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central tendency < 20 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 08:43:24 -0700
 
Cite this page as follows:
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2008/Dec/18/t1229615285cya2hlg1j8f1get.htm/, Retrieved Thu, 18 Dec 2008 16:48:07 +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/t1229615285cya2hlg1j8f1get.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 «
12460 12870 14122 15366 15366 15046 10356 10194 11027 11449 12107 12862 12587 13951 15210 17511 17247 16900 12237 12188 12801 13276 14171 14629 16242 17239 18516 19862 19542 18515 13182 13148 13853 14341 14895 15317 15649 16373 17543 18911 19401 18295 12665 12246 12969 13563 15714 16094 15823 15460 16827 18279 18789 18041 12129 11708 12387 12982 13664 14073 14222 14715 15697 16908 17412 16232 10281 10258 11013 11779 12333 12684 12654 13239 14729 16146 16324 13797 9399 9626 10290 10931 11382 11704 11716 12470 13662 15097 15821 13083 9081 9479 10295 10999 11643 12055 12431 12940 14168 16031 16445 14245 9820 10389 11298 12156 12759 13414 13683 14070 15176 16694 17694 14294 9255 9868 10878 11685 12496 12488
 
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 Mean13864.1916666667237.35038374370158.4123414842999
Geometric Mean13623.7748148620
Harmonic Mean13385.644801055
Quadratic Mean14103.8895317923
Winsorized Mean ( 1 / 40 )13862.975236.55677700765558.6031614708354
Winsorized Mean ( 2 / 40 )13863.025235.70030092788058.8163228702956
Winsorized Mean ( 3 / 40 )13852.775233.05645691461559.4395674910446
Winsorized Mean ( 4 / 40 )13853.6083333333231.55910465580159.8275259093176
Winsorized Mean ( 5 / 40 )13850.3166666667228.34388901463260.6555171081418
Winsorized Mean ( 6 / 40 )13852.6666666667227.98106411038660.7623563857013
Winsorized Mean ( 7 / 40 )13858.85223.09579521931362.1206239515905
Winsorized Mean ( 8 / 40 )13862.05222.33253630919862.3482744816173
Winsorized Mean ( 9 / 40 )13845.925219.17124112420563.1740046229582
Winsorized Mean ( 10 / 40 )13817.7583333333214.54608784347564.4046156805909
Winsorized Mean ( 11 / 40 )13804.375212.40806284794264.9898822808918
Winsorized Mean ( 12 / 40 )13807.275211.09298499494465.4084975885424
Winsorized Mean ( 13 / 40 )13800.125209.03292047782266.0189073015615
Winsorized Mean ( 14 / 40 )13837.925198.75780137693569.6220470549329
Winsorized Mean ( 15 / 40 )13843.55197.78915217596669.9914522495343
Winsorized Mean ( 16 / 40 )13808.4833333333190.46208735691972.4999054927751
Winsorized Mean ( 17 / 40 )13809.3333333333190.06162767795372.6571349622047
Winsorized Mean ( 18 / 40 )13800.4833333333188.31422611361473.2843376634073
Winsorized Mean ( 19 / 40 )13822.3333333333180.30042829800676.6627870150555
Winsorized Mean ( 20 / 40 )13794.8333333333173.21004570936679.642224426637
Winsorized Mean ( 21 / 40 )13793.9583333333170.23294815655481.029897459379
Winsorized Mean ( 22 / 40 )13820.5416666667165.05724747309383.7318074683125
Winsorized Mean ( 23 / 40 )13812.875162.17640374950785.1719157697869
Winsorized Mean ( 24 / 40 )13814.675161.50660771771785.5362835937055
Winsorized Mean ( 25 / 40 )13797.5916666667159.17738792223986.6806011002457
Winsorized Mean ( 26 / 40 )13788.0583333333157.59492061934887.4904995614468
Winsorized Mean ( 27 / 40 )13788.0583333333154.29897508052789.359364351821
Winsorized Mean ( 28 / 40 )13803.925141.54931050935097.5202560176951
Winsorized Mean ( 29 / 40 )13816.0083333333140.19521228785398.5483605885623
Winsorized Mean ( 30 / 40 )13794.7583333333136.442635772545101.102989217606
Winsorized Mean ( 31 / 40 )13797.3416666667135.210268604537102.043593353262
Winsorized Mean ( 32 / 40 )13793.075132.834703922493103.836381553182
Winsorized Mean ( 33 / 40 )13754.575125.443183910908109.647846707787
Winsorized Mean ( 34 / 40 )13730.4916666667122.163536668243112.394353021673
Winsorized Mean ( 35 / 40 )13755.8666666667119.599240306866115.016338158772
Winsorized Mean ( 36 / 40 )13757.3666666667116.327828038252118.263762838784
Winsorized Mean ( 37 / 40 )13737.9416666667111.294323808636123.437936424218
Winsorized Mean ( 38 / 40 )13736.3583333333109.195382155155125.796146890310
