verbetering opdracht 5

*Unverified author*

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

Title produced by software: Central Tendency

Date of computation: Thu, 09 Dec 2010 21:06:47 +0000

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2010/Dec/09/t1291929114adpzq7n6t8ppn4z.htm/, Retrieved Thu, 09 Dec 2010 22:11:55 +0100

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/2010/Dec/09/t1291929114adpzq7n6t8ppn4z.htm/}, year = {2010}, } @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 = {2010}, 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:

KDGP1W52 - Evi Van Dingenen

Dataseries X:

» Textbox « » Textfile « » CSV «

84,9 81,9 95,9 81 89,2 102,5 89,8 88,8 83,2 90,2 100,4 187,1 87,6 85,4 86,1 86,7 89,1 103,7 86,9 85,2 80,8 91,2 102,8 182,5 80,9 83,1 88,3 86,6 93 105,3 93,8 86,4 87 96,7 100,5 196,7 86,8 88,2 93,8 85 90,4 115,9 94,9 87,7 91,7 95,9 106,8 204,5 90,2 90,5 93,2 97,8 99,4 120 108,2 98,5 104,3 102,9 111,1 188,1 93,8 94,5 112,4 102,5 115,8 136,5 122,1 110,6 116,4 112,6 121,5 199,3 102,1 100,6 119 106,8 121,3 145,5 129,7 117,7 121,3 124,3 135,2 210,1 106,8 110,5 111,5 122,1 126,3 143,2 137,3 121,5 121,9 123,9 131,6 220,9

