eigen reeks (buitenlandse invoer) centrummaten- sorcha de bolle

*Unverified author*

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

Title produced by software: Central Tendency

Date of computation: Mon, 03 Nov 2008 15:53:14 -0700

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2008/Nov/03/t1225752928a52y4fbyxh0etj6.htm/, Retrieved Mon, 03 Nov 2008 22:55:30 +0000

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/2008/Nov/03/t1225752928a52y4fbyxh0etj6.htm/}, year = {2008}, } @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 = {2008}, note = {{ISBN} 3-900051-07-0}, url = {http://www.R-project.org}, }

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IsPrivate?

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User-defined keywords:

Dataseries X:

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11,9 13,6 15,2 12,5 14,9 13,7 12,5 13,1 14,5 15,2 16,1 14,8 15,1 14,8 16,1 14,3 15,2 14,9 13,1 12,6 13,6 14,4 14 12,9 13,4 13,5 14,8 14,3 14,3 14 13,2 12,2 14,3 15,7 14,2 14,6 14,5 14,3 15,3 14,4 13,7 14,2 13,5 11,9 14,6 15,6 14,1 14,9 14,2 14,6 17,2 15,4 14,3 17,5 14,5 14,4 16,6 16,7 16,6 16,9 15,7 16,4 18,4 16,9 16,5 18,3 15,1 15,7 18,1 16,8 18,9 19 18,1 17,8 21,5 17,1 18,7 19 16,4 16,9 18,6 19,3 19,4 17,6 18,6 18,1 20,4 18,1 19,6 19,9 19,2 17,8 19,2 22,1 21,2 19,5

