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R Software Module: rwasp_centraltendency.wasp (opens new window with default values)
Title produced by software: Central Tendency
Date of computation: Sun, 20 Apr 2008 14:07:40 -0600
 
Cite this page as follows:
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2008/Apr/20/t1208722111ly8p9qr4nhjxsw8.htm/, Retrieved Sun, 20 Apr 2008 22:08:34 +0200
 
User-defined keywords:
 
Dataseries X:
» Textbox « » Textfile « » CSV «
118,4 118,3 118,4 118,6 118,6 116,5 117,7 117,3 117,1 116,9 116,2 113,7 115,2 115,6 115,8 115,2 115,3 113,4 114,6 114,7 114,3 113,7 113,6 111,5 113 113 112,8 113,2 113 111,1 112,4 112 112,4 112,6 112,3 110 111,1 111 111,2 111,3 111,2 109,6 110,7 111 110,8 110,7 110,5 108,7 109,7 109,8 109,8 110 109,8 108,4 109,8 109,5 109 108 107,8 105,9 107,6 107,9 107,7 107,9 107,1 105,5 106,6 106,2 105,9 105,7 105,2 103,1 104,5 104,1 103,9 103,8 103,5 103,7 103,5 103,7 103,5 103,1 103 102,8 102,4 102,5 102,5 102,5 102,6 103 102,8 102,9 102,4 101,8 102 101,8 101,7 101,9 101,8 101,7 101,6 101,8 101,6 101,6 101,1 100,8 101,2 101,3 100,8 100,6 100,6 100,1 99,9 99,9 100 100,2 100 99,5 99,3 99,2 98,7 98,5 98,4 98,6 98,7 98,4 98,1 98,1 98 97,9 97,9 97,8
 
Text written by user:
 
Output produced by software:


