Isabelle Regnard oef 5/2 Koffie, thee, cacao: centrummaten

*Unverified author*

R Software Module: /rwasp_centraltendency.wasp (opens new window with default values)

Title produced by software: Central Tendency

Date of computation: Sun, 03 Apr 2011 15:35:37 +0000

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2011/Apr/03/t13018447956fogo4wxr5ur595.htm/, Retrieved Sun, 03 Apr 2011 17:33:18 +0200

Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords:

KDGP1W52

Dataseries X:

» Textbox « » Textfile « » CSV «

106,42 106,22 106,32 105,81 105,92 107,54 107,34 107,24 107,74 105,71 105,41 106,22 106,32 106,12 106,22 105,92 105,71 105,71 105,92 105,71 105,41 104,49 101,35 99,72 99,01 97,89 95,86 94,95 95,35 95,15 95,46 95,56 95,05 94,64 93,63 93,12 93,53 97,18 96,27 95,15 97,08 101,95 103,07 103,68 102,87 102,56 103,38 103,27 102,89 102,69 101,54 102,9 101,53 101,96 101,99 101,11 101,75 101,71 104,11 103,57 103,32 103,64 103,68 103,79 103,01 101,54 101,9 103,68 104,62 104,11 105,04 104,83 105,05 104,68 107,32 109,9 109,77 110,69 110,54 110,89 110,95 109,73 110,85 110,39 110,58 110,4 111,07 110,86 111,38 111,44 110,36 110,06 108,34 107,94 107,39 107,1 107,61 107,74 106,9 106,71 106,6 108,21 110,54 110,91 109,51 110,27 111,39 112,13 111,64

Output produced by software:

