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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: Thu, 13 Dec 2007 03:58:40 -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/Dec/13/t1197542616bq6hlk3t8oi4wr7.htm/, Retrieved Thu, 13 Dec 2007 11:43:37 +0100

User-defined keywords:

bridome

Dataseries X:

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25 27 30 37 31 29 22 21 18 13 18 4 -6 -6 -6 0,320164393 -6 -15 -12 -19 -21 -25 -15 -29 -34 -36 -40 -28 -29 -31 -28 -27 -31 -31 -28 -20 -18 -31 -32 -21 -17 -11 -13 -10 -8 -0,559875248 -16 -12 -5 5 7 20 23 27 33 34 41 49 37 41 39 40 48 -13 -8 -4 -7 -6 0,851515681 -1 -8 0,230447709 9 12 12 14 17 23 19 22 25 23 8 13 8 10 12 13 16 16 18 25 26 20 3 3 -18 -21 -30 -21 -27 -34 -32 -39 -50 -47

Text written by user:

Output produced by software:

Summary of compuational transaction Raw Input view raw input (R code) Raw Output view raw output of R engine Computing time 3 seconds R Server 'Herman Ole Andreas Wold' @ 193.190.124.10:1001 Central Tendency - Ungrouped Data Measure Value S.E. Value/S.E. Arithmetic Mean 0.0362476654245283 2.32549166618229 0.0155870975379737 Geometric Mean NaN Harmonic Mean 18.2194981467107 Quadratic Mean 23.8292261789802 Winsorized Mean ( 1 / 35 ) 0.0551155899528302 2.31798065894854 0.0237774158037329 Winsorized Mean ( 2 / 35 ) 0.0551155899528302 2.2697248043454 0.0242829394327062 Winsorized Mean ( 3 / 35 ) 0.083417476745283 2.26502087108981 0.0368285686944451 Winsorized Mean ( 4 / 35 ) 0.158889174858491 2.24057410855816 0.070914492072185 Winsorized Mean ( 5 / 35 ) 0.206058986179245 2.21847371826986 0.09288322168628 Winsorized Mean ( 6 / 35 ) 0.092851439009434 2.20000163937133 0.0422051680997689 Winsorized Mean ( 7 / 35 ) 0.224926910707547 2.18096048201644 0.103132043226931 Winsorized Mean ( 8 / 35 ) -0.00148818363207547 2.14568653401075 -0.000693569917360546 Winsorized Mean ( 9 / 35 ) -0.00148818363207547 2.12104912918926 -0.000701626196015698 Winsorized Mean ( 10 / 35 ) -0.190167428915094 2.09368109353832 -0.0908292239453293 Winsorized Mean ( 11 / 35 ) -0.293941013820755 2.07911869700178 -0.141377697312152 Winsorized Mean ( 12 / 35 ) -0.407148560990566 2.06358106326339 -0.197301946717176 Winsorized Mean ( 13 / 35 ) -0.529790070424528 2.01375419550068 -0.263085768664435 Winsorized Mean ( 14 / 35 ) -0.397714598726415 1.9955347142955 -0.1993022701521 Winsorized Mean ( 15 / 35 ) -0.539224032688679 1.97723734134330 -0.272715885652017 Winsorized Mean ( 16 / 35 ) -0.539224032688679 1.93757875693152 -0.278297865704633 Winsorized Mean ( 17 / 35 ) -0.539224032688679 1.93757875693152 -0.278297865704633 Winsorized Mean ( 18 / 35 ) -0.539224032688679 1.93757875693152 -0.278297865704633 Winsorized Mean ( 19 / 35 ) -0.718469315707548 1.86930271642551 -0.384351506791478 Winsorized Mean ( 20 / 35 ) -0.718469315707548 1.86930271642551 -0.384351506791478 Winsorized Mean ( 21 / 35 ) -0.322242900613208 1.81713880770075 -0.177335324768583 Winsorized Mean ( 22 / 35 ) 0.300398608820755 1.68803805856862 0.177957248828548 Winsorized Mean ( 23 / 35 ) 0.300398608820755 1.68803805856862 0.177957248828548 Winsorized Mean ( 24 / 35 ) 0.0739835144811321 1.66058947611886 0.0445525613314416 Winsorized Mean ( 25 / 35 ) -0.161865542122642 1.63256441467489 -0.099148027892594 Winsorized Mean ( 26 / 35 ) 0.083417476745283 1.60301985209257 0.0520377066050619 Winsorized Mean ( 27 / 35 ) 0.083417476745283 1.54287210013077 0.054066358927751 Winsorized Mean ( 28 / 35 ) 0.083417476745283 1.48131387469008 0.0563131677698863 Winsorized Mean ( 29 / 35 ) 0.0834174767452825 1.48131387469008 0.056313167769886 Winsorized Mean ( 30 / 35 ) 0.366436344669811 1.44870239480537 0.252941077466116 Winsorized Mean ( 31 / 35 ) 0.366436344669811 1.38178891490506 0.265189813521544 Winsorized Mean ( 32 / 35 ) 0.366436344669811 1.31351947742458 0.278972905212097 Winsorized Mean ( 33 / 35 ) 0.366436344669811 1.31351947742458 0.278972905212097 Winsorized Mean ( 34 / 35 ) 0.366436344669811 1.17088676885526 0.312956260517032 