Central_Tendency_Eigen_Reeks

*Unverified author*

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

Title produced by software: Central Tendency

Date of computation: Tue, 24 May 2011 14:18:37 +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/May/24/t13062469296ga0r6fnp6im9bf.htm/, Retrieved Tue, 24 May 2011 16:22:10 +0200

Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords:

KDGP1W52

Dataseries X:

» Textbox « » Textfile « » CSV «

476 475 470 461 455 456 517 525 523 519 509 512 519 517 510 509 501 507 569 580 578 565 547 555 562 561 555 544 537 543 594 611 613 611 594 595 591 589 584 573 567 569 621 629 628 612 595 597 593 590 580 574 573 573 620 626 620 588 566 577 561 549 532 526 511 499 555 565 542 527 510 514 517 508 493 490 469 478 528 534 518 506 502 516 528 533 536 537 524 536 587 597 581 564 558 575 580 575 563 552 537 545 601 604 586 564 549 551 556

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 'RServer@AstonUniversity' @ vre.aston.ac.uk Central Tendency - Ungrouped Data Measure Value S.E. Value/S.E. Arithmetic Mean 550.266055045872 4.00022600028034 137.558741682922 Geometric Mean 548.670601930839 Harmonic Mean 547.05000426805 Quadratic Mean 551.834147734176 Winsorized Mean ( 1 / 36 ) 550.266055045872 3.996550547187 137.685248453365 Winsorized Mean ( 2 / 36 ) 550.321100917431 3.97043270142588 138.604817736817 Winsorized Mean ( 3 / 36 ) 550.403669724771 3.90254887795497 141.036970179652 Winsorized Mean ( 4 / 36 ) 550.403669724771 3.88937930356269 141.514526294876 Winsorized Mean ( 5 / 36 ) 550.633027522936 3.8465437520324 143.150075241442 Winsorized Mean ( 6 / 36 ) 550.302752293578 3.77469228317756 145.787447296321 Winsorized Mean ( 7 / 36 ) 550.366972477064 3.74164968019907 147.092063532731 Winsorized Mean ( 8 / 36 ) 551.174311926605 3.58167277828479 153.887400118822 Winsorized Mean ( 9 / 36 ) 551.422018348624 3.54317320786054 155.629427634329 Winsorized Mean ( 10 / 36 ) 551.330275229358 3.36483723787986 163.850503383261 Winsorized Mean ( 11 / 36 ) 551.229357798165 3.29291584646804 167.398556021227 Winsorized Mean ( 12 / 36 ) 550.899082568807 3.21734872462654 171.227656595651 Winsorized Mean ( 13 / 36 ) 551.376146788991 3.15196676598186 174.930825013706 Winsorized Mean ( 14 / 36 ) 551.247706422018 3.10092321162707 177.76889938941 Winsorized Mean ( 15 / 36 ) 551.385321100917 3.08286585587191 178.854788654102 Winsorized Mean ( 16 / 36 ) 551.385321100917 3.04471457214592 181.095898494124 Winsorized Mean ( 17 / 36 ) 551.385321100917 3.04471457214592 181.095898494124 Winsorized Mean ( 18 / 36 ) 551.385321100917 3.0022335172156 183.658372321516 Winsorized Mean ( 19 / 36 ) 551.036697247706 2.95805214254236 186.283632165492 Winsorized Mean ( 20 / 36 ) 551.036697247706 2.91174192082805 189.246407212835 Winsorized Mean ( 21 / 36 ) 551.036697247706 2.86355610242469 192.430906725075 Winsorized Mean ( 22 / 36 ) 551.238532110092 2.7884067516173 197.689426691557 Winsorized Mean ( 23 / 36 ) 551.449541284404 2.71106911110743 203.406670462615 Winsorized Mean ( 24 / 36 ) 551.449541284404 2.65790757692667 207.475062741663 Winsorized Mean ( 25 / 36 ) 550.990825688073 2.6033674647361 211.645429679642 Winsorized Mean ( 26 / 36 ) 550.275229357798 2.52095773939684 218.280227692137 Winsorized Mean ( 27 / 36 ) 550.275229357798 2.46297322318712 223.419087214328 Winsorized Mean ( 28 / 36 ) 550.532110091743 2.43196828228034 226.373063375455 Winsorized Mean ( 29 / 36 ) 550.532110091743 2.43196828228034 226.373063375455 Winsorized Mean ( 30 / 36 ) 551.08256880734 2.24039947624932 245.97513731342 Winsorized Mean ( 31 / 36 ) 551.08256880734 2.17600233075552 253.254585722802 Winsorized Mean ( 32 / 36 ) 550.788990825688 2.07815660176275 265.037288507754 Winsorized Mean ( 33 / 36 ) 551.091743119266 2.04355152481927 269.673524952107 Winsorized Mean ( 34 / 36 ) 551.091743119266 1.97454671780875 279.097849723626 Winsorized Mean ( 35 / 36 ) 551.091743119266 1.9040231956739 289.435414637487 Winsorized Mean ( 36 / 36 ) 551.091743119266 1.9040231956739 289.435414637487 Trimmed Mean ( 1 / 36 ) 550.420560747664 3.90659858434902 140.895090412619 Trimmed Mean ( 2 / 36 ) 550.580952380952 3.80571627488242 144.67209655506 Trimmed Mean ( 3 / 36 ) 550.718446601942 3.70793668955678 148.524231320619 Trimmed Mean ( 4 / 36 ) 550.831683168317 3.6264449303768 151.893022986312 Trimmed Mean ( 5 / 36 ) 550.949494949495 3.53891036438854 155.68337093067 Trimmed Mean ( 6 / 36 ) 551.020618556701 3.45208299652757 159.619748166822 Trimmed Mean ( 7 / 36 ) 551.157894736842 3.37135405621162 163.482649863295 Trimmed Mean ( 8 / 36 ) 551.290322580645 3.28701742530651 167.717493170648 Trimmed Mean ( 9 / 36 ) 551.307692307692 3.22386901949659 171.008092752409 Trimmed Mean ( 10 / 36 ) 551.29213483146 3.15901365533035 174.514008162402 Trimmed Mean ( 11 / 36 ) 551.287356321839 3.11599284331971 176.921894253939 Trimmed Mean ( 12 / 36 ) 551.294117647059 3.07801563679255 179.106990574465 Trimmed Mean ( 13 / 36 ) 551.33734939759 3.04551027840049 181.032831610457 Trimmed Mean ( 14 / 36 ) 551.333333333333 3.01708100285322 182.737332147179 Trimmed Mean ( 15 / 36 ) 551.341772151899 2.99067500627661 184.353622842597 Trimmed Mean ( 16 / 36 ) 551.337662337662 2.96162574680164 186.16047720853 Trimmed Mean ( 17 / 36 ) 551.333333333333 2.93216602490336 188.029371001086 Trimmed Mean ( 18 / 36 ) 551.328767123288 2.8967555720471 190.326298995835 Trimmed Mean ( 19 / 36 ) 551.323943661972 2.86024401654123 192.754163796369 Trimmed Mean ( 20 / 36 ) 551.347826086957 2.8224548763385 195.343362513631 Trimmed Mean ( 21 / 36 ) 551.373134328358 2.78327984312808 198.10193922458 Trimmed Mean ( 22 / 36 ) 551.4 2.74254233541407 201.054325718093 Trimmed Mean ( 23 / 36 ) 551.412698412698 2.70362587894669 203.953033112527 Trimmed Mean ( 24 / 36 ) 551.409836065574 2.66687605556144 206.762453363994 Trimmed Mean ( 25 / 36 ) 551.406779661017 2.62892228954784 209.746321469189 Trimmed Mean ( 26 / 36 ) 551.438596491228 2.58950280495203 212.951534725773 Trimmed Mean ( 27 / 36 ) 551.527272727273 2.55206452973714 216.110237927283 Trimmed Mean ( 28 / 36 ) 551.622641509434 2.51327771795848 219.483361336412 Trimmed Mean ( 29 / 36 ) 551.705882352941 2.46851453587797 223.497117126239 Trimmed Mean ( 30 / 36 ) 551.795918367347 2.41064454781612 228.899743376615 Trimmed Mean ( 31 / 36 ) 551.851063829787 2.37080194697687 232.769786836678 Trimmed Mean ( 32 / 36 ) 551.911111111111 2.32939542644647 236.933199423793 Trimmed Mean ( 33 / 36 ) 552 2.29183151526288 240.855401596432 Trimmed Mean ( 34 / 36 ) 552.073170731707 2.24705504939309 245.687425806866 Trimmed Mean ( 35 / 36 ) 552.153846153846 2.1997234710083 251.01057175189 Trimmed Mean ( 36 / 36 ) 552.243243243243 2.14923878046241 256.948296421688 Median 555 Midrange 542 Midmean - Weighted Average at Xnp 551.527272727273 Midmean - Weighted Average at X(n+1)p 551.527272727273 Midmean - Empirical Distribution Function 551.527272727273 Midmean - Empirical Distribution Function - Averaging 551.527272727273 Midmean - Empirical Distribution Function - Interpolation 551.527272727273 Midmean - Closest Observation 549.741379310345 Midmean - True Basic - Statistics Graphics Toolkit 551.527272727273 Midmean - MS Excel (old versions) 551.527272727273 Number of observations 109

Charts produced by software:

http://www.freestatistics.org/blog/date/2011/May/24/t13062469296ga0r6fnp6im9bf/13udk1306246713.png (open in new window) http://www.freestatistics.org/blog/date/2011/May/24/t13062469296ga0r6fnp6im9bf/13udk1306246713.ps (open in new window) http://www.freestatistics.org/blog/date/2011/May/24/t13062469296ga0r6fnp6im9bf/2hgnr1306246713.png (open in new window) http://www.freestatistics.org/blog/date/2011/May/24/t13062469296ga0r6fnp6im9bf/2hgnr1306246713.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