Summary of computational transaction Raw Input view raw input (R code) Raw Output view raw output of R engine Computing time 2 seconds R Server 'George Udny Yule' @ 216.218.223.82 Central Tendency - Ungrouped Data Measure Value S.E. Value/S.E. Arithmetic Mean 104.595412844037 0.472355084723042 221.433866654287 Geometric Mean 104.477721466207 Harmonic Mean 104.357498206876 Quadratic Mean 104.710540420864 Winsorized Mean ( 1 / 36 ) 104.594678899083 0.470879404596599 222.126255423485 Winsorized Mean ( 2 / 36 ) 104.592844036697 0.469979921125734 222.547473488161 Winsorized Mean ( 3 / 36 ) 104.619266055046 0.464022959861537 225.461399768373 Winsorized Mean ( 4 / 36 ) 104.630275229358 0.461736433982413 226.601731050192 Winsorized Mean ( 5 / 36 ) 104.620642201835 0.458960756267795 227.951171800821 Winsorized Mean ( 6 / 36 ) 104.619541284404 0.457048014939266 228.902736396975 Winsorized Mean ( 7 / 36 ) 104.616972477064 0.456719427158723 229.061796490445 Winsorized Mean ( 8 / 36 ) 104.630183486239 0.453733389574768 230.598377572116 Winsorized Mean ( 9 / 36 ) 104.636788990826 0.451702876866327 231.649596116677 Winsorized Mean ( 10 / 36 ) 104.64504587156 0.449865114073731 232.61427169569 Winsorized Mean ( 11 / 36 ) 104.659174311927 0.442194376881909 236.681377655502 Winsorized Mean ( 12 / 36 ) 104.692201834862 0.432437173354756 242.098062529367 Winsorized Mean ( 13 / 36 ) 104.784036697248 0.414804444451477 252.610689443819 Winsorized Mean ( 14 / 36 ) 104.796880733945 0.412602311723134 253.990047453409 Winsorized Mean ( 15 / 36 ) 104.875321100917 0.393725995041017 266.366260856086 Winsorized Mean ( 16 / 36 ) 105.038256880734 0.367508274332658 285.811950959386 Winsorized Mean ( 17 / 36 ) 105.144311926605 0.350516810976265 299.969384160937 Winsorized Mean ( 18 / 36 ) 105.358990825688 0.317661748551183 331.670373616647 Winsorized Mean ( 19 / 36 ) 105.364220183486 0.307330484550834 342.836866110034 Winsorized Mean ( 20 / 36 ) 105.367889908257 0.299236259496619 352.122734342117 Winsorized Mean ( 21 / 36 ) 105.344770642202 0.29551436398124 356.479357629091 Winsorized Mean ( 22 / 36 ) 105.336697247706 0.294396878095274 357.805075682959 Winsorized Mean ( 23 / 36 ) 105.326146788991 0.283761591204956 371.178306203237 Winsorized Mean ( 24 / 36 ) 105.077339449541 0.24938339325183 421.348583317387 Winsorized Mean ( 25 / 36 ) 105.081926605505 0.241566114167184 435.002760911984 Winsorized Mean ( 26 / 36 ) 105.029449541284 0.232511762984814 451.716713997581 Winsorized Mean ( 27 / 36 ) 104.982385321101 0.226542918305178 463.410580681575 Winsorized Mean ( 28 / 36 ) 104.990091743119 0.225592454239197 465.397178718564 Winsorized Mean ( 29 / 36 ) 105.107155963303 0.203520079838419 516.446121909693 Winsorized Mean ( 30 / 36 ) 105.123669724771 0.197212509009084 533.047676605182 Winsorized Mean ( 31 / 36 ) 105.132201834862 0.186602779486896 563.401049673245 Winsorized Mean ( 32 / 36 ) 105.123394495413 0.184304222833487 570.379738886333 Winsorized Mean ( 33 / 36 ) 105.120366972477 0.18329102127828 573.516183386194 Winsorized Mean ( 34 / 36 ) 105.129724770642 0.176694382585203 594.980571722184 Winsorized Mean ( 35 / 36 ) 105.104036697248 0.169619365567243 619.646443940863 Winsorized Mean ( 36 / 36 ) 105.104036697248 0.155195727663214 677.23537419362 Trimmed Mean ( 1 / 36 ) 104.632242990654 0.463626773405843 225.682055033225 Trimmed Mean ( 2 / 36 ) 104.671238095238 0.455474668785718 229.806936078989 Trimmed Mean ( 3 / 36 ) 104.712718446602 0.446822872624888 234.349503711528 Trimmed Mean ( 4 / 36 ) 104.746336633663 0.439550867144375 238.303105427064 Trimmed Mean ( 5 / 36 ) 104.778282828283 0.432079844437055 242.497501740206 Trimmed Mean ( 6 / 36 ) 104.813711340206 0.424363843667729 246.990201696528 Trimmed Mean ( 7 / 36 ) 104.850842105263 0.416051957065197 252.01381780505 Trimmed Mean ( 8 / 36 ) 104.89 0.406643894165388 257.940673658165 Trimmed Mean ( 9 / 36 ) 104.928901098901 0.396514806112469 264.627952049636 Trimmed Mean ( 10 / 36 ) 104.968651685393 0.38529631192489 272.436170387885 Trimmed Mean ( 11 / 36 ) 105.009195402299 0.372725185057755 281.733565672594 Trimmed Mean ( 12 / 36 ) 105.05 0.359603929336705 292.126952544057 Trimmed Mean ( 13 / 36 ) 105.089156626506 0.346153974902578 303.590784003224 Trimmed Mean ( 14 / 36 ) 105.120740740741 0.333697337259942 315.018218616633 Trimmed Mean ( 15 / 36 ) 105.152658227848 0.319512860957824 329.103053669343 Trimmed Mean ( 16 / 36 ) 105.178831168831 0.306217077632574 343.478005805522 Trimmed Mean ( 17 / 36 ) 105.1916 0.295159937709759 356.38847472396 Trimmed Mean ( 18 / 36 ) 105.195753424658 0.284980634192656 369.132989414087 Trimmed Mean ( 19 / 36 ) 105.181830985915 0.278109984313066 378.202282977058 Trimmed Mean ( 20 / 36 ) 105.166666666667 0.271520509954487 387.32494530264 Trimmed Mean ( 21 / 36 ) 105.150298507463 0.264883679457822 396.967826491575 Trimmed Mean ( 22 / 36 ) 105.134769230769 0.257517186477643 408.263116993541 Trimmed Mean ( 23 / 36 ) 105.118888888889 0.248815124666347 422.477890079432 Trimmed Mean ( 24 / 36 ) 105.102786885246 0.240046799984765 437.842899350945 Trimmed Mean ( 25 / 36 ) 105.104745762712 0.235122654230863 447.020922362978 Trimmed Mean ( 26 / 36 ) 105.10649122807 0.230277223582809 456.434594758232 Trimmed Mean ( 27 / 36 ) 105.112363636364 0.225682647724477 465.752970803008 Trimmed Mean ( 28 / 36 ) 105.122264150943 0.220849830030469 475.989789697553 Trimmed Mean ( 29 / 36 ) 105.132352941176 0.214890868469993 489.236018681069 Trimmed Mean ( 30 / 36 ) 105.134285714286 0.211286752629536 497.590522859827 Trimmed Mean ( 31 / 36 ) 105.135106382979 0.207665512456616 506.271383915722 Trimmed Mean ( 32 / 36 ) 105.135333333333 0.204767569638743 513.437423312765 Trimmed Mean ( 33 / 36 ) 105.136279069767 0.201212829603081 522.512800387344 Trimmed Mean ( 34 / 36 ) 105.13756097561 0.196538887261096 534.945335453831 Trimmed Mean ( 35 / 36 ) 105.138205128205 0.191595288637763 548.751516155406 Trimmed Mean ( 36 / 36 ) 105.141081081081 0.186391280045082 564.087982311461 Median 105.41 Midrange 102.625 Midmean - Weighted Average at Xnp 105.112363636364 Midmean - Weighted Average at X(n+1)p 105.112363636364 Midmean - Empirical Distribution Function 105.112363636364 Midmean - Empirical Distribution Function - Averaging 105.112363636364 Midmean - Empirical Distribution Function - Interpolation 105.112363636364 Midmean - Closest Observation 105.055892857143 Midmean - True Basic - Statistics Graphics Toolkit 105.112363636364 Midmean - MS Excel (old versions) 105.112363636364 Number of observations 109

Charts produced by software:

http://www.freestatistics.org/blog/date/2011/Apr/03/t13018447956fogo4wxr5ur595/1u9mi1301844934.png (open in new window) http://www.freestatistics.org/blog/date/2011/Apr/03/t13018447956fogo4wxr5ur595/1u9mi1301844934.ps (open in new window) http://www.freestatistics.org/blog/date/2011/Apr/03/t13018447956fogo4wxr5ur595/2le1a1301844934.png (open in new window) http://www.freestatistics.org/blog/date/2011/Apr/03/t13018447956fogo4wxr5ur595/2le1a1301844934.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

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

Software written by Ed van Stee & Patrick Wessa

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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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