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

Title produced by software: Central Tendency

Date of computation: Sun, 16 Dec 2007 05:13:44 -0700

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2007/Dec/16/t11978063546g9vp3muc3ynnig.htm/, Retrieved Sun, 16 Dec 2007 12:59:16 +0100

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Dataseries X:

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0.102699932769213 0.436932487996657 2.07818217694826 -2.41674270523762 4.05475642104927 -8.4193081920432 -4.46408821795128 -0.497214713009744 4.43917439931882 4.70346267252493 0.594864366573096 0.611494767548666 1.09360599673657 -4.37382959137099 1.83754098364495 -3.06393847776798 0.90521871973667 -2.46114236111540 5.63279287242953 -1.66214129307524 0.247564759774209 -3.41283905100332 0.969424789347048 1.03882496987091 0.816918946896857 -0.83166265589295 -0.178479942110799 -1.60265251127524 3.12985086344751 2.37353836792323 7.69658751199975 5.95185918883425 7.29098470567829 -5.79154346010777 -5.07801578455752 -5.25171136462152 -1.96928620235456 1.60185107603636 -2.54871994912843 0.340673892578518 3.53850575839748 -5.94725691744121 -3.16530996350986 8.14297505767775 -0.750744339534478 -0.954828226619682 5.21659241593746 1.89571043841593 5.56930909964225 -1.25079494414587 6.72548698561079 0.0435781786206917 -4.0887148157548 -5.0146089955484 -9.46383140357744 0.871630377895457 3.77891243916459 -3.28120816338644 1.1275690814888 -1.14657060963980 -0.754992646092887 0.666040477641033 5.46251057858592 -6.98015410474689 4.7959706009719 -2.39231272624927 5.27558711710807 -5.68067940128377 3.72169062479435 -2.36541998156611 -1.35449161454467 6.52892106217763 1.93774442104035 7.71226634349185 -1.28258376857536 4.23051944228423 4.63764350373555 -7.2900814908113 4.37579358037308 -13.5459822979036 12.1562686602948 13.0476986424239 7.78485324010103 0.607420819656909 -3.28744792841272 4.26375546303694 -1.68951118488056 -11.3487058547407 6.68155532724265 9.97957380923293 -7.62124317778233 8.22961700702913 21.0563835153904

Text written by user:

Output produced by software:

Summary of compuational transaction Raw Input view raw input (R code) Raw Output view raw output of R engine Computing time 1 seconds R Server 'Gwilym Jenkins' @ 72.249.127.135 Central Tendency - Ungrouped Data Measure Value S.E. Value/S.E. Arithmetic Mean 0.788495676448986 0.561495878574472 1.40427687278992 Geometric Mean NaN Harmonic Mean 2.31764378532471 Quadratic Mean 5.44309347927643 Winsorized Mean ( 1 / 31 ) 0.726007413762926 0.527248116158539 1.37697488433438 Winsorized Mean ( 2 / 31 ) 0.747371810946456 0.51305613203776 1.45670573700784 Winsorized Mean ( 3 / 31 ) 0.710850145155242 0.49026672073385 1.44992534694424 Winsorized Mean ( 4 / 31 ) 0.669908562878127 0.469141632193402 1.42794524490625 Winsorized Mean ( 5 / 31 ) 0.683054785330796 0.464957880371667 1.46906809017796 Winsorized Mean ( 6 / 31 ) 0.679945467168712 0.457307692019315 1.48684458852267 Winsorized Mean ( 7 / 31 ) 0.752226886898556 0.442900034995333 1.69841234468740 Winsorized Mean ( 8 / 31 ) 0.764272876218241 0.440484822737126 1.73507198606556 Winsorized Mean ( 9 / 31 ) 0.735749771621713 0.432156935681649 1.70250599000847 Winsorized Mean ( 10 / 31 ) 0.721069160502869 0.415026456169201 1.73740529015552 Winsorized Mean ( 11 / 31 ) 0.736417581348616 0.411022898408583 1.79167044999174 Winsorized Mean ( 12 / 31 ) 0.724904358631725 0.406690490558806 1.78244727983603 Winsorized Mean ( 13 / 31 ) 0.721194312989775 0.382862759346629 1.8836888555589 Winsorized Mean ( 14 / 31 ) 0.686750144629108 0.373841716748891 1.83700778661467 Winsorized Mean ( 15 / 31 ) 0.722497080569255 0.365695629710584 1.97567873901323 Winsorized Mean ( 16 / 31 ) 0.82040284292541 0.346996864254783 2.36429468804371 Winsorized Mean ( 17 / 31 ) 0.809154996032041 0.339040715896157 2.38660124903663 Winsorized Mean ( 18 / 31 ) 0.798944363229913 0.337251606759366 2.36898608403065 Winsorized Mean ( 19 / 31 ) 0.736689001007433 0.32212779193096 2.28694642145414 Winsorized Mean ( 20 / 31 ) 0.738595142361177 0.316552519756759 2.33324676400845 Winsorized Mean ( 21 / 31 ) 0.840072417166054 0.299762603632012 2.80245903587536 Winsorized Mean ( 22 / 31 ) 0.813840015436147 0.290807395256319 2.79855336800780 Winsorized Mean ( 23 / 31 ) 0.80914574930106 0.287345919216741 2.81592914737283 Winsorized Mean ( 24 / 31 ) 0.786537197469372 0.282692562844995 2.78230594237686 Winsorized Mean ( 25 / 31 ) 0.784832015730246 0.280616192557859 2.79681656491874 Winsorized Mean ( 26 / 31 ) 0.846441044841981 0.260786888004242 3.24571933550666 Winsorized Mean ( 27 / 31 ) 0.84758231323888 0.240706230884800 3.52123129560582 Winsorized Mean ( 28 / 31 ) 0.838594637627937 0.237485650972065 3.5311381306426 Winsorized Mean ( 29 / 31 ) 0.800022740280525 0.227860360507115 3.511022007075 Winsorized Mean ( 30 / 31 ) 0.748250482790397 0.201652243641156 3.71059835129791 Winsorized Mean ( 31 / 31 ) 0.520115599605406 0.167454604957567 3.10600953456732 Trimmed Mean ( 1 / 31 ) 0.723293370244713 0.504057277526401 1.43494281799518 Trimmed Mean ( 2 / 31 ) 0.720457347242536 0.477164852810158 1.50987094501944 Trimmed Mean ( 3 / 31 ) 0.706072030435268 0.45496511713136 1.55192563967801 Trimmed Mean ( 4 / 31 ) 0.704329423890337 0.439545999757059 1.60240207914445 Trimmed Mean ( 5 / 31 ) 0.713971412065444 0.429157007849263 1.66366015003119 Trimmed Mean ( 6 / 31 ) 0.721070785611918 0.418374468267166 1.72350571151836 Trimmed Mean ( 7 / 31 ) 0.729139677205205 0.407856549330177 1.78773561048038 Trimmed Mean ( 8 / 31 ) 0.725156169781306 0.399009891725918 1.81738895405485 Trimmed Mean ( 9 / 31 ) 0.719093080283581 0.389182432452461 1.84770179823422 Trimmed Mean ( 10 / 31 ) 0.716735283792796 0.379375088641307 1.88925236593607 Trimmed Mean ( 11 / 31 ) 0.716167606984293 0.371181357110610 1.92942774001141 Trimmed Mean ( 12 / 31 ) 0.713686384828981 0.36221408006014 1.97034412552512 Trimmed Mean ( 13 / 31 ) 0.713686384828981 0.352337756954453 2.02557452541551 Trimmed Mean ( 14 / 31 ) 0.7114196540875 0.344847874159344 2.06299562037832 Trimmed Mean ( 15 / 31 ) 0.714020860867126 0.337389808201318 2.11630832796548 Trimmed Mean ( 16 / 31 ) 0.713159343454779 0.329756987275517 2.16268152298142 Trimmed Mean ( 17 / 31 ) 0.70259404107049 0.323626626067553 2.17100196485017 Trimmed Mean ( 18 / 31 ) 0.692366828674799 0.317395487422005 2.18140098430019 Trimmed Mean ( 19 / 31 ) 0.682354999671137 0.309935541158621 2.20160294337434 Trimmed Mean ( 20 / 31 ) 0.677337063102839 0.303326157356404 2.23303215590134 Trimmed Mean ( 21 / 31 ) 0.67175176764105 0.295961181380604 2.26972930878115 Trimmed Mean ( 22 / 31 ) 0.656539114185437 0.28959501990123 2.26709393831896 Trimmed Mean ( 23 / 31 ) 0.642391160784745 0.283049873254407 2.26953346913305 Trimmed Mean ( 24 / 31 ) 0.627407415149945 0.275155379588575 2.2801931624527 Trimmed Mean ( 25 / 31 ) 0.613067231278136 0.265761382201959 2.30683339392121 Trimmed Mean ( 26 / 31 ) 0.613067231278136 0.253738957738432 2.41613363884832 Trimmed Mean ( 27 / 31 ) 0.574649263219155 0.242328301943665 2.37136668977586 Trimmed Mean ( 28 / 31 ) 0.549241081385487 0.231864559074205 2.36880135359415 Trimmed Mean ( 29 / 31 ) 0.52178201941554 0.21814505490715 2.39190395417228 Trimmed Mean ( 30 / 31 ) 0.494742952497626 0.201769807865511 2.45201676966157 Trimmed Mean ( 31 / 31 ) 0.469392199468349 0.187248009304311 2.50679407066754 Median 0.607420819656909 Midrange 3.7552006087434 Midmean - Weighted Average at Xnp 0.561230238619781 Midmean - Weighted Average at X(n+1)p 0.642391160784745 Midmean - Empirical Distribution Function 0.642391160784745 Midmean - Empirical Distribution Function - Averaging 0.642391160784745 Midmean - Empirical Distribution Function - Interpolation 0.642391160784745 Midmean - Closest Observation 0.577734212411825 Midmean - True Basic - Statistics Graphics Toolkit 0.642391160784745 Midmean - MS Excel (old versions) 0.642391160784745 Number of observations 93

Charts produced by software:

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2007/Dec/16/t11978063546g9vp3muc3ynnig/1e2kq1197807221.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2007/Dec/16/t11978063546g9vp3muc3ynnig/1e2kq1197807221.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2007/Dec/16/t11978063546g9vp3muc3ynnig/24rxk1197807221.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2007/Dec/16/t11978063546g9vp3muc3ynnig/24rxk1197807221.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.

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