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 3 seconds R Server 'RServer@AstonUniversity' @ vre.aston.ac.uk Central Tendency - Ungrouped Data Measure Value S.E. Value/S.E. Arithmetic Mean 110.792708333333 3.17111699452483 34.9380702524143 Geometric Mean 107.41167076504 Harmonic Mean 104.739701535714 Quadratic Mean 115.023226368272 Winsorized Mean ( 1 / 32 ) 110.68125 3.13164567482904 35.3428393542773 Winsorized Mean ( 2 / 32 ) 110.566666666667 3.09329164748077 35.7440161701902 Winsorized Mean ( 3 / 32 ) 110.432291666667 3.03950108974205 36.3323744279488 Winsorized Mean ( 4 / 32 ) 110.373958333333 3.00156839294486 36.7720950796143 Winsorized Mean ( 5 / 32 ) 109.93125 2.86894989365875 38.3175914793707 Winsorized Mean ( 6 / 32 ) 109.975 2.84090924720893 38.711197870205 Winsorized Mean ( 7 / 32 ) 109.646875 2.74543638604786 39.937867639993 Winsorized Mean ( 8 / 32 ) 106.580208333333 1.97525404750242 53.9577217766479 Winsorized Mean ( 9 / 32 ) 106.383333333333 1.92908410834676 55.1470684316116 Winsorized Mean ( 10 / 32 ) 105.841666666667 1.80233624378819 58.724706353464 Winsorized Mean ( 11 / 32 ) 105.784375 1.78164701061955 59.3744857255505 Winsorized Mean ( 12 / 32 ) 105.646875 1.74958889477292 60.3838280613413 Winsorized Mean ( 13 / 32 ) 105.172916666667 1.66386484614667 63.2100118649874 Winsorized Mean ( 14 / 32 ) 104.910416666667 1.61661634880548 64.895061060211 Winsorized Mean ( 15 / 32 ) 104.394791666667 1.5318192155709 68.1508565798734 Winsorized Mean ( 16 / 32 ) 104.078125 1.48073980081926 70.287922930427 Winsorized Mean ( 17 / 32 ) 104.113541666667 1.45780312651725 71.418108366524 Winsorized Mean ( 18 / 32 ) 103.794791666667 1.40834244504864 73.6999669587334 Winsorized Mean ( 19 / 32 ) 103.89375 1.39653692335343 74.3938439884033 Winsorized Mean ( 20 / 32 ) 103.872916666667 1.38836840942085 74.8165371394446 Winsorized Mean ( 21 / 32 ) 103.894791666667 1.36361263100555 76.1908399088774 Winsorized Mean ( 22 / 32 ) 103.963541666667 1.3556397141685 76.6896547660041 Winsorized Mean ( 23 / 32 ) 103.939583333333 1.34636244758898 77.200298864147 Winsorized Mean ( 24 / 32 ) 104.089583333333 1.32923147493655 78.3080940347897 Winsorized Mean ( 25 / 32 ) 103.855208333333 1.27175099435715 81.663162674255 Winsorized Mean ( 26 / 32 ) 103.584375 1.23587042992879 83.8149149712795 Winsorized Mean ( 27 / 32 ) 103.275 1.1819391960494 87.377591288278 Winsorized Mean ( 28 / 32 ) 102.925 1.13042357377239 91.0499412680538 Winsorized Mean ( 29 / 32 ) 102.985416666667 1.08720325570941 94.7250811895955 Winsorized Mean ( 30 / 32 ) 103.110416666667 1.06556907533621 96.765586627158 Winsorized Mean ( 31 / 32 ) 102.496875 0.891700835291796 114.945361654236 Winsorized Mean ( 32 / 32 ) 102.496875 0.876300353466007 116.965461208131 Trimmed Mean ( 1 / 32 ) 109.940425531915 2.99887698005409 36.6605320135312 Trimmed Mean ( 2 / 32 ) 109.167391304348 2.84343911197446 38.3927304244412 Trimmed Mean ( 3 / 32 ) 108.421111111111 2.6852584549534 40.3764155033607 Trimmed Mean ( 4 / 32 ) 107.689772727273 2.52333935157557 42.6774831772156 Trimmed Mean ( 5 / 32 ) 106.940697674419 2.34424135238105 45.6184673842558 Trimmed Mean ( 6 / 32 ) 106.257142857143 2.17500818425817 48.8536749545077 Trimmed Mean ( 7 / 32 ) 105.531707317073 1.97649990541054 53.3932265962609 Trimmed Mean ( 8 / 32 ) 104.82625 1.75932573367854 59.5831959899891 Trimmed Mean ( 9 / 32 ) 104.55641025641 1.7077818304353 61.2235171923336 Trimmed Mean ( 10 / 32 ) 104.3 1.65705932725267 62.9428278665945 Trimmed Mean ( 11 / 32 ) 104.1 1.62291759888346 64.1437372246252 Trimmed Mean ( 12 / 32 ) 103.895833333333 1.58620746982352 65.499523429235 Trimmed Mean ( 13 / 32 ) 103.695714285714 1.54840255051593 66.9694804178426 Trimmed Mean ( 14 / 32 ) 103.535294117647 1.51889730100503 68.1647758865195 Trimmed Mean ( 15 / 32 ) 103.392424242424 1.4916165267807 69.3156869651828 Trimmed Mean ( 16 / 32 ) 103.2921875 1.47292917703231 70.1270564197224 Trimmed Mean ( 17 / 32 ) 103.216129032258 1.45806749951727 70.7896781640292 Trimmed Mean ( 18 / 32 ) 103.131666666667 1.44271693561449 71.4843391110125 Trimmed Mean ( 19 / 32 ) 103.070689655172 1.43102349502702 72.0258542318525 Trimmed Mean ( 20 / 32 ) 102.996428571429 1.41725902527111 72.6729741951905 Trimmed Mean ( 21 / 32 ) 102.918518518519 1.40042190426728 73.4910802272596 Trimmed Mean ( 22 / 32 ) 102.832692307692 1.38238138342669 74.3880766484191 Trimmed Mean ( 23 / 32 ) 102.734 1.35982775019636 75.5492745203689 Trimmed Mean ( 24 / 32 ) 102.629166666667 1.33188848466349 77.0553750170735 Trimmed Mean ( 25 / 32 ) 102.502173913043 1.29809406599013 78.9635948569407 Trimmed Mean ( 26 / 32 ) 102.384090909091 1.26547897316403 80.9054066327978 Trimmed Mean ( 27 / 32 ) 102.278571428571 1.22992844996603 83.1581474771125 Trimmed Mean ( 28 / 32 ) 102.19 1.19445191808435 85.5538832939305 Trimmed Mean ( 29 / 32 ) 102.123684210526 1.15847077679598 88.1538716867536 Trimmed Mean ( 30 / 32 ) 102.044444444444 1.11895248948351 91.1964050337353 Trimmed Mean ( 31 / 32 ) 101.944117647059 1.06851881735358 95.406946505206 Trimmed Mean ( 32 / 32 ) 101.890625 1.0469748989408 97.3190714534613 Median 102.3 Midrange 150.85 Midmean - Weighted Average at Xnp 102.734 Midmean - Weighted Average at X(n+1)p 103.010204081633 Midmean - Empirical Distribution Function 102.734 Midmean - Empirical Distribution Function - Averaging 103.010204081633 Midmean - Empirical Distribution Function - Interpolation 103.010204081633 Midmean - Closest Observation 102.734 Midmean - True Basic - Statistics Graphics Toolkit 103.010204081633 Midmean - MS Excel (old versions) 102.734 Number of observations 96

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Dec/09/t1291929114adpzq7n6t8ppn4z/18sc61291928803.png (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/09/t1291929114adpzq7n6t8ppn4z/18sc61291928803.ps (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/09/t1291929114adpzq7n6t8ppn4z/2j2t91291928803.png (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/09/t1291929114adpzq7n6t8ppn4z/2j2t91291928803.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