718119.072383112876
Trimmed Mean ( 40 / 40 )739322.2256105.85443006446121.084155128178
Median733300
Midrange611019.5
Midmean - Weighted Average at Xnp736645.672131148
Midmean - Weighted Average at X(n+1)p738439.766666667
Midmean - Empirical Distribution Function736645.672131148
Midmean - Empirical Distribution Function - Averaging738439.766666667
Midmean - Empirical Distribution Function - Interpolation738439.766666667
Midmean - Closest Observation736645.672131148
Midmean - True Basic - Statistics Graphics Toolkit738439.766666667
Midmean - MS Excel (old versions)738233.451612903
Number of observations120
 
Charts produced by software:
http://www.freestatistics.org/blog/date/2010/Mar/12/t1268420717a1zxhz91mpenub4/1c6zv1268420674.png (open in new window)
http://www.freestatistics.org/blog/date/2010/Mar/12/t1268420717a1zxhz91mpenub4/1c6zv1268420674.ps (open in new window)


http://www.freestatistics.org/blog/date/2010/Mar/12/t1268420717a1zxhz91mpenub4/2gz8d1268420674.png (open in new window)
http://www.freestatistics.org/blog/date/2010/Mar/12/t1268420717a1zxhz91mpenub4/2gz8d1268420674.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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