Maarten Verhaegen 2MAR03 - tweede zit - Oefening 5.2 - Centrummaten evolutie prijzen diesel

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

Title produced by software: Central Tendency

Date of computation: Sun, 17 Aug 2008 07:43:10 -0600

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2008/Aug/17/t1218980678bist1d3bej40pb1.htm/, Retrieved Sun, 17 Aug 2008 13:44:38 +0000

IsPrivate?

No (this computation is public)

User-defined keywords:

Dataseries X:

» Textbox « » Textfile « » CSV «

0,6200 0,6200 0,6100 0,6100 0,6100 0,6000 0,5900 0,5900 0,5900 0,5900 0,5900 0,5700 0,5800 0,5700 0,5900 0,6200 0,6200 0,6100 0,6400 0,6500 0,6700 0,6700 0,6900 0,7400 0,7300 0,7400 0,7500 0,7400 0,7600 0,7600 0,7800 0,7900 0,8900 0,8800 0,8800 0,8400 0,7600 0,7700 0,7600 0,7700 0,7800 0,7900 0,7800 0,7600 0,7800 0,7600 0,7400 0,7300 0,7200 0,7100 0,7300 0,7500 0,7500 0,7200 0,7200 0,7200 0,7400 0,7800 0,7400 0,7400 0,7500 0,7800 0,8100 0,7500 0,7000 0,7100 0,7100 0,7300 0,7400 0,7400 0,7500 0,7400 0,7400 0,7300 0,7600 0,8000 0,8300 0,8100 0,8300 0,8800 0,8900 0,9300 0,9100 0,9000 0,8600 0,8800 0,9300 0,9800 0,9700 1,0300 1,0600 1,0600 1,0800 1,0900 1,0400 1,0000

Text written by user:

