mauro de colfmaker opgave 5 oefening 2 stap 1

*Unverified author*

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

Title produced by software: Central Tendency

Date of computation: Mon, 01 Jun 2009 09:01:46 -0600

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2009/Jun/01/t1243869386khe40mrdp1se56g.htm/, Retrieved Mon, 01 Jun 2009 17:16:26 +0200

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/Jun/01/t1243869386khe40mrdp1se56g.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 «

0,22 0,22 0,2 0,21 0,21 0,19 0,19 0,18 0,18 0,19 0,18 0,17 0,17 0,17 0,18 0,2 0,2 0,2 0,22 0,23 0,25 0,25 0,27 0,29 0,3 0,31 0,33 0,31 0,33 0,33 0,35 0,37 0,47 0,45 0,45 0,4 0,34 0,35 0,34 0,35 0,36 0,37 0,36 0,35 0,36 0,33 0,3 0,28 0,28 0,28 0,3 0,32 0,32 0,3 0,3 0,31 0,33 0,34 0,31 0,33 0,35 0,38 0,4 0,32 0,29 0,3 0,3 0,32 0,32 0,32 0,32 0,32 0,33 0,31 0,33 0,35 0,37 0,37 0,38 0,42 0,42 0,49 0,45 0,41 0,4 0,42 0,47 0,49 0,47 0,52 0,56 0,57 0,61 0,52 0,5 0,5