Summary of compuational 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 Mean106.8916666666670.529024610682421202.054241916610
Geometric Mean106.721445896646
Harmonic Mean106.552688294678
Quadratic Mean107.063023424750
Winsorized Mean ( 1 / 44 )106.8924242424240.528925758523147202.093436592853
Winsorized Mean ( 2 / 44 )106.8893939393940.528417801642298202.281970075926
Winsorized Mean ( 3 / 44 )106.8916666666670.528124183732221202.398734917363
Winsorized Mean ( 4 / 44 )106.8916666666670.527234284568325202.740356223580
Winsorized Mean ( 5 / 44 )106.8689393939390.523562474137919204.118791305481
Winsorized Mean ( 6 / 44 )106.8643939393940.519010710151176205.900170939183
Winsorized Mean ( 7 / 44 )106.8537878787880.517395080951687206.522620358591
Winsorized Mean ( 8 / 44 )106.8477272727270.514822470978081207.542858550314
Winsorized Mean ( 9 / 44 )106.8272727272730.509973500498869209.476124980556
Winsorized Mean ( 10 / 44 )106.8121212121210.505787726262451211.179741353978
Winsorized Mean ( 11 / 44 )106.7787878787880.501135687201661213.073605823285
Winsorized Mean ( 12 / 44 )106.8060606060610.493175444380871216.568083068580
Winsorized Mean ( 13 / 44 )106.7863636363640.488040847189705218.806200856493
Winsorized Mean ( 14 / 44 )106.7969696969700.484169878445103220.577475905657
Winsorized Mean ( 15 / 44 )106.8424242424240.479040361869365223.034284262587
Winsorized Mean ( 16 / 44 )106.7818181818180.471115510683369226.657403036736
Winsorized Mean ( 17 / 44 )106.7818181818180.468037894283746228.147804880692
Winsorized Mean ( 18 / 44 )106.7409090909090.462879474079631230.601949466755
Winsorized Mean ( 19 / 44 )106.6689393939390.450750694395968236.647310187468
Winsorized Mean ( 20 / 44 )106.6840909090910.449072900004244237.565194666796
Winsorized Mean ( 21 / 44 )106.7318181818180.440286111556862242.414683044196
Winsorized Mean ( 22 / 44 )106.6984848484850.436347351233117244.526486861797
Winsorized Mean ( 23 / 44 )106.6984848484850.428596935274588248.948314994662
Winsorized Mean ( 24 / 44 )106.6621212121210.424418790378621251.313381099288
Winsorized Mean ( 25 / 44 )106.7189393939390.418511252523985254.996583127292
Winsorized Mean ( 26 / 44 )106.7386363636360.416502138778228256.273921369875
Winsorized Mean ( 27 / 44 )106.7181818181820.409766579038084260.436519905308
Winsorized Mean ( 28 / 44 )106.7393939393940.398638321857876267.759992170168
Winsorized Mean ( 29 / 44 )106.6954545454550.393742788890585270.977545636026
Winsorized Mean ( 30 / 44 )106.6954545454550.393742788890585270.977545636026
Winsorized Mean ( 31 / 44 )106.6954545454550.388840491253978274.393888870397
Winsorized Mean ( 32 / 44 )106.6227272727270.380920137837324279.908350023389
Winsorized Mean ( 33 / 44 )106.5227272727270.365211068213256291.674422119447
Winsorized Mean ( 34 / 44 )106.4712121212120.359892950489408295.841338310253
Winsorized Mean ( 35 / 44 )106.4446969696970.357187710917344298.007724555589
Winsorized Mean ( 36 / 44 )106.4446969696970.357187710917344298.007724555589
Winsorized Mean ( 37 / 44 )106.4446969696970.351572447361317302.767460216534
Winsorized Mean ( 38 / 44 )106.4734848484850.348742594190389305.306798258081
Winsorized Mean ( 39 / 44 )106.5621212121210.334344747604950318.719291914916
Winsorized Mean ( 40 / 44 )106.5621212121210.334344747604950318.719291914916
Winsorized Mean ( 41 / 44 )106.5310606060610.325138331698192327.64841982688
Winsorized Mean ( 42 / 44 )106.4992424242420.321959246540883330.784854196505
Winsorized Mean ( 43 / 44 )106.4992424242420.321959246540883330.784854196505
Winsorized Mean ( 44 / 44 )106.4659090909090.312194943949064341.023809496029
Trimmed Mean ( 1 / 44 )106.8715384615380.524854223013295203.621374803783
Trimmed Mean ( 2 / 44 )106.850.520351089078818205.342128118070
Trimmed Mean ( 3 / 44 )106.8293650793650.515659623752585207.170311885078
Trimmed Mean ( 4 / 44 )106.8072580645160.510581929645514209.187305431413
Trimmed Mean ( 5 / 44 )106.7844262295080.505232102802209211.357167601269
Trimmed Mean ( 6 / 44 )106.7658333333330.500247131969674213.426177803266
Trimmed Mean ( 7 / 44 )106.7474576271190.495710576456861215.34230395104
Trimmed Mean ( 8 / 44 )106.7301724137930.490971285657022217.38577291942
Trimmed Mean ( 9 / 44 )106.7131578947370.486141609279092219.510438641497
Trimmed Mean ( 10 / 44 )106.6982142857140.481546505448185221.574059989093
Trimmed Mean ( 11 / 44 )106.6845454545450.477041176604502223.638022641794
Trimmed Mean ( 12 / 44 )106.6740740740740.472659141291335225.689222433387
Trimmed Mean ( 13 / 44 )106.6603773584910.468805289392721227.515302774539
Trimmed Mean ( 14 / 44 )106.6480769230770.465110145332608229.296389238749
Trimmed Mean ( 15 / 44 )106.6343137254900.461385013886136231.117852804396
Trimmed Mean ( 16 / 44 )106.6160.457738666564981232.918929047618
Trimmed Mean ( 17 / 44 )106.6020408163270.454518839582154234.538222693535
Trimmed Mean ( 18 / 44 )106.58750.451149239127046236.257740800455
Trimmed Mean ( 19 / 44 )106.5755319148940.447846690179638237.973248997653
Trimmed Mean ( 20 / 44 )106.5684782608700.445374725726412239.278234944866
Trimmed Mean ( 21 / 44 )106.560.442616778922546240.750023664708
Trimmed Mean ( 22 / 44 )106.5477272727270.440287551120516241.995775264522
Trimmed Mean ( 23 / 44 )106.5372093023260.437909617543562243.285840352039
Trimmed Mean ( 24 / 44 )106.5261904761900.435857379573638244.406072877316
Trimmed Mean ( 25 / 44 )106.5170731707320.433777150521452245.557132372430
Trimmed Mean ( 26 / 44 )106.503750.431803121709097246.648865294102
Trimmed Mean ( 27 / 44 )106.4884615384620.429521571577399247.923430591361
Trimmed Mean ( 28 / 44 )106.4736842105260.42740903791088249.114255353504
Trimmed Mean ( 29 / 44 )106.4567567567570.425919225355598249.945882738392
Trimmed Mean ( 30 / 44 )106.4416666666670.424465741708555250.766213165328
Trimmed Mean ( 31 / 44 )106.4257142857140.4224726862882251.911467273208
Trimmed Mean ( 32 / 44 )106.4088235294120.420401242836611253.112533187176
Trimmed Mean ( 33 / 44 )106.3954545454550.418613717374154254.161414520392
Trimmed Mean ( 34 / 44 )106.38750.418030506025881254.496976814925
Trimmed Mean ( 35 / 44 )106.3822580645160.417558339217619254.772203241935
Trimmed Mean ( 36 / 44 )106.3783333333330.416876274960851255.17962935963
Trimmed Mean ( 37 / 44 )106.3741379310340.41558827425869255.960392820949
Trimmed Mean ( 38 / 44 )106.3696428571430.414289562790006256.751925249585
Trimmed Mean ( 39 / 44 )106.3629629629630.412575692788848257.802301061392
Trimmed Mean ( 40 / 44 )106.350.411903391856911258.191610223361
Trimmed Mean ( 41 / 44 )106.3360.410432922258278259.082530258342
Trimmed Mean ( 42 / 44 )106.3229166666670.409367696820064259.724735225996
Trimmed Mean ( 43 / 44 )106.3108695652170.407824773645177260.677811735174
Trimmed Mean ( 44 / 44 )106.2977272727270.405100784008979262.398226487686
Median106.05
Midrange108.2
Midmean - Weighted Average at Xnp106.257352941176
Midmean - Weighted Average at X(n+1)p106.395454545455
Midmean - Empirical Distribution Function106.257352941176
Midmean - Empirical Distribution Function - Averaging106.395454545455
Midmean - Empirical Distribution Function - Interpolation106.395454545455
Midmean - Closest Observation106.257352941176
Midmean - True Basic - Statistics Graphics Toolkit106.395454545455
Midmean - MS Excel (old versions)106.340579710145
Number of observations132
 
Charts produced by software:
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Apr/20/t1208722111ly8p9qr4nhjxsw8/15vcs1208722057.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Apr/20/t1208722111ly8p9qr4nhjxsw8/15vcs1208722057.ps (open in new window)


http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Apr/20/t1208722111ly8p9qr4nhjxsw8/2eiwd1208722058.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Apr/20/t1208722111ly8p9qr4nhjxsw8/2eiwd1208722058.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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