prijs ton per koffie

*Unverified author*

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

Title produced by software: Central Tendency

Date of computation: Mon, 04 Apr 2011 19:37:16 +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/04/t1301945647i96jdfjcx8dxcny.htm/, Retrieved Mon, 04 Apr 2011 21:34:08 +0200

Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords:

KDGP1W52

Dataseries X:

» Textbox « » Textfile « » CSV «

600 425 398 582 458 455 621 635 589 220 351 379 683 524 536 598 581 632 645 722 689 645 354 486 423 479 684 601 608 463 602 485 563 645 486 435 479 579 563 202 389 467 466 706 546 689 531 528 579 684 651 637 548 496 582 467 693 615 708 648 899 852 745 689 582 674 684 542 489 472 398 486 549 766 654 628 689 648 578 536 548 496 475 687 642 584 596 609 678 694 485 489 537 706 489 598

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 'Gwilym Jenkins' @ www.wessa.org Central Tendency - Ungrouped Data Measure Value S.E. Value/S.E. Arithmetic Mean 568.833333333333 11.9982058843997 47.4098660094623 Geometric Mean 555.001361369815 Harmonic Mean 538.005668367031 Quadratic Mean 580.729946561509 Winsorized Mean ( 1 / 32 ) 568.53125 11.8060435861889 48.1559504544849 Winsorized Mean ( 2 / 32 ) 569.46875 10.6790082774839 53.3259957481906 Winsorized Mean ( 3 / 32 ) 568.90625 10.5375277374195 53.9885886117075 Winsorized Mean ( 4 / 32 ) 568.989583333333 10.1626735197166 55.9881789205803 Winsorized Mean ( 5 / 32 ) 568.78125 9.950361484276 57.1618680284946 Winsorized Mean ( 6 / 32 ) 569.21875 9.826914383434 57.9244641593272 Winsorized Mean ( 7 / 32 ) 569.21875 9.826914383434 57.9244641593272 Winsorized Mean ( 8 / 32 ) 570.302083333333 9.31886550714612 61.1986601690946 Winsorized Mean ( 9 / 32 ) 570.395833333333 9.2747237057096 61.5000350880742 Winsorized Mean ( 10 / 32 ) 571.020833333333 9.04873475655268 63.1050471359906 Winsorized Mean ( 11 / 32 ) 573.3125 8.70312396650282 65.8743345730343 Winsorized Mean ( 12 / 32 ) 573.6875 8.64989494536145 66.323059831801 Winsorized Mean ( 13 / 32 ) 574.364583333333 8.55584236360185 67.1312722843969 Winsorized Mean ( 14 / 32 ) 574.510416666667 8.45532629278556 67.9465696263979 Winsorized Mean ( 15 / 32 ) 574.197916666667 8.36904566799043 68.6097243874334 Winsorized Mean ( 16 / 32 ) 574.197916666667 8.36904566799043 68.6097243874334 Winsorized Mean ( 17 / 32 ) 575.083333333333 8.25112521123404 69.697564709156 Winsorized Mean ( 18 / 32 ) 575.458333333333 8.15160511406634 70.5944811213104 Winsorized Mean ( 19 / 32 ) 575.260416666667 7.9132113159896 72.696203057826 Winsorized Mean ( 20 / 32 ) 574.427083333333 7.80027193621314 73.6419304391848 Winsorized Mean ( 21 / 32 ) 571.364583333333 7.06692816140955 80.8504869843435 Winsorized Mean ( 22 / 32 ) 570.677083333333 6.98299147288991 81.723869426001 Winsorized Mean ( 23 / 32 ) 570.197916666667 6.86566942264041 83.0505929671427 Winsorized Mean ( 24 / 32 ) 570.197916666667 6.86566942264041 83.0505929671427 Winsorized Mean ( 25 / 32 ) 569.416666666667 6.77318413981289 84.0692730202957 Winsorized Mean ( 26 / 32 ) 570.229166666667 6.66842321979522 85.5118440854115 Winsorized Mean ( 27 / 32 ) 570.229166666667 6.66842321979522 85.5118440854115 Winsorized Mean ( 28 / 32 ) 569.354166666667 6.56582692054739 86.7147692981221 Winsorized Mean ( 29 / 32 ) 569.958333333333 6.11999736029833 93.1304867924894 Winsorized Mean ( 30 / 32 ) 569.333333333333 6.04824656819707 94.1319648453166 Winsorized Mean ( 31 / 32 ) 577.40625 4.82622537219324 119.639305144509 Winsorized Mean ( 32 / 32 ) 577.40625 4.5136629357527 127.924095843836 Trimmed Mean ( 1 / 32 ) 569.223404255319 11.0597072837123 51.4682160796078 Trimmed Mean ( 2 / 32 ) 