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 4 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 0.763333333333333 0.0126817200486296 60.191624669701 Geometric Mean 0.753788201775021 Harmonic Mean 0.744659134798744 Quadratic Mean 0.773276308960775 Winsorized Mean ( 1 / 32 ) 0.763229166666667 0.0126538729176980 60.3158552034449 Winsorized Mean ( 2 / 32 ) 0.763020833333333 0.0125141321793889 60.9727324592311 Winsorized Mean ( 3 / 32 ) 0.763333333333333 0.0124672084505597 61.227285671883 Winsorized Mean ( 4 / 32 ) 0.7625 0.0122635531899244 62.176107380238 Winsorized Mean ( 5 / 32 ) 0.761979166666667 0.0121410025450828 62.7608110481183 Winsorized Mean ( 6 / 32 ) 0.760104166666667 0.0117208903990728 64.8503774701962 Winsorized Mean ( 7 / 32 ) 0.758645833333333 0.0114148447051115 66.4613363503416 Winsorized Mean ( 8 / 32 ) 0.7578125 0.0112470299442026 67.3788994747563 Winsorized Mean ( 9 / 32 ) 0.755 0.0103935708873069 72.6410593804714 Winsorized Mean ( 10 / 32 ) 0.756041666666667 0.0102335438789130 73.8787731417803 Winsorized Mean ( 11 / 32 ) 0.75375 0.00983665941369593 76.6266237652315 Winsorized Mean ( 12 / 32 ) 0.7525 0.00963136324176058 78.1301650774876 Winsorized Mean ( 13 / 32 ) 0.751145833333333 0.00941707784190029 79.7642162403277 Winsorized Mean ( 14 / 32 ) 0.752604166666667 0.00919124868822678 81.882689958187 Winsorized Mean ( 15 / 32 ) 0.751041666666667 0.00894976130068179 83.917508124988 Winsorized Mean ( 16 / 32 ) 0.751041666666667 0.00894976130068179 83.917508124988 Winsorized Mean ( 17 / 32 ) 0.751041666666667 0.00894976130068179 83.917508124988 Winsorized Mean ( 18 / 32 ) 0.754791666666667 0.00839012991381899 89.9618568984832 Winsorized Mean ( 19 / 32 ) 0.7528125 0.0074951784574918 100.439569820719 Winsorized Mean ( 20 / 32 ) 0.7528125 0.00628578025729363 119.764368015646 Winsorized Mean ( 21 / 32 ) 0.750625 0.00597291492650768 125.671470167563 Winsorized Mean ( 22 / 32 ) 0.755208333333333 0.00535162536112609 141.117563800173 Winsorized Mean ( 23 / 32 ) 0.7528125 0.00435966139488725 172.676827811181 Winsorized Mean ( 24 / 32 ) 0.7553125 0.00405270411404101 186.372475943443 Winsorized Mean ( 25 / 32 ) 0.752708333333333 0.00369173795028402 203.889968212783 Winsorized Mean ( 26 / 32 ) 0.75 0.00333771641653287 224.704530404378 Winsorized Mean ( 27 / 32 ) 0.7528125 0.00299745186008196 251.150822478736 Winsorized Mean ( 28 / 32 ) 0.749895833333333 0.00263035081905182 285.093466583159 Winsorized Mean ( 29 / 32 ) 0.749895833333333 0.00263035081905182 285.093466583159 Winsorized Mean ( 30 / 32 ) 0.749895833333333 0.00263035081905182 285.093466583159 Winsorized Mean ( 31 / 32 ) 0.753125 0.00226196865428822 332.951121392523 Winsorized Mean ( 32 / 32 ) 0.753125 0.00226196865428822 332.951121392523 Trimmed Mean ( 1 / 32 ) 0.761914893617021 0.0122994333325046 61.9471542321755 Trimmed Mean ( 2 / 32 ) 0.76054347826087 0.0118935436905987 63.9459103229294 Trimmed Mean ( 3 / 32 ) 0.759222222222222 0.0115136869945810 65.9408426318657 Trimmed Mean ( 4 / 32 ) 0.757727272727273 0.0110955846047042 68.2908832407101 Trimmed Mean ( 5 / 32 ) 0.75639534883721 0.0106850353576225 70.7901587145998 Trimmed Mean ( 6 / 32 ) 0.755119047619048 0.0102458225785125 73.7001877431177 Trimmed Mean ( 7 / 32 ) 0.754146341463415 0.00985127467653553 76.553173698394 Trimmed Mean ( 8 / 32 ) 0.753375 0.00946837465835008 79.5675104951201 Trimmed Mean ( 9 / 32 ) 0.752692307692308 0.00905945337949448 83.0836338753043 Trimmed Mean ( 10 / 32 ) 0.752368421052632 0.00876770073492962 85.8113710536758 Trimmed Mean ( 11 / 32 ) 0.751891891891892 0.00845677572985824 88.9099954770227 Trimmed Mean ( 12 / 32 ) 0.751666666666667 0.00816975605070387 92.006011195635 Trimmed Mean ( 13 / 32 ) 0.751571428571429 0.00786963058076231 95.5027584660303 Trimmed Mean ( 14 / 32 ) 0.751617647058824 0.00755317786040694 99.5101215607187 Trimmed Mean ( 15 / 32 ) 0.751515151515151 0.00721705576423487 104.130434357926 Trimmed Mean ( 16 / 32 ) 0.7515625 0.00685818199075046 109.586257846995 Trimmed Mean ( 17 / 32 ) 0.751612903225806 0.00641914091520175 117.089329110355 Trimmed Mean ( 18 / 32 ) 0.751666666666667 0.00587134507860125 128.022907290222 Trimmed Mean ( 19 / 32 ) 0.751379310344828 0.00530639147003658 141.598921713111 Trimmed Mean ( 20 / 32 ) 0.75125 0.00480166705358738 156.456079027540 Trimmed Mean ( 21 / 32 ) 0.751111111111111 0.00444444444444445 169 Trimmed Mean ( 22 / 32 ) 0.751153846153846 0.00406075510065179 184.978859235633 Trimmed Mean ( 23 / 32 ) 0.7508 0.00371252705617847 202.234216381131 Trimmed Mean ( 24 / 32 ) 0.750625 0.00350286420292216 214.28892372528 Trimmed Mean ( 25 / 32 ) 0.750217391304348 0.00329674309248589 227.563195025504 Trimmed Mean ( 26 / 32 ) 0.75 0.00311851864871254 240.498802311037 Trimmed Mean ( 27 / 32 ) 0.75 0.00297101757186175 252.438762767069 Trimmed Mean ( 28 / 32 ) 0.74975 0.00285296741602898 262.796552034783 Trimmed Mean ( 29 / 32 ) 0.749736842105263 0.00278399311307783 269.302692806017 Trimmed Mean ( 30 / 32 ) 0.749722222222222 0.002687009050354 279.017378867202 Trimmed Mean ( 31 / 32 ) 0.749705882352941 0.00255021910622924 293.977047117907 Trimmed Mean ( 32 / 32 ) 0.749375 0.00245678372884603 305.022778847525 Median 0.75 Midrange 0.83 Midmean - Weighted Average at Xnp 0.7508 Midmean - Weighted Average at X(n+1)p 0.751836734693878 Midmean - Empirical Distribution Function 0.7508 Midmean - Empirical Distribution Function - Averaging 0.751836734693878 Midmean - Empirical Distribution Function - Interpolation 0.751836734693878 Midmean - Closest Observation 0.7508 Midmean - True Basic - Statistics Graphics Toolkit 0.751836734693878 Midmean - MS Excel (old versions) 0.7508 Number of observations 96

Charts produced by software:

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Aug/17/t1218980678bist1d3bej40pb1/120jp1218980584.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Aug/17/t1218980678bist1d3bej40pb1/120jp1218980584.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Aug/17/t1218980678bist1d3bej40pb1/2gtsh1218980584.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Aug/17/t1218980678bist1d3bej40pb1/2gtsh1218980584.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