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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, 18 Nov 2007 15:21:35 -0700
 
Cite this page as follows:
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2007/Nov/18/t1195424151qstcyeijqit8iwd.htm/, Retrieved Sun, 18 Nov 2007 23:15:53 +0100
 
User-defined keywords:
 
Dataseries X:
» Textbox « » Textfile « » CSV «
112,1 104,2 102,4 100,3 102,6 101,5 103,4 99,4 97,9 98 90,2 87,1 91,8 94,8 91,8 89,3 91,7 86,2 82,8 82,3 79,8 79,4 85,3 87,5 88,3 88,6 94,9 94,7 92,6 91,8 96,4 96,4 107,1 111,9 107,8 109,2 115,3 119,2 107,8 106,8 104,2 94,8 97,5 98,3 100,6 94,9 93,6 98 104,3 103,9 105,3 102,6 103,3 107,9 107,8 109,8 110,6 110,8 119,3 128,1 127,6 137,9 151,4 143,6 143,4 141,9 135,2 133,1 129,6 134,1 136,8 143,5 162,5 163,1 157,2 158,8 155,4 148,5 154,2 153,3 149,4 147,9 156 163 159,1 159,5 157,3 156,4 156,6 162,4 166,8 162,6 168,1
 
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 Mean117.6602150537632.7859466417134442.2334775878546
Geometric Mean114.771580274988
Harmonic Mean112.080604171931
Quadratic Mean120.656471380616
Winsorized Mean ( 1 / 31 )117.6505376344092.7825903120025642.2809412966506
Winsorized Mean ( 2 / 31 )117.6247311827962.7601098350988142.6159603096319
Winsorized Mean ( 3 / 31 )117.6376344086022.7573031564441642.6640190556009
Winsorized Mean ( 4 / 31 )117.7279569892472.7399322128602442.9674706683164
Winsorized Mean ( 5 / 31 )117.7709677419352.7328249766632043.0949543961409
Winsorized Mean ( 6 / 31 )117.8225806451612.7244731462810543.2460054913703
Winsorized Mean ( 7 / 31 )117.6344086021512.6828609900043143.8466282973393
Winsorized Mean ( 8 / 31 )117.6688172043012.6687226085034644.0918126257739
Winsorized Mean ( 9 / 31 )117.6688172043012.6603731448752544.2301928325242
Winsorized Mean ( 10 / 31 )117.5827956989252.6246759517058744.7989762783873
Winsorized Mean ( 11 / 31 )117.6774193548392.6104055672278945.0801288628134
Winsorized Mean ( 12 / 31 )117.7935483870972.5759658956565845.7279145604032
Winsorized Mean ( 13 / 31 )117.7795698924732.5698559866820645.8311946283567
Winsorized Mean ( 14 / 31 )117.7193548387102.5600443663540445.9833260649162
Winsorized Mean ( 15 / 31 )117.6225806451612.5443706846686246.2285551998806
Winsorized Mean ( 16 / 31 )117.5537634408602.4961670285382247.0937089132616
Winsorized Mean ( 17 / 31 )117.5720430107532.4503505419390547.981723838465
Winsorized Mean ( 18 / 31 )117.4172043010752.3701315711284549.5403739317186
Winsorized Mean ( 19 / 31 )117.0290322580652.3049606953318550.7726802001782
Winsorized Mean ( 20 / 31 )116.8354838709682.2755497797858751.343848817916
Winsorized Mean ( 21 / 31 )116.7225806451612.2527356643484551.8137047734452
Winsorized Mean ( 22 / 31 )115.7053763440862.1027800370076455.0249547302819
Winsorized Mean ( 23 / 31 )116.0516129032262.0600178905658156.335245162046
Winsorized Mean ( 24 / 31 )116.0258064516132.0562820104414656.4250457196303
Winsorized Mean ( 25 / 31 )115.9182795698921.967781603025558.908102094087
Winsorized Mean ( 26 / 31 )114.9118279569891.7982933376258563.9004914007514
Winsorized Mean ( 27 / 31 )114.6215053763441.7511312375658765.4556911083784
Winsorized Mean ( 28 / 31 )114.1397849462371.6852473899329167.7288009036941
Winsorized Mean ( 29 / 31 )113.8903225806451.6290871314917169.9105163738903
Winsorized Mean ( 30 / 31 )113.9225806451611.5490893198821773.5416474589253
Winsorized Mean ( 31 / 31 )113.0559139784951.3629878956394482.9471151872958
Trimmed Mean ( 1 / 31 )117.5263736263742.7602121784826342.5787461350096