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 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 Central Tendency - Ungrouped Data Measure Value S.E. Value/S.E. Arithmetic Mean 0.331041666666667 0.0101453030860395 32.6300420854059 Geometric Mean 0.316153712906627 Harmonic Mean 0.301130621755906 Quadratic Mean 0.345494814239905 Winsorized Mean ( 1 / 32 ) 0.330625 0.0100326358896721 32.9549485933557 Winsorized Mean ( 2 / 32 ) 0.330416666666667 0.0099812506980376 33.1037338568832 Winsorized Mean ( 3 / 32 ) 0.329479166666667 0.00964770879043158 34.1510273396144 Winsorized Mean ( 4 / 32 ) 0.329479166666667 0.00964770879043158 34.1510273396144 Winsorized Mean ( 5 / 32 ) 0.3284375 0.00943970724740268 34.7931870546482 Winsorized Mean ( 6 / 32 ) 0.3284375 0.00943970724740268 34.7931870546482 Winsorized Mean ( 7 / 32 ) 0.3284375 0.0091841875518111 35.7611926092725 Winsorized Mean ( 8 / 32 ) 0.3284375 0.0091841875518111 35.7611926092725 Winsorized Mean ( 9 / 32 ) 0.3265625 0.00885039909522372 36.8980535777461 Winsorized Mean ( 10 / 32 ) 0.327604166666667 0.00868521731548794 37.7197431873657 Winsorized Mean ( 11 / 32 ) 0.327604166666667 0.00868521731548794 37.7197431873657 Winsorized Mean ( 12 / 32 ) 0.325104166666667 0.00827036931395336 39.3095101712286 Winsorized Mean ( 13 / 32 ) 0.325104166666667 0.00827036931395336 39.3095101712286 Winsorized Mean ( 14 / 32 ) 0.3265625 0.00804296047904898 40.6022758473896 Winsorized Mean ( 15 / 32 ) 0.321875 0.00733190650991783 43.9005870525765 Winsorized Mean ( 16 / 32 ) 0.323541666666667 0.00706948465618913 45.7659479299407 Winsorized Mean ( 17 / 32 ) 0.323541666666667 0.00706948465618913 45.7659479299407 Winsorized Mean ( 18 / 32 ) 0.321666666666667 0.00680664450053954 47.2577444938059 Winsorized Mean ( 19 / 32 ) 0.321666666666667 0.00623140508687448 51.6202465065558 Winsorized Mean ( 20 / 32 ) 0.325833333333333 0.00561105321028548 58.0699061516751 Winsorized Mean ( 21 / 32 ) 0.325833333333333 0.00561105321028548 58.0699061516751 Winsorized Mean ( 22 / 32 ) 0.325833333333333 0.00435201774807183 74.869486338307 Winsorized Mean ( 23 / 32 ) 0.328229166666667 0.00403926667302964 81.2595931975145 Winsorized Mean ( 24 / 32 ) 0.325729166666667 0.00371325503771909 87.7206556937036 Winsorized Mean ( 25 / 32 ) 0.325729166666667 0.00371325503771909 87.7206556937036 Winsorized Mean ( 26 / 32 ) 0.3284375 0.00337472586605974 97.3227198401976 Winsorized Mean ( 27 / 32 ) 0.3284375 0.00337472586605974 97.3227198401976 Winsorized Mean ( 28 / 32 ) 0.3284375 0.00266280473505241 123.342690388274 Winsorized Mean ( 29 / 32 ) 0.3284375 0.00266280473505241 123.342690388274 Winsorized Mean ( 30 / 32 ) 0.3284375 0.00266280473505241 123.342690388274 Winsorized Mean ( 31 / 32 ) 0.325208333333333 0.002274858616518 142.957602275570 Winsorized Mean ( 32 / 32 ) 0.325208333333333 0.002274858616518 142.957602275570 Trimmed Mean ( 1 / 32 ) 0.329787234042553 0.00977202821447448 33.7480845126979 Trimmed Mean ( 2 / 32 ) 0.328913043478261 0.00947430518366964 34.7163234772288 Trimmed Mean ( 3 / 32 ) 0.328111111111111 0.00916473516517533 35.8014830977207 Trimmed Mean ( 4 / 32 ) 0.327613636363636 0.00895535530658815 36.5829858389451 Trimmed Mean ( 5 / 32 ) 0.327093023255814 0.00871476298120599 37.5332093323953 Trimmed Mean ( 6 / 32 ) 0.326785714285714 0.0084991996421912 38.4489984990474 Trimmed Mean ( 7 / 32 ) 0.326463414634146 0.00825002979422049 39.5711800777796 Trimmed Mean ( 8 / 32 ) 0.326125 0.00802191174458898 40.6542742407981 Trimmed Mean ( 9 / 32 ) 0.325769230769231 0.00775610408270582 42.0016579580997 Trimmed Mean ( 10 / 32 ) 0.325657894736842 0.00751684780498854 43.3237313280069 Trimmed Mean ( 11 / 32 ) 0.325405405405405 0.00726906381536947 44.7657929095875 Trimmed Mean ( 12 / 32 ) 0.325138888888889 0.00697635469749359 46.6058425907878 Trimmed Mean ( 13 / 32 ) 0.325142857142857 0.00671126754771501 48.4473096670924 Trimmed Mean ( 14 / 32 ) 0.325147058823529 0.00639459223030453 50.8471919886665 Trimmed Mean ( 15 / 32 ) 0.325 0.00605818716297472 53.6464112542236 Trimmed Mean ( 16 / 32 ) 0.3253125 0.0057905263951164 56.1801255710295 Trimmed Mean ( 17 / 32 ) 0.325483870967742 0.00551751894438829 58.9909838549412 Trimmed Mean ( 18 / 32 ) 0.325666666666667 0.00518236179969862 62.8413606100612 Trimmed Mean ( 19 / 32 ) 0.326034482758621 0.00481942313906659 67.6501052824687 Trimmed Mean ( 20 / 32 ) 0.326428571428571 0.00448973266948197 72.7055696762086 Trimmed Mean ( 21 / 32 ) 0.326481481481481 0.00421435939566402 77.4688276034039 Trimmed Mean ( 22 / 32 ) 0.326538461538462 0.00386308490604313 84.527901788451 Trimmed Mean ( 23 / 32 ) 0.3266 0.00369897945109078 88.2946240492604 Trimmed Mean ( 24 / 32 ) 0.326458333333333 0.00355416027495206 91.852451234135 Trimmed Mean ( 25 / 32 ) 0.326521739130435 0.00343634160180341 95.0201630009877 Trimmed Mean ( 26 / 32 ) 0.326590909090909 0.00328271760352627 99.4879695835206 Trimmed Mean ( 27 / 32 ) 0.326428571428571 0.00315715783495588 103.393174650432 Trimmed Mean ( 28 / 32 ) 0.32625 0.00298902908513699 109.149155363621 Trimmed Mean ( 29 / 32 ) 0.326052631578947 0.00293455097566288 111.108184619385 Trimmed Mean ( 30 / 32 ) 0.325833333333333 0.00285565437417799 114.101109812046 Trimmed Mean ( 31 / 32 ) 0.325588235294118 0.0027423910768318 118.724217725453 Trimmed Mean ( 32 / 32 ) 0.325625 0.00269173990379409 120.971940691975 Median 0.325 Midrange 0.39 Midmean - Weighted Average at Xnp 0.325510204081633 Midmean - Weighted Average at X(n+1)p 0.325510204081633 Midmean - Empirical Distribution Function 0.325510204081633 Midmean - Empirical Distribution Function - Averaging 0.325510204081633 Midmean - Empirical Distribution Function - Interpolation 0.325510204081633 Midmean - Closest Observation 0.325510204081633 Midmean - True Basic - Statistics Graphics Toolkit 0.325510204081633 Midmean - MS Excel (old versions) 0.327647058823529 Number of observations 96

Charts produced by software:

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/01/t1243869386khe40mrdp1se56g/11zl21243868501.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/01/t1243869386khe40mrdp1se56g/11zl21243868501.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/01/t1243869386khe40mrdp1se56g/2l4nu1243868501.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/01/t1243869386khe40mrdp1se56g/2l4nu1243868501.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 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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