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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 13:50:04 -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/t119783720252hrmvwitg310cv.htm/, Retrieved Sun, 16 Dec 2007 21:33:22 +0100

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Dataseries X:

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0.112099938198320 -7.5234317022524 -0.174508990247777 -2.7838976248972 3.32086811233621 -2.45317788349593 3.18406012068406 -5.44042146983815 0.649481017642372 -1.07642801808016 -6.95667668647274 -1.51981598559022 4.16227230153779 1.31150417256041 -3.04705830224746 -1.92422722261651 2.75950343482618 -6.41361862382443 -1.11530752560768 -1.56757720439110 -1.87571926492828 -0.248344227067880 5.19714930126309 0.523454484546629 1.7483538545492 -0.151122707042641 6.41455842806672 -2.33399246036476 -0.345905183770059 -1.93508355264285 5.12010225384436 -1.81633381269994 11.8083712468710 0.951312732337543 -2.00735217132620 1.39325355869821 5.89468248583685 2.47323836463487 -10.8055792141131 1.87601361620464 -4.67348222231403 -7.31601418786265 4.05419945496961 -0.73915923860179 4.19522631703279 -6.8416643186816 0.922135364442534 3.04248996617448 6.7374333015147 -1.80882009330620 1.70018100638115 -3.87944179177855 2.02934054306604 2.46312058350850 0.0958696906479143 2.06857942650907 0.451957173332116 -0.169740018337748 8.36055226069874 6.95713440198822 -0.737722119028973 10.8460464500845 10.4303191959713 -9.3254800323235 2.98350849441621 -3.37677921920559 -4.70835338252925 -1.60721490048834 -3.14479871850406 5.22904587501341 1.71870765649422 7.8616002868662 16.6634543338289 -1.86414944852601 -2.56744340647083 0.579191901975491 -3.42163983030900 -6.11260379447978 6.30214100944247 -3.35893281479719 -2.22878328457179 -1.44249975349172 8.89655891765128 4.94508794854377 -2.25423698595273 1.09067021401188 -3.32773833069336 0.423899895235991 -0.782494091513541 5.71247870563437 3.12159570925235 -4.26681435448836 6.29041863604803