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 'George Udny Yule' @ 72.249.76.132 Central Tendency - Ungrouped Data Measure Value S.E. Value/S.E. Arithmetic Mean 15.909375 0.239389199569684 66.4581987349388 Geometric Mean 15.7437837411919 Harmonic Mean 15.5840052023451 Quadratic Mean 16.0795645411601 Winsorized Mean ( 1 / 32 ) 15.903125 0.237763949011538 66.8861913932471 Winsorized Mean ( 2 / 32 ) 15.903125 0.235176553336074 67.6220685030365 Winsorized Mean ( 3 / 32 ) 15.8875 0.228093980707707 69.6533067234211 Winsorized Mean ( 4 / 32 ) 15.8666666666667 0.223948158683606 70.8497304015929 Winsorized Mean ( 5 / 32 ) 15.85625 0.220251115157382 71.9916899792758 Winsorized Mean ( 6 / 32 ) 15.86875 0.21632553695437 73.3558794001618 Winsorized Mean ( 7 / 32 ) 15.8760416666667 0.212992179205664 74.5381437284457 Winsorized Mean ( 8 / 32 ) 15.8677083333333 0.211554888939861 75.0051601872652 Winsorized Mean ( 9 / 32 ) 15.8677083333333 0.208690018127211 76.0348217692945 Winsorized Mean ( 10 / 32 ) 15.8885416666667 0.205963023591586 77.1426899333776 Winsorized Mean ( 11 / 32 ) 15.8770833333333 0.200703145362696 79.1072970213866 Winsorized Mean ( 12 / 32 ) 15.8770833333333 0.200703145362696 79.1072970213866 Winsorized Mean ( 13 / 32 ) 15.8770833333333 0.196830584194299 80.6637007064942 Winsorized Mean ( 14 / 32 ) 15.8479166666667 0.192194044663443 82.4578966243124 Winsorized Mean ( 15 / 32 ) 15.8479166666667 0.187866479080192 84.3573411513283 Winsorized Mean ( 16 / 32 ) 15.8479166666667 0.187866479080192 84.3573411513283 Winsorized Mean ( 17 / 32 ) 15.865625 0.176291152499385 89.9967172207088 Winsorized Mean ( 18 / 32 ) 15.846875 0.173476786486150 91.3486773705319 Winsorized Mean ( 19 / 32 ) 15.8270833333333 0.165470350120515 95.6490593136847 Winsorized Mean ( 20 / 32 ) 15.8479166666667 0.163218581019621 97.0962776888838 Winsorized Mean ( 21 / 32 ) 15.8479166666667 0.163218581019621 97.0962776888838 Winsorized Mean ( 22 / 32 ) 15.8479166666667 0.163218581019621 97.0962776888837 Winsorized Mean ( 23 / 32 ) 15.8 0.150430668299095 105.031774296087 Winsorized Mean ( 24 / 32 ) 15.8 0.150430668299095 105.031774296087 Winsorized Mean ( 25 / 32 ) 15.7479166666667 0.143239303867740 109.941309692538 Winsorized Mean ( 26 / 32 ) 15.7208333333333 0.139578914567398 112.630431194121 Winsorized Mean ( 27 / 32 ) 15.6364583333333 0.128504554766593 121.680187614629 Winsorized Mean ( 28 / 32 ) 15.6072916666667 0.124800233282391 125.058193051221 Winsorized Mean ( 29 / 32 ) 15.5770833333333 0.113993297420178 136.649116095979 Winsorized Mean ( 30 / 32 ) 15.5770833333333 0.113993297420178 136.649116095979 Winsorized Mean ( 31 / 32 ) 15.5770833333333 0.113993297420178 136.649116095979 Winsorized Mean ( 32 / 32 ) 15.5770833333333 0.106349712413383 146.470385108188 Trimmed Mean ( 1 / 32 ) 15.8861702127660 0.231423044730184 68.6455846749731 Trimmed Mean ( 2 / 32 ) 15.8684782608696 0.224182590949052 70.7837222939218 Trimmed Mean ( 3 / 32 ) 15.85 0.217477595097835 72.8810707736107 Trimmed Mean ( 4 / 32 ) 15.8363636363636 0.212864610169828 74.3964138694968 Trimmed Mean ( 5 / 32 ) 15.8279069767442 0.208981970977598 75.7381457486629 Trimmed Mean ( 6 / 32 ) 15.8214285714286 0.205560059641522 76.9674254766206 Trimmed Mean ( 7 / 32 ) 15.8121951219512 0.202561065798945 78.0613740334772 Trimmed Mean ( 8 / 32 ) 15.80125 0.199798108146667 79.0860841805402 Trimmed Mean ( 9 / 32 ) 15.7910256410256 0.196854940985309 80.2165572374642 Trimmed Mean ( 10 / 32 ) 15.7802631578947 0.193943559675997 81.3652342168894 Trimmed Mean ( 11 / 32 ) 15.7662162162162 0.190978278353235 82.5550232841396 Trimmed Mean ( 12 / 32 ) 15.7527777777778 0.188385075594272 83.6200942568548 Trimmed Mean ( 13 / 32 ) 15.7385714285714 0.185267897989469 84.9503427165026 Trimmed Mean ( 14 / 32 ) 15.7235294117647 0.182174429036128 86.3102988435687 Trimmed Mean ( 15 / 32 ) 15.7106060606061 0.179238596668144 87.6519139998285 Trimmed Mean ( 16 / 32 ) 15.696875 0.176368919551406 89.0002333740265 Trimmed Mean ( 17 / 32 ) 15.6822580645161 0.172846333686898 90.7294805160501 Trimmed Mean ( 18 / 32 ) 15.665 0.170373882643455 91.9448436400461 Trimmed Mean ( 19 / 32 ) 15.6482758620690 0.167744392940685 93.2864317414307 Trimmed Mean ( 20 / 32 ) 15.6321428571429 0.165735416252445 94.3198696489368 Trimmed Mean ( 21 / 32 ) 15.6129629629630 0.163428635532222 95.5338268114261 Trimmed Mean ( 22 / 32 ) 15.5923076923077 0.160406867531218 97.2047390007986 Trimmed Mean ( 23 / 32 ) 15.57 0.156472596544532 99.5062416285067 Trimmed Mean ( 24 / 32 ) 15.55 0.153822454530314 101.090572553148 Trimmed Mean ( 25 / 32 ) 15.5282608695652 0.150254632295846 103.346303753155 Trimmed Mean ( 26 / 32 ) 15.5090909090909 0.147057760790272 105.462580320459 Trimmed Mean ( 27 / 32 ) 15.4904761904762 0.143533050652493 107.922712713604 Trimmed Mean ( 28 / 32 ) 15.4775 0.141262054171380 109.565870967886 Trimmed Mean ( 29 / 32 ) 15.4657894736842 0.138846923692646 111.387339829866 Trimmed Mean ( 30 / 32 ) 15.4555555555556 0.137750893434400 112.199312615826 Trimmed Mean ( 31 / 32 ) 15.4441176470588 0.135840368231196 113.693137379997 Trimmed Mean ( 32 / 32 ) 15.43125 0.132777213054242 116.219113543948 Median 15.2 Midrange 17 Midmean - Weighted Average at Xnp 15.57 Midmean - Weighted Average at X(n+1)p 15.57 Midmean - Empirical Distribution Function 15.57 Midmean - Empirical Distribution Function - Averaging 15.57 Midmean - Empirical Distribution Function - Interpolation 15.57 Midmean - Closest Observation 15.57 Midmean - True Basic - Statistics Graphics Toolkit 15.57 Midmean - MS Excel (old versions) 15.57 Number of observations 96

Charts produced by software:

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Nov/03/t1225752928a52y4fbyxh0etj6/121yh1225752792.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Nov/03/t1225752928a52y4fbyxh0etj6/121yh1225752792.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Nov/03/t1225752928a52y4fbyxh0etj6/2qy8j1225752792.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Nov/03/t1225752928a52y4fbyxh0etj6/2qy8j1225752792.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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