569.945652173913 10.17834707578 55.9958948079235 Trimmed Mean ( 3 / 32 ) 570.2 9.87404066991124 57.7473821570887 Trimmed Mean ( 4 / 32 ) 570.670454545455 9.58675562342157 59.5269637572945 Trimmed Mean ( 5 / 32 ) 571.139534883721 9.3858927641259 60.8508481011726 Trimmed Mean ( 6 / 32 ) 571.678571428571 9.21506537816074 62.0373863850627 Trimmed Mean ( 7 / 32 ) 572.158536585366 9.04852370523846 63.2322525998497 Trimmed Mean ( 8 / 32 ) 572.6625 8.8549661341725 64.6713371144379 Trimmed Mean ( 9 / 32 ) 573.025641025641 8.73655142426743 65.5894543737193 Trimmed Mean ( 10 / 32 ) 573.394736842105 8.60544664217711 66.6316067816604 Trimmed Mean ( 11 / 32 ) 573.702702702703 8.49223200005369 67.5561740069131 Trimmed Mean ( 12 / 32 ) 573.75 8.41738713041561 68.1624821468406 Trimmed Mean ( 13 / 32 ) 573.757142857143 8.33457802002963 68.8405749491206 Trimmed Mean ( 14 / 32 ) 573.691176470588 8.2483471979675 69.5522584951266 Trimmed Mean ( 15 / 32 ) 573.606060606061 8.15827918426602 70.3096875763104 Trimmed Mean ( 16 / 32 ) 573.546875 8.06071730899095 71.1533295380877 Trimmed Mean ( 17 / 32 ) 573.483870967742 7.9399431993715 72.2277044769208 Trimmed Mean ( 18 / 32 ) 573.333333333333 7.80976741288206 73.4123441867976 Trimmed Mean ( 19 / 32 ) 573.137931034483 7.66460616761851 74.7772186202965 Trimmed Mean ( 20 / 32 ) 572.946428571429 7.52387626518428 76.1504320881326 Trimmed Mean ( 21 / 32 ) 572.814814814815 7.36670859878188 77.757224564242 Trimmed Mean ( 22 / 32 ) 572.942307692308 7.2919309865407 78.5720968492205 Trimmed Mean ( 23 / 32 ) 573.14 7.20498750158244 79.5476744233242 Trimmed Mean ( 24 / 32 ) 573.395833333333 7.10806526624483 80.6683410823908 Trimmed Mean ( 25 / 32 ) 573.673913043478 6.97739998000626 82.2188658651275 Trimmed Mean ( 26 / 32 ) 574.045454545455 6.81978487145082 84.1735429146072 Trimmed Mean ( 27 / 32 ) 574.380952380952 6.63131910024214 86.6163946717598 Trimmed Mean ( 28 / 32 ) 574.75 6.37711754675482 90.1269258071742 Trimmed Mean ( 29 / 32 ) 575.236842105263 6.05550831506381 94.9939810460323 Trimmed Mean ( 30 / 32 ) 575.722222222222 5.73593671666945 100.371090313652 Trimmed Mean ( 31 / 32 ) 576.323529411765 5.30474522518874 108.643017703317 Trimmed Mean ( 32 / 32 ) 576.21875 5.09342839871364 113.129842002987 Median 581.5 Midrange 550.5 Midmean - Weighted Average at Xnp 573.14 Midmean - Weighted Average at X(n+1)p 573.14 Midmean - Empirical Distribution Function 573.14 Midmean - Empirical Distribution Function - Averaging 573.14 Midmean - Empirical Distribution Function - Interpolation 573.14 Midmean - Closest Observation 573.14 Midmean - True Basic - Statistics Graphics Toolkit 573.14 Midmean - MS Excel (old versions) 573.14 Number of observations 96

Charts produced by software:

http://www.freestatistics.org/blog/date/2011/Apr/04/t1301945647i96jdfjcx8dxcny/1d6ty1301945834.png (open in new window) http://www.freestatistics.org/blog/date/2011/Apr/04/t1301945647i96jdfjcx8dxcny/1d6ty1301945834.ps (open in new window) http://www.freestatistics.org/blog/date/2011/Apr/04/t1301945647i96jdfjcx8dxcny/2y7v91301945834.png (open in new window) http://www.freestatistics.org/blog/date/2011/Apr/04/t1301945647i96jdfjcx8dxcny/2y7v91301945834.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

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:

• personalize online software applications according to your needs
• enforce strict security rules with respect to the data that you upload (e.g. statistical data)
• manage user sessions of online applications
• alert you about important changes or upgrades in resources or applications

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.

FreeStatistics.org is powered by