Home » date » 2008 » Dec » 13 »

Central tendency toegepast op het aantal mannelijke werklozen in het Vlaamse Gewest

*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: Sat, 13 Dec 2008 05:37:12 -0700
 
Cite this page as follows:
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2008/Dec/13/t122917189300bi382rmxe64ps.htm/, Retrieved Sat, 13 Dec 2008 13:38:13 +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/2008/Dec/13/t122917189300bi382rmxe64ps.htm/},
    year = {2008},
}
@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 = {2008},
    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:
 
Dataseries X:
» Textbox « » Textfile « » CSV «
93803 90684 87251 83606 79695 75858 89756 98707 89871 84625 81979 84525 85826 82652 81514 77360 74095 71637 84186 92713 81321 76536 73038 74940 74654 71999 68611 67430 65460 63421 76226 84540 74255 70680 67409 67938 70051 68043 67383 67028 65478 65133 78443 85418 84786 83684 80369 82361 83071 81881 80767 78375 76381 76068 94619 99126 93632 91541 90445 91621 93856 91738 89952 89365 87146 88689 108165 113374 106099 103235 98857 101107 102700 101477 99639 96622 94697 95093 112885 121162 113624 111632 106707 108827 108413 106249 104861 102382 100320 100228 117089 121523 114948 112831 107605 108928 101993 102850 99925 101536 99450 98305 110159 109483 106810 96279 91982 90276 90999 86622 83117 80367 77550 77443 92844 92175 84822 81632 78872 81485
 
Output produced by software:


Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24


Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean89529.21666666671289.6868617715869.4193445870143
Geometric Mean88421.479568847
Harmonic Mean87315.9755050519
Quadratic Mean90627.8787620932
Winsorized Mean ( 1 / 40 )89540.4751286.7120020911069.5885908070209
Winsorized Mean ( 2 / 40 )89478.04166666671272.6432755403770.3088158216793
Winsorized Mean ( 3 / 40 )89424.96666666671263.1470194905370.7953747955126
Winsorized Mean ( 4 / 40 )89432.51247.7893490745471.6727547533005
Winsorized Mean ( 5 / 40 )89436.8751243.8806840855971.9014903473215
Winsorized Mean ( 6 / 40 )89413.7251239.7649819054072.1215119841341
Winsorized Mean ( 7 / 40 )89411.81239.0815911148872.1597355986467
Winsorized Mean ( 8 / 40 )89365.73333333331221.5898571510473.1552679569144
Winsorized Mean ( 9 / 40 )89263.13333333331203.9059089753474.1446093651177
Winsorized Mean ( 10 / 40 )89254.13333333331188.8103007726575.0785329461933
Winsorized Mean ( 11 / 40 )89335.25833333331162.7364918627276.8319038393791
Winsorized Mean ( 12 / 40 )89388.05833333331152.6325187546777.5512202535377
Winsorized Mean ( 13 / 40 )89446.88333333331132.3745431208078.9905459079114
Winsorized Mean ( 14 / 40 )89460.18333333331122.7622757595779.67865082821
Winsorized Mean ( 15 / 40 )89520.05833333331096.3160566095081.65533816059
Winsorized Mean ( 16 / 40 )89554.99166666671064.2369118533984.1494883979404
Winsorized Mean ( 17 / 40 )89563.06666666671059.4912253271884.5340334357267
Winsorized Mean ( 18 / 40 )89554.21666666671042.9732528632585.8643463970105
Winsorized Mean ( 19 / 40 )89575.751034.3713887782186.5992147228722
Winsorized Mean ( 20 / 40 )89522.4166666667989.08706078241190.5101484148933
Winsorized Mean ( 21 / 40 )89274.6166666667948.64946463294194.1070648273749
Winsorized Mean ( 22 / 40 )89233936.58837476956895.2745116251889
Winsorized Mean ( 23 / 40 )89233.9583333333929.6228681278295.989418282107
Winsorized Mean ( 24 / 40 )89201.3583333333918.31891386513597.1354907173713
Winsorized Mean ( 25 / 40 )89291.9833333333888.931987358384100.448610920932
Winsorized Mean ( 26 / 40 )89210.95875.097150897204101.944052621512
Winsorized Mean ( 27 / 40 )89221.75870.810467359589102.458288392573
Winsorized Mean ( 28 / 40 )89327.9166666667839.211219759492106.442710206218
Winsorized Mean ( 29 / 40 )89154.1583333333815.23742275585109.35974704394
Winsorized Mean ( 30 / 40 )89238.4083333333800.833025369974111.431978335442
Winsorized Mean ( 31 / 40 )89372.7416666667768.994481380962116.220264033847
Winsorized Mean ( 32 / 40 )89475.675741.475446078699120.672471992422
Winsorized Mean ( 33 / 40 )89424.25735.448170042817121.591505210753
Winsorized Mean ( 34 / 40 )89445.2166666667713.356332535525125.386447960371
Winsorized Mean ( 35 / 40 )89528.3416666667688.05241941451130.118489726189
Winsorized Mean ( 36 / 40 )89532.5416666667678.010802705127132.051792256775
Winsorized Mean ( 37 / 40 )89417.5333333333663.088865498499134.849999729841
Winsorized Mean ( 38 / 40 )88921.95600.522794279767148.074229399815
Winsorized Mean ( 39 / 40 )88891.4580.318196836728153.176999247207
Winsorized Mean ( 40 / 40 )88528.7333333333535.440866250576165.338021270688
Trimmed Mean ( 1 / 40 )89479.33898305091263.6700850157270.8090980739945
Trimmed Mean ( 2 / 40 )89416.09482758621238.1152769945172.2195230840224
Trimmed Mean ( 3 / 40 )89383.49122807021217.9591207625773.387923867352
Trimmed Mean ( 4 / 40 )89368.67857142861199.4083759314674.510634046577
Trimmed Mean ( 5 / 40 )89351.27272727271183.6026033204775.4909396757045
Trimmed Mean ( 6 / 40 )89332.251166.9721008822976.5504590319343
Trimmed Mean ( 7 / 40 )89316.87735849061149.3132772620077.7132563640695
Trimmed Mean ( 8 / 40 )89301.23076923081129.6580609286779.0515589255546
Trimmed Mean ( 9 / 40 )89291.74509803921110.9493679258380.37427057972
Trimmed Mean ( 10 / 40 )89295.561093.0387166172381.6947823004428
Trimmed Mean ( 11 / 40 )89300.63265306121075.3476051928883.0435035348816
Trimmed Mean ( 12 / 40 )89296.69791666671059.4547860416884.2855203385279
Trimmed Mean ( 13 / 40 )89286.97872340431042.9283993024485.611801139104
Trimmed Mean ( 14 / 40 )89270.93478260871027.0656522299586.9184307631992
Trimmed Mean ( 15 / 40 )89252.91111111111010.3080158063788.3422775180838
Trimmed Mean ( 16 / 40 )89228.625994.77547866601589.6972501972554
Trimmed Mean ( 17 / 40 )89200.1627906977981.21968850834190.9074326935903
Trimmed Mean ( 18 / 40 )89169.6666666667966.1574560452792.2930999587386
Trimmed Mean ( 19 / 40 )89138.4024390244950.8863965441593.7424310232896
Trimmed Mean ( 20 / 40 )89103.875934.2502318374395.3747421873855
Trimmed Mean ( 21 / 40 )89071.6794871795920.80907475204596.7319740101005
Trimmed Mean ( 22 / 40 )89056.4210526316910.24485105067597.8378740070166
Trimmed Mean ( 23 / 40 )89043.4054054054899.1969931424799.0254705970721
Trimmed Mean ( 24 / 40 )89029.5972222222886.889660012704100.384073956784
Trimmed Mean ( 25 / 40 )89017.3285714286873.651031554596101.891173198787
Trimmed Mean ( 26 / 40 )88997.9411764706861.615423624454103.291954549854
Trimmed Mean ( 27 / 40 )88983.0454545455848.90636306658104.820801593599
Trimmed Mean ( 28 / 40 )88966.46875834.035897582785106.669831607781
Trimmed Mean ( 29 / 40 )88941.4838709677820.337861269633108.420552153126
Trimmed Mean ( 30 / 40 )88926.8166666667806.99818833997110.194567908006
Trimmed Mean ( 31 / 40 )88905.3275862069792.540892049386112.177590428567
Trimmed Mean ( 32 / 40 )88873.0178571429779.245070269717114.050150906160
Trimmed Mean ( 33 / 40 )88831.1666666667766.59218841137115.877996162150
Trimmed Mean ( 34 / 40 )88789.6923076923751.427962655556118.16128321058
Trimmed Mean ( 35 / 40 )88743.42735.714545958345120.622081604221
Trimmed Mean ( 36 / 40 )88687.3541666667719.719162187477123.224944987035
Trimmed Mean ( 37 / 40 )88626.1086956522700.641004803349126.492894489564
Trimmed Mean ( 38 / 40 )88567.7727272727678.788296638129130.479227714925
Trimmed Mean ( 39 / 40 )88541.1428571429663.788975789963133.387486213931
Trimmed Mean ( 40 / 40 )88514.2647.7176113883136.655540074449
Median89560.5
Midrange92472
Midmean - Weighted Average at Xnp88754.9508196721
Midmean - Weighted Average at X(n+1)p88926.8166666667
Midmean - Empirical Distribution Function88754.9508196721
Midmean - Empirical Distribution Function - Averaging88926.8166666667
Midmean - Empirical Distribution Function - Interpolation88926.8166666667
Midmean - Closest Observation88754.9508196721
Midmean - True Basic - Statistics Graphics Toolkit88926.8166666667
Midmean - MS Excel (old versions)88941.4838709677
Number of observations120
 
Charts produced by software:
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/13/t122917189300bi382rmxe64ps/1a1cz1229171827.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/13/t122917189300bi382rmxe64ps/1a1cz1229171827.ps (open in new window)


http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/13/t122917189300bi382rmxe64ps/25zp71229171827.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/13/t122917189300bi382rmxe64ps/25zp71229171827.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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