Home » date » 2009 » Dec » 28 »

ct goudprijs

*Unverified author*
R Software Module: /rwasp_centraltendency.wasp (opens new window with default values)
Title produced by software: Central Tendency
Date of computation: Mon, 28 Dec 2009 06:35:22 -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/28/t1262007392b5yr5uhg12fj6iw.htm/, Retrieved Mon, 28 Dec 2009 14:36:34 +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/28/t1262007392b5yr5uhg12fj6iw.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:
 
Dataseries X:
» Textbox « » Textfile « » CSV «
10070 10137 9984 9732 9103 9155 9308 9394 9948 10177 10002 9728 10002 10063 10018 9960 10236 10893 10756 10940 10997 10827 10166 10186 10457 10368 10244 10511 10812 10738 10171 9721 9897 9828 9924 10371 10846 10413 10709 10662 10570 10297 10635 10872 10296 10383 10431 10574 10653 10805 10872 10625 10407 10463 10556 10646 10702 11353 11346 11451 11964 12574 13031 13812 14544 14931 14886 16005 17064 15168 16050 15839 15137 14954 15648 15305 15579 16348 15928 16171 15937 15713 15594 15683 16438 17032 17696 17745 19394 20148 20108 18584 18441 18391 19178 18079 18483 19644 19195 19650 20830 23595 22937 21814 21928 21777 21383 21467 22052 22680 24320
 