Winsorized Mean ( 39 / 40 )13713.9333333333106.046135600582129.320443933820
Winsorized Mean ( 40 / 40 )13702.9333333333103.59709834827132.27140095437
Trimmed Mean ( 1 / 40 )13853.8983050847232.39109324932959.6145838094626
Trimmed Mean ( 2 / 40 )13844.5086206897227.77309900872360.7820180738704
Trimmed Mean ( 3 / 40 )13834.7631578947223.14442613999361.9991428744685
Trimmed Mean ( 4 / 40 )13828.3303571429219.08122850399063.1196495088625
Trimmed Mean ( 5 / 40 )13821.4363636364215.03544116108364.2751552442127
Trimmed Mean ( 6 / 40 )13815.0185185185211.38535364707165.3546628475692
Trimmed Mean ( 7 / 40 )13807.9150943396207.38639931194466.5806202342623
Trimmed Mean ( 8 / 40 )13799.5192307692203.93117559676467.6675314129275
Trimmed Mean ( 9 / 40 )13790.3235294118200.19237358553568.8853590295221
Trimmed Mean ( 10 / 40 )13782.91196.55724130670270.1216088930225
Trimmed Mean ( 11 / 40 )13778.6428571429193.24408531588571.3017572290491
Trimmed Mean ( 12 / 40 )13775.71875189.84013744667772.5648376327657
Trimmed Mean ( 13 / 40 )13772.3617021277186.18198825392973.9725782890656
Trimmed Mean ( 14 / 40 )13769.5760869565182.33486414735675.5180648053597
Trimmed Mean ( 15 / 40 )13763.0666666667179.42828877154776.7051102192151
Trimmed Mean ( 16 / 40 )13755.75176.22930171858978.0559751746948
Trimmed Mean ( 17 / 40 )13751.1511627907173.57291368736479.2240613507185
Trimmed Mean ( 18 / 40 )13746.2619047619170.55884497181780.5954209354156
Trimmed Mean ( 19 / 40 )13741.8536585366167.31166172007082.1332686392663
Trimmed Mean ( 20 / 40 )13735.5164.60537965892383.4450248737992
Trimmed Mean ( 21 / 40 )13730.9358974359162.37805008302684.5615271917299
Trimmed Mean ( 22 / 40 )13726.1973684211160.13620630053985.7157646326412
Trimmed Mean ( 23 / 40 )13719.2432432432158.12949905453186.7595440779343
Trimmed Mean ( 24 / 40 )13712.4583333333156.10359549481487.8420403442206
Trimmed Mean ( 25 / 40 )13705.1571428571153.75573464464289.1359088136277
Trimmed Mean ( 26 / 40 )13698.6323529412151.25749156729190.5649843257317
Trimmed Mean ( 27 / 40 )13692.3787878788148.46906824715392.223780680602
Trimmed Mean ( 28 / 40 )13685.734375145.56246314104694.0196674312865
Trimmed Mean ( 29 / 40 )13677.5645161290143.79499410056295.1185025715411
Trimmed Mean ( 30 / 40 )13668.0166666667141.75449950842996.4203373724583
Trimmed Mean ( 31 / 40 )13659.2758620690139.75921908150497.7343459117584
Trimmed Mean ( 32 / 40 )13649.7321428571137.41307403693599.333576797709
Trimmed Mean ( 33 / 40 )13639.7777777778134.816907874952101.172605074351
Trimmed Mean ( 34 / 40 )13631.75132.748838238022102.688280974316
Trimmed Mean ( 35 / 40 )13624.78130.624657140454104.304809660476
Trimmed Mean ( 36 / 40 )13615.4166666667128.236662839523106.174134332435
Trimmed Mean ( 37 / 40 )13605.1304347826125.667014987007108.263337329921
Trimmed Mean ( 38 / 40 )13595.3409090909123.230489894860110.324489667212
Trimmed Mean ( 39 / 40 )13584.7380952381120.344168951422112.882395662408
Trimmed Mean ( 40 / 40 )13574.8117.139283738940115.885974087508
Median13612.5
Midrange14471.5
Midmean - Weighted Average at Xnp13642.4262295082
Midmean - Weighted Average at X(n+1)p13668.0166666667
Midmean - Empirical Distribution Function13642.4262295082
Midmean - Empirical Distribution Function - Averaging13668.0166666667
Midmean - Empirical Distribution Function - Interpolation13668.0166666667
Midmean - Closest Observation13642.4262295082
Midmean - True Basic - Statistics Graphics Toolkit13668.0166666667
Midmean - MS Excel (old versions)13677.5645161290
Number of observations120
 
Charts produced by software:
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/18/t1229615285cya2hlg1j8f1get/1u2on1229615001.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/18/t1229615285cya2hlg1j8f1get/1u2on1229615001.ps (open in new window)


http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/18/t1229615285cya2hlg1j8f1get/29tg11229615001.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/18/t1229615285cya2hlg1j8f1get/29tg11229615001.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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Software written by Ed van Stee & Patrick Wessa


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