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central tendency 20-25 jaar

*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: Thu, 18 Dec 2008 08:52:59 -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/18/t1229615646xzntw29qydyu7gx.htm/, Retrieved Thu, 18 Dec 2008 16:54:09 +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/18/t1229615646xzntw29qydyu7gx.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 «
40628 40167 43375 45610 46255 44375 35461 38096 40813 41582 44461 46390 45744 47990 51847 56641 55016 53119 44471 45200 46256 46922 48965 49447 51702 52837 56273 59070 57871 54862 44357 45264 47111 49050 50518 51824 53495 54623 58088 61321 60205 56527 45623 46127 48141 50648 52441 53661 54156 54245 58182 60436 59412 55903 43648 43555 45483 46956 49087 50433 50505 50890 53703 55276 53959 49732 37776 38437 40187 41626 42682 43647 43625 44352 49669 50986 48869 43127 33629 34948 36346 37607 38948 40274 40044 41139 45041 47433 48126 41639 33538 34742 37152 38399 41374 43363 44071 45080 48487 52140 52780 46700 38202 39915 42199 44356 46188 47883 48149 48201 51438 55796 55989 48794 39252 41414 43856 46086 48284 50101
 
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'George Udny Yule' @ 72.249.76.132


Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean47167.6416666667590.02674235503479.9415319353181
Geometric Mean46723.150597703
Harmonic Mean46273.5529300297
Quadratic Mean47604.7694631711
Winsorized Mean ( 1 / 40 )47161.025588.43742440953680.1462025419669
Winsorized Mean ( 2 / 40 )47175.725584.26019921513180.7443756452583
Winsorized Mean ( 3 / 40 )47161.05579.7255676028981.3506469880334
Winsorized Mean ( 4 / 40 )47166.75574.7440566959282.0656594017718
Winsorized Mean ( 5 / 40 )47166.625562.33836333892783.875879852736
Winsorized Mean ( 6 / 40 )47202.225555.23995184640785.0122993545992
Winsorized Mean ( 7 / 40 )47216.1083333333549.19510760557985.9732865050265
Winsorized Mean ( 8 / 40 )47145.375534.72721442459788.1671508915657
Winsorized Mean ( 9 / 40 )47160.825529.96242833141288.9889971039757
Winsorized Mean ( 10 / 40 )47148.4916666667525.57991007663889.7075606634044
Winsorized Mean ( 11 / 40 )47140.5166666667519.24769392335790.7861839702744
Winsorized Mean ( 12 / 40 )47135.7166666667517.48254117200391.086583442821
Winsorized Mean ( 13 / 40 )47179.4833333333508.15251630745592.8451238934486
Winsorized Mean ( 14 / 40 )47154.2833333333494.8507529273295.2899092390771
Winsorized Mean ( 15 / 40 )47204.6583333333479.52653725251698.4401376486817
Winsorized Mean ( 16 / 40 )47201.325474.53965399746899.4676095082496
Winsorized Mean ( 17 / 40 )47184.8916666667467.778006255821100.870265458487
Winsorized Mean ( 18 / 40 )47131.1916666667459.924686822132102.475890112187
Winsorized Mean ( 19 / 40 )47130.875456.353877866166103.27703408674
Winsorized Mean ( 20 / 40 )47157.0416666667444.755113809747106.029228675354
Winsorized Mean ( 21 / 40 )47144.6166666667435.061466918947108.363117056859
Winsorized Mean ( 22 / 40 )47196.6833333333426.864640801148110.565923766264
Winsorized Mean ( 23 / 40 )47209.9083333333417.496000080779113.078708117440
Winsorized Mean ( 24 / 40 )47142.7083333333407.157324495302115.784993900748
Winsorized Mean ( 25 / 40 )47118.9583333333395.841120441611119.035026681327
Winsorized Mean ( 26 / 40 )47116.1416666667393.224564727119.819934696546
Winsorized Mean ( 27 / 40 )47042.7916666667383.754315096467122.585700840500
Winsorized Mean ( 28 / 40 )47103.225360.263905460124130.746445275556
Winsorized Mean ( 29 / 40 )47149.1416666667338.829594160499139.152962076662
Winsorized Mean ( 30 / 40 )47254.6416666667326.071570608479144.921072323126
Winsorized Mean ( 31 / 40 )47284.0916666667315.941230838829149.661035190395
Winsorized Mean ( 32 / 40 )47216.8916666667307.407377318223153.597132504040
Winsorized Mean ( 33 / 40 )47142.0916666667288.070952004488163.647501904087
Winsorized Mean ( 34 / 40 )47134.725282.957796182608166.57864047535
Winsorized Mean ( 35 / 40 )47070.5583333333274.484887512602171.486884978949
Winsorized Mean ( 36 / 40 )47031.8583333333270.203323509965174.060991265338
Winsorized Mean ( 37 / 40 )47091.9833333333263.077517568048179.004210502908
Winsorized Mean ( 38 / 40 )47137.2666666667253.611331066979185.864198055952