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 Mean13767.9729729730404.03907832737734.0758449157171
Geometric Mean13181.7453875367
Harmonic Mean12674.6063992917
Quadratic Mean14405.3571019338
Winsorized Mean ( 1 / 37 )13761.9099099099402.48934293877634.1919858285621
Winsorized Mean ( 2 / 37 )13752.8108108108399.65126065288934.4120290984284
Winsorized Mean ( 3 / 37 )13748.1891891892397.98400869053134.5445768899716
Winsorized Mean ( 4 / 37 )13737.3423423423392.36004844526435.012082389063
Winsorized Mean ( 5 / 37 )13732.0720720721391.2608359161735.0969757551054
Winsorized Mean ( 6 / 37 )13726.1261261261390.073207836835.1885898604677
Winsorized Mean ( 7 / 37 )13729.8468468468389.0761876588535.288324709518
Winsorized Mean ( 8 / 37 )13712.4774774775384.47610500912735.6653568292677
Winsorized Mean ( 9 / 37 )13707.8558558559383.03431328145935.7875401251144
Winsorized Mean ( 10 / 37 )13660.1981981982373.95796008140136.5287001651863
Winsorized Mean ( 11 / 37 )13593.8018018018362.39883590955837.5106111135366
Winsorized Mean ( 12 / 37 )13592.0720720721361.4530222010437.6039795968621
Winsorized Mean ( 13 / 37 )13540.5405405405352.63971488610338.3976618881793
Winsorized Mean ( 14 / 37 )13539.7837837838352.52055717042838.408494223609
Winsorized Mean ( 15 / 37 )13508.1621621622347.0592928453238.9217705465175
Winsorized Mean ( 16 / 37 )13485.9639639640342.0802617449639.4233911514559
Winsorized Mean ( 17 / 37 )13484.4324324324341.58802353858939.4757178332662
Winsorized Mean ( 18 / 37 )13398.9729729730326.33850306802341.0585108622014
Winsorized Mean ( 19 / 37 )13386.6486486486323.40128620065941.3933067673167
Winsorized Mean ( 20 / 37 )13379.9819819820322.23740643630241.5221253483706
Winsorized Mean ( 21 / 37 )13371.6576576577320.78653784996241.6839738577553
Winsorized Mean ( 22 / 37 )13311.6036036036311.9291232519442.6750906258023
Winsorized Mean ( 23 / 37 )13252.7567567568301.48880133881243.9577082064264
Winsorized Mean ( 24 / 37 )13243.8918918919299.89900957850344.1611724910518
Winsorized Mean ( 25 / 37 )13113.2612612613280.08320242452746.819163547642
Winsorized Mean ( 26 / 37 )13106279.10193817294046.9577534494909
Winsorized Mean ( 27 / 37 )12978.7837837838259.51183252637450.0123006239601
Winsorized Mean ( 28 / 37 )12956.8378378378256.70372650342250.4738985067484
Winsorized Mean ( 29 / 37 )12913.7297297297250.91038137822351.4674987092843
Winsorized Mean ( 30 / 37 )12887.5135135135246.47908605641352.2864382520628
Winsorized Mean ( 31 / 37 )12876.6216216216244.86299970543352.5870451522364
Winsorized Mean ( 32 / 37 )12862.2072072072242.1187358443553.1235518075557
Winsorized Mean ( 33 / 37 )12867.2612612613241.10584457911253.3676870576203
Winsorized Mean ( 34 / 37 )12841.8378378378237.80388224591154.0018006289663
Winsorized Mean ( 35 / 37 )12817.2432432432231.90009788672355.2705383052668
Winsorized Mean ( 36 / 37 )12822.1081081081229.4816262038655.874225401896
Winsorized Mean ( 37 / 37 )12815.1081081081227.74227906977956.2702198311699
Trimmed Mean ( 1 / 37 )13713.9633027523397.47629234669734.5025944108142
Trimmed Mean ( 2 / 37 )13664.2242990654391.80729600761434.8748592440705
Trimmed Mean ( 3 / 37 )13617.4387.05621961526135.181969207305
Trimmed Mean ( 4 / 37 )13570.4174757282382.33373959184235.4936435644293
Trimmed Mean ( 5 / 37 )13524.5544554455378.74072232541135.7092693186168
Trimmed Mean ( 6 / 37 )13478.0202020202374.89003403257435.9519298420430
Trimmed Mean ( 7 / 37 )13478.0202020202370.72379753132336.3559617477252
Trimmed Mean ( 8 / 37 )13380.7684210526366.10725132708536.5487664408429
Trimmed Mean ( 9 / 37 )13331.2795698925361.67121321943836.8602174644293
Trimmed Mean ( 10 / 37 )13280.2417582418356.77635276900737.222875493769
Trimmed Mean ( 11 / 37 )13232.8539325843352.68511882628737.5203069996895
Trimmed Mean ( 12 / 37 )13190.9885057471349.80310247863237.7097527502716
Trimmed Mean ( 13 / 37 )13147.3411764706346.49552102914837.9437550517849
Trimmed Mean ( 14 / 37 )13147.3411764706343.89618186322238.2305529105865
Trimmed Mean ( 15 / 37 )13064.5185185185340.74835629573438.3406648253349
Trimmed Mean ( 16 / 37 )13022.9620253165337.74486156007838.5585792931447
Trimmed Mean ( 17 / 37 )12981.2467532468334.79054732709838.7742331941164
Trimmed Mean ( 18 / 37 )12937.44331.22777075982439.0590437822348
Trimmed Mean ( 19 / 37 )12898.4520547945329.0430587180439.1998910569553
Trimmed Mean ( 20 / 37 )12858.2816901408326.64860683511839.3642630676558
Trimmed Mean ( 21 / 37 )12816.3188405797323.749431788639.587154701011
Trimmed Mean ( 22 / 37 )12772.5074626866320.28303952318839.8788130701559
Trimmed Mean ( 23 / 37 )12730.6615384615317.23394158070240.1302000505609
Trimmed Mean ( 24 / 37 )12690.6666666667314.84184945615340.3080679667843
Trimmed Mean ( 25 / 37 )12648.7213114754311.89396328553840.5545563570128
Trimmed Mean ( 26 / 37 )12613.7627118644310.97912090774140.5614456528308
Trimmed Mean ( 27 / 37 )12576.8947368421309.60457406721240.6224448548095
Trimmed Mean ( 28 / 37 )12576.8947368421310.38813153984540.5198957654978
Trimmed Mean ( 29 / 37 )12516.1886792453311.19605291555440.2196254161413
Trimmed Mean ( 30 / 37 )12486.3529411765312.45123456187339.9625655462208
Trimmed Mean ( 31 / 37 )12486.3529411765313.98624315612239.7671974914135
Trimmed Mean ( 32 / 37 )12424.0212765957315.39306267966439.3921831096661
Trimmed Mean ( 33 / 37 )12390.2444444444316.78280670164739.1127428077681
Trimmed Mean ( 34 / 37 )12352.9302325581317.78462690608438.8720195587335
Trimmed Mean ( 35 / 37 )12314318.72075666907438.6357014481663
Trimmed Mean ( 36 / 37 )12273.0769230769319.96822840043938.3571737245024
Trimmed Mean ( 37 / 37 )12227.3243243243320.79256919937338.1159836552355
Median10940
Midrange16711.5
Midmean - Weighted Average at Xnp12507.9464285714
Midmean - Weighted Average at X(n+1)p12576.8947368421
Midmean - Empirical Distribution Function12576.8947368421
Midmean - Empirical Distribution Function - Averaging12576.8947368421
Midmean - Empirical Distribution Function - Interpolation12546.8545454545
Midmean - Closest Observation12507.9464285714
Midmean - True Basic - Statistics Graphics Toolkit12576.8947368421
Midmean - MS Excel (old versions)12576.8947368421
Number of observations111
 
