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central tendency

*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: Mon, 26 Oct 2009 12:36:16 -0600
 
Cite this page as follows:
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2009/Oct/26/t1256582461c6sz74gby6vqyuu.htm/, Retrieved Mon, 26 Oct 2009 19:41:03 +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/2009/Oct/26/t1256582461c6sz74gby6vqyuu.htm/},
    year = {2009},
}
@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 = {2009},
    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:
central tendency
 
Dataseries X:
» Textbox « » Textfile « » CSV «
376643 370037 358182 356625 348675 347652 368859 381303 367753 361112 350758 350754 357631 354425 346660 345181 342994 339946 361758 370490 373040 371009 354179 357361 363037 364153 363434 358410 356551 357445 379570 377613 376404 379665 378899 384098 392105 394149 392231 395590 392491 395893 418584 420585 420064 417696 409837 417869 426174 427853 429778 423952 422504 426529 440727 449002 451671 461854 454959 460866 460543 462768 462027 455748 455321 456149 472006 471654 471011 465436 458880 465030 468082 467356 463184 460486 462038 460849 476002 475863 470769 453286 443059 441660 444010 437582 427064 424117 416496 405611 431233 434217 417711 412099 404315 409339 412140 406280 398077 396995 385326 390094 412512 413263 400937 397363 397347 409383 418885 423560 428029 430001 424400 432721 455894 459146 445819
 
Output produced by software:


Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time7 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135


Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean411080.7008547013660.31221372641112.307551064393
Geometric Mean409169.865349469
Harmonic Mean407244.750002985
Quadratic Mean412966.702451201
Winsorized Mean ( 1 / 39 )411105.5641025643655.85632184509112.451236566945
Winsorized Mean ( 2 / 39 )411077.0170940173640.14562534764112.928728518865
Winsorized Mean ( 3 / 39 )411105.9145299153632.98728207844113.159194516838
Winsorized Mean ( 4 / 39 )411117.8461538463624.6896287675113.421530740451
Winsorized Mean ( 5 / 39 )411151.2222222223616.66353235472113.682464112035
Winsorized Mean ( 6 / 39 )411120.0427350433581.74084450799114.782185697613
Winsorized Mean ( 7 / 39 )411076.8461538463575.78182458486114.961389234527
Winsorized Mean ( 8 / 39 )411179.4786324793524.8465010923116.651740297077
Winsorized Mean ( 9 / 39 )411167.1709401713518.0788741827116.87264147416
Winsorized Mean ( 10 / 39 )411191.1025641033472.52401541502118.412745524226
Winsorized Mean ( 11 / 39 )411158.9487179493466.54644328036118.607656191928
Winsorized Mean ( 12 / 39 )411159.5641025643446.78059969219119.287999978670
Winsorized Mean ( 13 / 39 )411167.6752136753445.36985222644119.339198068380
Winsorized Mean ( 14 / 39 )411169.2307692313439.74891863512119.534663865054
Winsorized Mean ( 15 / 39 )411113.2051282053414.28795865178120.409646200593
Winsorized Mean ( 16 / 39 )411142.059829063409.83399541071120.575388826088
Winsorized Mean ( 17 / 39 )411490.1965811973352.63194743826122.736465866948
Winsorized Mean ( 18 / 39 )411580.8119658123338.6954118619123.275939010047
Winsorized Mean ( 19 / 39 )411570.9059829063284.78120133890125.296292433464
Winsorized Mean ( 20 / 39 )411593.2991452993270.4793303791125.851062662912
Winsorized Mean ( 21 / 39 )411232.1709401713193.81560284321128.758895965717
Winsorized Mean ( 22 / 39 )411861.1452991453103.47596863048132.709629287348
Winsorized Mean ( 23 / 39 )412049.8632478633073.47231153862134.066561036167
Winsorized Mean ( 24 / 39 )412203.9145299153033.62315209197135.878417939176
Winsorized Mean ( 25 / 39 )412223.3589743593012.57564285105136.834193674964
Winsorized Mean ( 26 / 39 )411966.9145299152953.64218879407139.477596877811
Winsorized Mean ( 27 / 39 )412062.9145299152853.21494316032144.420565130470
Winsorized Mean ( 28 / 39 )412229.2393162392683.43024556171153.620255267693
Winsorized Mean ( 29 / 39 )411499.529914532584.79854881507159.199845613954
Winsorized Mean ( 30 / 39 )411284.4017094022503.2299251012164.301488083550
Winsorized Mean ( 31 / 39 )411373.1623931622435.55988188526168.902914460365
Winsorized Mean ( 32 / 39 )411174.0512820512371.8132135788173.358529638021
Winsorized Mean ( 33 / 39 )410937.6923076922339.70842365686175.636283629486
Winsorized Mean ( 34 / 39 )410499.7606837612185.86989304231187.796978214666
Winsorized Mean ( 35 / 39 )410329.2478632481983.98668428265206.820565437218
Winsorized Mean ( 36 / 39 )410246.7863247861893.57169829233216.652364784897
Winsorized Mean ( 37 / 39 )411284.0512820511677.5421260614245.170624863937
Winsorized Mean ( 38 / 39 )411537.059829061566.17965431552262.764912502274
Winsorized Mean ( 39 / 39 )411504.7264957261554.14387047916264.779042862264
Trimmed Mean ( 1 / 39 )411134.7304347833628.02093357809113.322039194880
Trimmed Mean ( 2 / 39 )411164.929203543596.77297003796114.314951938487
Trimmed Mean ( 3 / 39 )411211.2612612613570.65207170228115.164192142983
Trimmed Mean ( 4 / 39 )411248.9541284403543.95409795097116.042404264269
Trimmed Mean ( 5 / 39 )411284.7943925233516.28606822377116.965680952199
Trimmed Mean ( 6 / 39 )411314.5619047623486.98619694931117.957037588681
Trimmed Mean ( 7 / 39 )411351.3883495153461.55644436981118.834228174604
Trimmed Mean ( 8 / 39 )411396.8217821783433.65012606078119.813261887037
Trimmed Mean ( 9 / 39 )411428.9292929293411.03489620553120.617039054806
Trimmed Mean ( 10 / 39 )411464.0103092783385.99410675163121.519411238438
Trimmed Mean ( 11 / 39 )411497.6210526323364.24729828630122.314914620647
Trimmed Mean ( 12 / 39 )411536.354838713339.72106403582123.224768460572
Trimmed Mean ( 13 / 39 )411576.7252747253313.97010398059124.194459322478
Trimmed Mean ( 14 / 39 )411618.0898876403284.09304618740125.336914666745
Trimmed Mean ( 15 / 39 )411618.0898876403250.065241676126.649177564010
Trimmed Mean ( 16 / 39 )411711.4941176473213.90635866191128.103139348795
Trimmed Mean ( 17 / 39 )411761.6626506023172.36017797756129.796630757453
Trimmed Mean ( 18 / 39 )411784.7283950623131.61997067725131.492560480130
Trimmed Mean ( 19 / 39 )411801.5063291143085.78877492891133.450970356388
Trimmed Mean ( 20 / 39 )411819.9480519483039.26314047994135.499931732438
Trimmed Mean ( 21 / 39 )411837.6266666672986.44857933892137.902132156527
Trimmed Mean ( 22 / 39 )411883.8356164382934.543375823140.357044646145
Trimmed Mean ( 23 / 39 )411885.5352112682885.39840892061142.748236755751
Trimmed Mean ( 24 / 39 )411873.4202898552830.93695967482145.49014201191
Trimmed Mean ( 25 / 39 )411849.3731343282771.43096671605148.605315477997
Trimmed Mean ( 26 / 39 )411822.4461538462703.07622575212152.353249320321
Trimmed Mean ( 27 / 39 )411812.1269841272629.66715320732156.602377027775
Trimmed Mean ( 28 / 39 )411794.311475412556.38845953297161.084404030928
Trimmed Mean ( 29 / 39 )411763.5084745762493.80319934470165.114676484005
Trimmed Mean ( 30 / 39 )411763.5084745762432.57174040246169.270859163419
Trimmed Mean ( 31 / 39 )411817.4909090912369.99508500431173.763014748337
Trimmed Mean ( 32 / 39 )411849.1320754722303.40284433868178.800305421051
Trimmed Mean ( 33 / 39 )411897.5294117652230.94652740041184.629046170696
Trimmed Mean ( 34 / 39 )411966.9795918372144.97429846205192.061499239044
Trimmed Mean ( 35 / 39 )412074.4042553192065.57620908568199.496103045127
Trimmed Mean ( 36 / 39 )412204.0444444442003.86875010113205.704113317622
Trimmed Mean ( 37 / 39 )412351.9767441861941.3257088235212.407415649012
Trimmed Mean ( 38 / 39 )412434.3414634151905.41040922235216.454334177665
Trimmed Mean ( 39 / 39 )412505.1794871791878.94440850317219.540917560086
Median413263
Midrange407974
Midmean - Weighted Average at Xnp411176.344827586
Midmean - Weighted Average at X(n+1)p411763.508474576
Midmean - Empirical Distribution Function411763.508474576
Midmean - Empirical Distribution Function - Averaging411763.508474576
Midmean - Empirical Distribution Function - Interpolation411763.508474576
Midmean - Closest Observation411174.183333333
Midmean - True Basic - Statistics Graphics Toolkit411763.508474576
Midmean - MS Excel (old versions)411763.508474576
Number of observations117
 
Charts produced by software:
http://www.freestatistics.org/blog/date/2009/Oct/26/t1256582461c6sz74gby6vqyuu/16du41256582168.png (open in new window)
http://www.freestatistics.org/blog/date/2009/Oct/26/t1256582461c6sz74gby6vqyuu/16du41256582168.ps (open in new window)


http://www.freestatistics.org/blog/date/2009/Oct/26/t1256582461c6sz74gby6vqyuu/2207i1256582168.png (open in new window)
http://www.freestatistics.org/blog/date/2009/Oct/26/t1256582461c6sz74gby6vqyuu/2207i1256582168.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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Software written by Ed van Stee & Patrick Wessa


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