Winsorized Mean ( 39 / 40 )47120.6916666667232.701772871321202.493909200784
Winsorized Mean ( 40 / 40 )46999.025219.508890813125214.109892432611
Trimmed Mean ( 1 / 40 )47163.2033898305576.29745920757881.8382983237181
Trimmed Mean ( 2 / 40 )47165.4568965517562.83505701771383.7997852274283
Trimmed Mean ( 3 / 40 )47160.0526315789550.3322129508885.6937891727379
Trimmed Mean ( 4 / 40 )47159.6964285714538.29159539508687.6099438148537
Trimmed Mean ( 5 / 40 )47157.7727272727526.49202192512689.5697764893751
Trimmed Mean ( 6 / 40 )47155.8055555556516.69311365975891.2646294461893
Trimmed Mean ( 7 / 40 )47147.0471698113507.40506481421292.9179672005724
Trimmed Mean ( 8 / 40 )47135.6634615385498.26992911211294.5986516696511
Trimmed Mean ( 9 / 40 )47134.2352941177490.79515951116296.0364713887235
Trimmed Mean ( 10 / 40 )47130.69483.2162480325297.5353999206337
Trimmed Mean ( 11 / 40 )47128.5102040816475.39123450665499.136262478609
Trimmed Mean ( 12 / 40 )47127.1458333333467.544563496444100.797120772621
Trimmed Mean ( 13 / 40 )47126.2340425532458.91343761378102.690900243838
Trimmed Mean ( 14 / 40 )47120.8913043478450.490483732159104.599082568776
Trimmed Mean ( 15 / 40 )47117.7111111111442.809320073191106.406322033428
Trimmed Mean ( 16 / 40 )47109.8068181818436.143634087865108.014431797693
Trimmed Mean ( 17 / 40 )47101.8255813954429.154106483110109.755038737464
Trimmed Mean ( 18 / 40 )47094.8452380952422.006937814309111.597324636444
Trimmed Mean ( 19 / 40 )47091.8902439024414.79683755143113.53001272114
Trimmed Mean ( 20 / 40 )47088.8125406.904936762032115.724357818590
Trimmed Mean ( 21 / 40 )47083.5641025641399.272766148815117.923304804153
Trimmed Mean ( 22 / 40 )47078.9736842105391.652024201257120.206128846709
Trimmed Mean ( 23 / 40 )47070.2972972973383.797768412004122.643488762467
Trimmed Mean ( 24 / 40 )47060.1805555556375.810691429604125.223102026545
Trimmed Mean ( 25 / 40 )47054.2857142857367.802345392937127.933620608144
Trimmed Mean ( 26 / 40 )47049.7205882353359.863023183272130.743415013978
Trimmed Mean ( 27 / 40 )47045.0757575758350.741501124411134.13033703385
Trimmed Mean ( 28 / 40 )47045.234375341.206292437729137.879152341793
Trimmed Mean ( 29 / 40 )47041.2258064516333.232811281738141.166248382065
Trimmed Mean ( 30 / 40 )47033.7833333333326.714154934922143.960041592633
Trimmed Mean ( 31 / 40 )47018.5517241379320.524271993135146.692640253918
Trimmed Mean ( 32 / 40 )47000.1964285714314.337052763475149.521655227636
Trimmed Mean ( 33 / 40 )46985.1481481481307.987988829172152.555131538616
Trimmed Mean ( 34 / 40 )46974.1730769231303.138806968793154.959285967497
Trimmed Mean ( 35 / 40 )46962.84297.707920633905157.748036733463
Trimmed Mean ( 36 / 40 )46955.1458333333292.159265364429160.71763383839
Trimmed Mean ( 37 / 40 )46949.5869565217285.674816950493164.346257250453
Trimmed Mean ( 38 / 40 )46939.0909090909278.470622790023168.560297092755
Trimmed Mean ( 39 / 40 )46924.1904761905270.795005928623173.283071876735
Trimmed Mean ( 40 / 40 )46909.075265.006926342719177.010750803302
Median46811
Midrange47429.5
Midmean - Weighted Average at Xnp46962.4426229508
Midmean - Weighted Average at X(n+1)p47033.7833333333
Midmean - Empirical Distribution Function46962.4426229508
Midmean - Empirical Distribution Function - Averaging47033.7833333333
Midmean - Empirical Distribution Function - Interpolation47033.7833333333
Midmean - Closest Observation46962.4426229508
Midmean - True Basic - Statistics Graphics Toolkit47033.7833333333
Midmean - MS Excel (old versions)47041.2258064516
Number of observations120
 
Charts produced by software:
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/18/t1229615646xzntw29qydyu7gx/1xopt1229615576.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/18/t1229615646xzntw29qydyu7gx/1xopt1229615576.ps (open in new window)


http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/18/t1229615646xzntw29qydyu7gx/2m65s1229615576.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/18/t1229615646xzntw29qydyu7gx/2m65s1229615576.ps (open in new window)


 
Parameters (Session):
par1 = 60 ; par2 = 1 ; par3 = 1 ; par4 = 0 ; par5 = 12 ;
 
Parameters (R input):
par1 = 60 ; par2 = 1 ; par3 = 1 ; par4 = 0 ; par5 = 12 ;
 
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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