Winsorized Mean ( 35 / 35 ) 0.0362476654245283 1.13460850826242 0.0319472885674365 Trimmed Mean ( 1 / 35 ) 0.0465601205288461 2.27187254143923 0.0204941605127858 Trimmed Mean ( 2 / 35 ) 0.0376691425 2.22008029031936 0.0169674685479872 Trimmed Mean ( 3 / 35 ) 0.02842252535 2.19031646084541 0.0129764469464059 Trimmed Mean ( 4 / 35 ) 0.00859441362244896 2.15858701163628 0.00398149973854152 Trimmed Mean ( 5 / 35 ) -0.0328932027604167 2.13052919158757 -0.0154389824322971 Trimmed Mean ( 6 / 35 ) -0.0867845475 2.10455069526538 -0.0412366153475132 Trimmed Mean ( 7 / 35 ) -0.12127986375 2.07923092970047 -0.0583291937502447 Trimmed Mean ( 8 / 35 ) -0.179530527388889 2.05417553322788 -0.0873978511012536 Trimmed Mean ( 9 / 35 ) -0.206338039375 2.03221339035215 -0.101533648166369 Trimmed Mean ( 10 / 35 ) -0.234392412383721 2.01116817935074 -0.116545406192430 Trimmed Mean ( 11 / 35 ) -0.239973184107143 1.99128036202248 -0.120512002570753 Trimmed Mean ( 12 / 35 ) -0.233631066646341 1.97029728976772 -0.118576555862737 Trimmed Mean ( 13 / 35 ) -0.2144718433125 1.9480400039798 -0.110096221265651 Trimmed Mean ( 14 / 35 ) -0.181509582884615 1.92930432594687 -0.0940803275271431 Trimmed Mean ( 15 / 35 ) -0.159970361381579 1.90963619532291 -0.0837700718981863 Trimmed Mean ( 16 / 35 ) -0.123753344121622 1.88870553513183 -0.0655228365775841 Trimmed Mean ( 17 / 35 ) -0.0855242703472222 1.86924220342298 -0.045753445000658 Trimmed Mean ( 18 / 35 ) -0.0451106780714286 1.84565135491888 -0.0244416032048541 Trimmed Mean ( 19 / 35 ) -0.00231981566176471 1.81715762913993 -0.00127661773781436 Trimmed Mean ( 20 / 35 ) 0.0582159475 1.79262738184234 0.0324752082276964 Trimmed Mean ( 21 / 35 ) 0.122535195859375 1.76265500828858 0.069517401467204 Trimmed Mean ( 22 / 35 ) 0.158746008629032 1.73408238156735 0.091544675337483 Trimmed Mean ( 23 / 35 ) 0.147370875583333 1.71795857208648 0.0857825549334111 Trimmed Mean ( 24 / 35 ) 0.135211250603448 1.69722147493633 0.0796662383785359 Trimmed Mean ( 25 / 35 ) 0.140040223839286 1.67497779785955 0.0836072119990146 Trimmed Mean ( 26 / 35 ) 0.163745417314815 1.65084167088421 0.0991890501692453 Trimmed Mean ( 27 / 35 ) 0.170043317980769 1.62462324030958 0.104666308939645 Trimmed Mean ( 28 / 35 ) 0.1768450507 1.60071800752236 0.110478578905804 Trimmed Mean ( 29 / 35 ) 0.184213594479167 1.5796754996455 0.116614832932780 Trimmed Mean ( 30 / 35 ) 0.192222881195652 1.55129593126672 0.123911161836601 Trimmed Mean ( 31 / 35 ) 0.178233012159091 1.51956869130038 0.117291842862705 Trimmed Mean ( 32 / 35 ) 0.162910774642857 1.49020796784897 0.109320831828600 Trimmed Mean ( 33 / 35 ) 0.146056313375 1.46395601481458 0.099768238865769 Trimmed Mean ( 34 / 35 ) 0.127427698289474 1.42687502693409 0.0893054373257031 Trimmed Mean ( 35 / 35 ) 0.106729237083333 1.40796601858336 0.0758038444640306 Median -0.1647137695 Midrange -0.5 Midmean - Weighted Average at Xnp -0.210523537075472 Midmean - Weighted Average at X(n+1)p 0.524404591545455 Midmean - Empirical Distribution Function 0.524404591545455 Midmean - Empirical Distribution Function - Averaging 0.524404591545455 Midmean - Empirical Distribution Function - Interpolation 0.170043317980769 Midmean - Closest Observation 0.524404591545455 Midmean - True Basic - Statistics Graphics Toolkit 0.524404591545455 Midmean - MS Excel (old versions) 0.524404591545455 Number of observations 106

Charts produced by software:

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2007/Dec/13/t1197542616bq6hlk3t8oi4wr7/1mvlw1197543514.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2007/Dec/13/t1197542616bq6hlk3t8oi4wr7/1mvlw1197543514.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2007/Dec/13/t1197542616bq6hlk3t8oi4wr7/2t2l21197543514.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2007/Dec/13/t1197542616bq6hlk3t8oi4wr7/2t2l21197543514.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')

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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