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Central Tendency Paper

*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, 19 Dec 2009 04:41:24 -0700
 
Cite this page as follows:
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2009/Dec/19/t1261223217nvh8wzwoggg7tl1.htm/, Retrieved Sat, 19 Dec 2009 12:46:59 +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/Dec/19/t1261223217nvh8wzwoggg7tl1.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 «
7.5 7.2 7 6.9 7 6.9 6.9 6.9 6.8 7 6.8 6.8 6.7 6.4 6.2 6.1 6.2 6.5 6.6 6.5 6.2 6.2 6.6 7.1 7.3 7.4 7.4 7.4 7.4 7.3 7.3 7.4 7.6 7.6 7.6 7.6 7.8 7.9 8.1 8.2 8.2 8.1 8.1 8.1 8.1 8.1 8.2 8.3 8.4 8.5 8.6 8.5 8.3 7.8 7.8 8 8.6 8.9 8.9 8.3 8.3 8.3 8.4 8.5 8.4 8.6 8.5 8.5 8.4 8.5 8.5 8.5 8.5 8.5 8.5 8.5 8.5 8.6 8.4 8.1 8 8 8 8 7.9 7.8 7.8 7.9 8.1 8 7.6 7.3 7 6.8 7 7.1 7.2 7.1 6.9 6.7 6.7 6.6 6.9 7.3 7.4 7.3 7 6.9 7.1 7.5 7.7 7.9 7.8 7.7 7.8 7.8 7.9 8 8.1
 
Output produced by software:


Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135


Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean7.636134453781510.0644317252521407118.515132473933
Geometric Mean7.60324224414912
Harmonic Mean7.56958163667955
Quadratic Mean7.6681432021101
Winsorized Mean ( 1 / 39 )7.636974789915970.064267209705234118.831591179133
Winsorized Mean ( 2 / 39 )7.631932773109240.0635211932566545120.147818103365
Winsorized Mean ( 3 / 39 )7.631932773109240.0635211932566545120.147818103365
Winsorized Mean ( 4 / 39 )7.631932773109240.0635211932566545120.147818103365
Winsorized Mean ( 5 / 39 )7.640336134453780.0620051333238768123.2210258229
Winsorized Mean ( 6 / 39 )7.640336134453780.0605406883290668126.201672715133
Winsorized Mean ( 7 / 39 )7.640336134453780.0605406883290668126.201672715133
Winsorized Mean ( 8 / 39 )7.647058823529410.0595025613412543128.516464689186
Winsorized Mean ( 9 / 39 )7.647058823529410.0595025613412543128.516464689186
Winsorized Mean ( 10 / 39 )7.647058823529410.0595025613412543128.516464689186
Winsorized Mean ( 11 / 39 )7.65630252100840.0581688804417584131.621968015600
Winsorized Mean ( 12 / 39 )7.65630252100840.0581688804417584131.621968015600
Winsorized Mean ( 13 / 39 )7.65630252100840.0581688804417584131.621968015600
Winsorized Mean ( 14 / 39 )7.668067226890760.0565838082048242135.516987459268
Winsorized Mean ( 15 / 39 )7.668067226890760.0565838082048242135.516987459268
Winsorized Mean ( 16 / 39 )7.668067226890760.0565838082048242135.516987459268
Winsorized Mean ( 17 / 39 )7.668067226890760.0565838082048242135.516987459268
Winsorized Mean ( 18 / 39 )7.683193277310920.0546814176729923140.508304361424
Winsorized Mean ( 19 / 39 )7.66722689075630.0527293687805989145.407143458493
Winsorized Mean ( 20 / 39 )7.66722689075630.0527293687805989145.407143458493
Winsorized Mean ( 21 / 39 )7.66722689075630.0527293687805989145.407143458493
Winsorized Mean ( 22 / 39 )7.66722689075630.0527293687805989145.407143458493
Winsorized Mean ( 23 / 39 )7.66722689075630.0527293687805989145.407143458493
Winsorized Mean ( 24 / 39 )7.647058823529410.0504335784283544151.626338281603
Winsorized Mean ( 25 / 39 )7.668067226890760.0478706652177604160.183009615790
Winsorized Mean ( 26 / 39 )7.668067226890760.0478706652177604160.183009615790
Winsorized Mean ( 27 / 39 )7.668067226890760.0478706652177604160.183009615790
Winsorized Mean ( 28 / 39 )7.668067226890760.0478706652177604160.183009615790
Winsorized Mean ( 29 / 39 )7.64369747899160.0452349679936483168.977625452612
Winsorized Mean ( 30 / 39 )7.64369747899160.0452349679936483168.977625452612
Winsorized Mean ( 31 / 39 )7.669747899159660.0421700665903578181.876589706723
Winsorized Mean ( 32 / 39 )7.642857142857140.0394119180682192193.922486330858
Winsorized Mean ( 33 / 39 )7.642857142857140.0394119180682192193.922486330858
Winsorized Mean ( 34 / 39 )7.642857142857140.0394119180682192193.922486330858
Winsorized Mean ( 35 / 39 )7.672268907563030.0360593516379148212.767799726493
Winsorized Mean ( 36 / 39 )7.672268907563030.0360593516379148212.767799726493
Winsorized Mean ( 37 / 39 )7.703361344537820.0327040127064016235.547894800993
Winsorized Mean ( 38 / 39 )7.703361344537820.0327040127064016235.547894800993
Winsorized Mean ( 39 / 39 )7.703361344537810.0327040127064016235.547894800993
Trimmed Mean ( 1 / 39 )7.638461538461540.0632740444931607120.720298499129
Trimmed Mean ( 2 / 39 )7.640.0621727128590694122.883490982902
Trimmed Mean ( 3 / 39 )7.644247787610620.0613782140998175124.543340006260
Trimmed Mean ( 4 / 39 )7.648648648648650.0604902827545297126.444253528901
Trimmed Mean ( 5 / 39 )7.653211009174310.0594968255596971128.632257892404
Trimmed Mean ( 6 / 39 )7.656074766355140.0587919525729941130.223175643803
Trimmed Mean ( 7 / 39 )7.659047619047620.0583298571140343131.305784001395
Trimmed Mean ( 8 / 39 )7.66213592233010.0578028530175635132.556362226652
Trimmed Mean ( 9 / 39 )7.664356435643560.0573953487337519133.536194216666
Trimmed Mean ( 10 / 39 )7.666666666666670.056925995422607134.677779628637
Trimmed Mean ( 11 / 39 )7.669072164948450.0563867814767394136.008333231647
Trimmed Mean ( 12 / 39 )7.670526315789470.0559729914914983137.039777782014
Trimmed Mean ( 13 / 39 )7.672043010752690.0554923054064414138.254176945082
Trimmed Mean ( 14 / 39 )7.673626373626370.0549355303099912139.684214029163
Trimmed Mean ( 15 / 39 )7.674157303370790.0545088594229086140.787339610807
Trimmed Mean ( 16 / 39 )7.674712643678160.0540084836664699142.101983293467
Trimmed Mean ( 17 / 39 )7.675294117647060.0534235725296331143.668679465225
Trimmed Mean ( 18 / 39 )7.675903614457830.0527412069886702145.539020677072
Trimmed Mean ( 19 / 39 )7.675308641975310.0521906188118869147.062993631859
Trimmed Mean ( 20 / 39 )7.67594936708860.0517846134087366148.228380243032
Trimmed Mean ( 21 / 39 )7.676623376623380.0512954566058997149.655035446950
Trimmed Mean ( 22 / 39 )7.677333333333330.0507093229636862151.398853004431
Trimmed Mean ( 23 / 39 )7.678082191780820.0500093817432104153.532835722834
Trimmed Mean ( 24 / 39 )7.678873239436620.0491749021129467156.154316724403
Trimmed Mean ( 25 / 39 )7.681159420289860.0484752757011268158.455198226161
Trimmed Mean ( 26 / 39 )7.68208955223880.047976954984271160.120406865282
Trimmed Mean ( 27 / 39 )7.683076923076920.0473616015541614162.221645192694
Trimmed Mean ( 28 / 39 )7.684126984126980.046605531010491164.875859528288
Trimmed Mean ( 29 / 39 )7.685245901639340.0456786150999819168.246035586188
Trimmed Mean ( 30 / 39 )7.688135593220340.0449094644658914171.191878697629
Trimmed Mean ( 31 / 39 )7.691228070175440.0439497820737175.000368768107
Trimmed Mean ( 32 / 39 )7.692727272727270.043255917284983177.842194908162
Trimmed Mean ( 33 / 39 )7.696226415094340.0427605361914107179.984329023458
Trimmed Mean ( 34 / 39 )7.70.042101651031852182.890689825313
Trimmed Mean ( 35 / 39 )7.704081632653060.0412350966350546186.833116964341
Trimmed Mean ( 36 / 39 )7.70638297872340.0407383582479655189.167735523762
Trimmed Mean ( 37 / 39 )7.708888888888890.0400532754082801192.465879764112
Trimmed Mean ( 38 / 39 )7.70930232558140.0397687046874545193.853493247251
Trimmed Mean ( 39 / 39 )7.709756097560980.0393243048484572196.055750439119
Median7.8
Midrange7.5
Midmean - Weighted Average at Xnp7.64307692307692
Midmean - Weighted Average at X(n+1)p7.64307692307692
Midmean - Empirical Distribution Function7.64307692307692
Midmean - Empirical Distribution Function - Averaging7.64307692307692
Midmean - Empirical Distribution Function - Interpolation7.64307692307692
Midmean - Closest Observation7.64307692307692
Midmean - True Basic - Statistics Graphics Toolkit7.64307692307692
Midmean - MS Excel (old versions)7.64307692307692
Number of observations119
 
Charts produced by software:
http://www.freestatistics.org/blog/date/2009/Dec/19/t1261223217nvh8wzwoggg7tl1/1z3qo1261222882.png (open in new window)
http://www.freestatistics.org/blog/date/2009/Dec/19/t1261223217nvh8wzwoggg7tl1/1z3qo1261222882.ps (open in new window)


http://www.freestatistics.org/blog/date/2009/Dec/19/t1261223217nvh8wzwoggg7tl1/2d5gv1261222882.png (open in new window)
http://www.freestatistics.org/blog/date/2009/Dec/19/t1261223217nvh8wzwoggg7tl1/2d5gv1261222882.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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