Charts produced by software:
http://www.freestatistics.org/blog/date/2009/Dec/28/t1262007392b5yr5uhg12fj6iw/1e5j61262007320.png (open in new window)
http://www.freestatistics.org/blog/date/2009/Dec/28/t1262007392b5yr5uhg12fj6iw/1e5j61262007320.ps (open in new window)


http://www.freestatistics.org/blog/date/2009/Dec/28/t1262007392b5yr5uhg12fj6iw/2xnx31262007320.png (open in new window)
http://www.freestatistics.org/blog/date/2009/Dec/28/t1262007392b5yr5uhg12fj6iw/2xnx31262007320.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')
 




Copyright

Creative Commons License

This work is licensed under a Creative Commons Attribution-Noncommercial-Share Alike 3.0 License.

Software written by Ed van Stee & Patrick Wessa


Disclaimer

Information provided on this web site is provided "AS IS" without warranty of any kind, either express or implied, including, without limitation, warranties of merchantability, fitness for a particular purpose, and noninfringement. We use reasonable efforts to include accurate and timely information and periodically update the information, and software without notice. However, we make no warranties or representations as to the accuracy or completeness of such information (or software), and we assume no liability or responsibility for errors or omissions in the content of this web site, or any software bugs in online applications. Your use of this web site is AT YOUR OWN RISK. Under no circumstances and under no legal theory shall we be liable to you or any other person for any direct, indirect, special, incidental, exemplary, or consequential damages arising from your access to, or use of, this web site.


Privacy Policy

We may request personal information to be submitted to our servers in order to be able to:

  • personalize online software applications according to your needs
  • enforce strict security rules with respect to the data that you upload (e.g. statistical data)
  • manage user sessions of online applications
  • alert you about important changes or upgrades in resources or applications

We NEVER allow other companies to directly offer registered users information about their products and services. Banner references and hyperlinks of third parties NEVER contain any personal data of the visitor.

We do NOT sell, nor transmit by any means, personal information, nor statistical data series uploaded by you to third parties.

We carefully protect your data from loss, misuse, alteration, and destruction. However, at any time, and under any circumstance you are solely responsible for managing your passwords, and keeping them secret.

We store a unique ANONYMOUS USER ID in the form of a small 'Cookie' on your computer. This allows us to track your progress when using this website which is necessary to create state-dependent features. The cookie is used for NO OTHER PURPOSE. At any time you may opt to disallow cookies from this website - this will not affect other features of this website.

We examine cookies that are used by third-parties (banner and online ads) very closely: abuse from third-parties automatically results in termination of the advertising contract without refund. We have very good reason to believe that the cookies that are produced by third parties (banner ads) do NOT cause any privacy or security risk.

FreeStatistics.org is safe. There is no need to download any software to use the applications and services contained in this website. Hence, your system's security is not compromised by their use, and your personal data - other than data you submit in the account application form, and the user-agent information that is transmitted by your browser - is never transmitted to our servers.

As a general rule, we do not log on-line behavior of individuals (other than normal logging of webserver 'hits'). However, in cases of abuse, hacking, unauthorized access, Denial of Service attacks, illegal copying, hotlinking, non-compliance with international webstandards (such as robots.txt), or any other harmful behavior, our system engineers are empowered to log, track, identify, publish, and ban misbehaving individuals - even if this leads to ban entire blocks of IP addresses, or disclosing user's identity.

FreeStatistics.org is powered by