Trimmed Mean ( 2 / 31 )117.3966292134832.7340649139370442.9384937479164
Trimmed Mean ( 3 / 31 )117.2747126436782.7167642250588843.1670557061817
Trimmed Mean ( 4 / 31 )117.1423529411762.6971924278617643.4312182294101
Trimmed Mean ( 5 / 31 )116.9783132530122.6793537232613243.6591526670937
Trimmed Mean ( 6 / 31 )116.7962962962962.6596443675547243.9142532441955
Trimmed Mean ( 7 / 31 )116.5949367088612.6377301934856844.2027531840866
Trimmed Mean ( 8 / 31 )116.4155844155842.6204093178247644.426488496928
Trimmed Mean ( 9 / 31 )116.2213333333332.6017231250114344.6709076058287
Trimmed Mean ( 10 / 31 )116.0164383561642.580101833396344.9658369504924
Trimmed Mean ( 11 / 31 )115.8112676056342.5598553383546745.2413329262858
Trimmed Mean ( 12 / 31 )115.5826086956522.5368191988349845.5620206393632
Trimmed Mean ( 13 / 31 )115.5826086956522.5135522155590345.9837706892219
Trimmed Mean ( 14 / 31 )115.0569230769232.4851820174311846.2971815625208
Trimmed Mean ( 15 / 31 )114.7761904761902.4512927655955646.822718235496
Trimmed Mean ( 16 / 31 )114.4868852459022.4116752395909247.4719329395783
Trimmed Mean ( 17 / 31 )114.1847457627122.3702850871294848.1734228438296
Trimmed Mean ( 18 / 31 )113.8596491228072.3257505588437348.9560880421387
Trimmed Mean ( 19 / 31 )113.5254545454552.2832566059243349.7208479550182
Trimmed Mean ( 20 / 31 )113.2018867924532.2409477484034150.5151835303188
Trimmed Mean ( 21 / 31 )112.8705882352942.1917873342479651.497052871702
Trimmed Mean ( 22 / 31 )112.5224489795922.1323238443287452.7698685539083
Trimmed Mean ( 23 / 31 )112.2361702127662.0866817568155453.7869130480387
Trimmed Mean ( 24 / 31 )111.8933333333332.0326089121862555.0491206953245
Trimmed Mean ( 25 / 31 )111.5209302325581.9605312582030756.8830156448375
Trimmed Mean ( 26 / 31 )111.5209302325581.8831230941564659.2212641747213
Trimmed Mean ( 27 / 31 )110.7743589743591.8218745738581160.8024067978381
Trimmed Mean ( 28 / 31 )110.4162162162161.7488370804155963.1369367980103
Trimmed Mean ( 29 / 31 )110.0628571428571.6655333802047466.0826486283495
Trimmed Mean ( 30 / 31 )109.6909090909091.5631732709239770.1719451907418
Trimmed Mean ( 31 / 31 )109.2677419354841.4371820328787776.029159449352
Median107.8
Midrange123.75
Midmean - Weighted Average at Xnp111.556521739130
Midmean - Weighted Average at X(n+1)p112.236170212766
Midmean - Empirical Distribution Function112.236170212766
Midmean - Empirical Distribution Function - Averaging112.236170212766
Midmean - Empirical Distribution Function - Interpolation112.236170212766
Midmean - Closest Observation111.528571428571
Midmean - True Basic - Statistics Graphics Toolkit112.236170212766
Midmean - MS Excel (old versions)112.236170212766
Number of observations93
 
Charts produced by software:
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2007/Nov/18/t1195424151qstcyeijqit8iwd/13zxf1195424492.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2007/Nov/18/t1195424151qstcyeijqit8iwd/13zxf1195424492.ps (open in new window)


http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2007/Nov/18/t1195424151qstcyeijqit8iwd/26zbx1195424492.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2007/Nov/18/t1195424151qstcyeijqit8iwd/26zbx1195424492.ps (open in new window)


 
Parameters:
 
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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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:

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.

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