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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 3 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 0.554856322296781 0.494858168929813 1.12124313012094 Geometric Mean NaN Harmonic Mean -114.274537335474 Quadratic Mean 4.77883347849628 Winsorized Mean ( 1 / 31 ) 0.518566172778842 0.475046618247806 1.09161112374941 Winsorized Mean ( 2 / 31 ) 0.536624743387113 0.461810291036319 1.16200256642811 Winsorized Mean ( 3 / 31 ) 0.529905074363776 0.457346722832824 1.15865064273670 Winsorized Mean ( 4 / 31 ) 0.479392266753879 0.439845672914995 1.08991015775328 Winsorized Mean ( 5 / 31 ) 0.456758165186062 0.432852864612313 1.05522731285412 Winsorized Mean ( 6 / 31 ) 0.452183566542490 0.421606285957475 1.07252567526495 Winsorized Mean ( 7 / 31 ) 0.406762519351809 0.40512407409779 1.00404430484085 Winsorized Mean ( 8 / 31 ) 0.445685635409281 0.392033896427411 1.13685484717213 Winsorized Mean ( 9 / 31 ) 0.485284978686144 0.375510198255776 1.29233501763804 Winsorized Mean ( 10 / 31 ) 0.476946671330334 0.37288322685289 1.27907783719781 Winsorized Mean ( 11 / 31 ) 0.52366065454263 0.365608783319934 1.432297795987 Winsorized Mean ( 12 / 31 ) 0.522581481961808 0.349990150312386 1.49313196812932 Winsorized Mean ( 13 / 31 ) 0.561105958913119 0.337264672792221 1.66369621302970 Winsorized Mean ( 14 / 31 ) 0.495084334469617 0.324578637853322 1.52531398167167 Winsorized Mean ( 15 / 31 ) 0.492818178124146 0.323391176833797 1.52390730925050 Winsorized Mean ( 16 / 31 ) 0.484929565080722 0.320607409849917 1.51253386597561 Winsorized Mean ( 17 / 31 ) 0.486378277092637 0.311321544165025 1.56230201927438 Winsorized Mean ( 18 / 31 ) 0.360161267688563 0.287036578569949 1.25475738835423 Winsorized Mean ( 19 / 31 ) 0.407192736239638 0.279246408428985 1.45818432734898 Winsorized Mean ( 20 / 31 ) 0.430500558144625 0.27015370731683 1.59353933144343 Winsorized Mean ( 21 / 31 ) 0.290711502092706 0.243713792047818 1.19283976360134 Winsorized Mean ( 22 / 31 ) 0.286542722442582 0.23593903090127 1.21447783076844 Winsorized Mean ( 23 / 31 ) 0.290819006835564 0.231512148652672 1.25617168916638 Winsorized Mean ( 24 / 31 ) 0.276973318655711 0.228025130923947 1.21466137321543 Winsorized Mean ( 25 / 31 ) 0.320642577120044 0.218934859167137 1.4645569843917 Winsorized Mean ( 26 / 31 ) 0.27822163665151 0.208407049668300 1.33499148466583 Winsorized Mean ( 27 / 31 ) 0.198264260474583 0.197454657189895 1.00410019847701 Winsorized Mean ( 28 / 31 ) 0.209822593202885 0.195372468379812 1.07396192996335 Winsorized Mean ( 29 / 31 ) 0.0904014224790397 0.179870334049069 0.502592175396628 Winsorized Mean ( 30 / 31 ) 0.0931681167961494 0.176541645206855 0.527740164010502 Winsorized Mean ( 31 / 31 ) 0.0445637143069294 0.170210096807018 0.261815927156514 Trimmed Mean ( 1 / 31 ) 0.502678712680053 0.456460680168367 1.10125304219991 Trimmed Mean ( 2 / 31 ) 0.486077209430757 0.434998886092766 1.11742173364347 Trimmed Mean ( 3 / 31 ) 0.45906042404029 0.418506961766867 1.09690032897473 Trimmed Mean ( 4 / 31 ) 0.433222963334077 0.401419641474416 1.0792271193877 Trimmed Mean ( 5 / 31 ) 0.420289995809856 0.387937202177224 1.08339698655107 Trimmed Mean ( 6 / 31 ) 0.411915823582727 0.374429896134589 1.10011467523059 Trimmed Mean ( 7 / 31 ) 0.404015190470369 0.36175281725008 1.11682665954491 Trimmed Mean ( 8 / 31 ) 0.403541161553905 0.351002139024139 1.14968291269061 Trimmed Mean ( 9 / 31 ) 0.397008768106322 0.341356000286488 1.16303439158276 Trimmed Mean ( 10 / 31 ) 0.384513048800502 0.333453381645166 1.15312385468524 Trimmed Mean ( 11 / 31 ) 0.372405546131102 0.324644575868122 1.14711772138889 Trimmed Mean ( 12 / 31 ) 0.353872311503602 0.315566494152385 1.12138746686053 Trimmed Mean ( 13 / 31 ) 0.353872311503602 0.307670923580919 1.15016494696657 Trimmed Mean ( 14 / 31 ) 0.309401691144075 0.300448588228388 1.02979911794054 Trimmed Mean ( 15 / 31 ) 0.289822909024715 0.294037668147949 0.985665921139352 Trimmed Mean ( 16 / 31 ) 0.269190602985101 0.286434791769073 0.93979715705111 Trimmed Mean ( 17 / 31 ) 0.247936658626105 0.277643715181341 0.893002956916084 Trimmed Mean ( 18 / 31 ) 0.225052168928078 0.268538622075561 0.838062574346395 Trimmed Mean ( 19 / 31 ) 0.212360102074821 0.26189340330481 0.810864647200223 Trimmed Mean ( 20 / 31 ) 0.194366621461784 0.254929835483203 0.76243183185434 Trimmed Mean ( 21 / 31 ) 0.172836762528937 0.247782913146354 0.697533015227929 Trimmed Mean ( 22 / 31 ) 0.162183360410928 0.243756330081973 0.665350353594458 Trimmed Mean ( 23 / 31 ) 0.150998234038642 0.239854855366859 0.629540034983615 Trimmed Mean ( 24 / 31 ) 0.138434628367035 0.235449185408240 0.587959682795276 Trimmed Mean ( 25 / 31 ) 0.125950037091020 0.230219635119300 0.547086424777594 Trimmed Mean ( 26 / 31 ) 0.125950037091020 0.224953299639794 0.55989415266501 Trimmed Mean ( 27 / 31 ) 0.0926993689651418 0.220073523041257 0.42121999813564 Trimmed Mean ( 28 / 31 ) 0.0828720066924911 0.215812973020230 0.383999189356993 Trimmed Mean ( 29 / 31 ) 0.0708246551154843 0.210104967501417 0.337091768737009 Trimmed Mean ( 30 / 31 ) 0.0689222106381482 0.205962741931941 0.334634361494969 Trimmed Mean ( 31 / 31 ) 0.0664976200223481 0.200533146843724 0.331604131631017 Median 0.0958696906479143 Midrange 2.9289375598579 Midmean - Weighted Average at Xnp 0.0864200280557354 Midmean - Weighted Average at X(n+1)p 0.150998234038642 Midmean - Empirical Distribution Function 0.150998234038642 Midmean - Empirical Distribution Function - Averaging 0.150998234038642 Midmean - Empirical Distribution Function - Interpolation 0.150998234038642 Midmean - Closest Observation 0.0992275945719046 Midmean - True Basic - Statistics Graphics Toolkit 0.150998234038642 Midmean - MS Excel (old versions) 0.150998234038642 Number of observations 93

Charts produced by software:

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2007/Dec/16/t119783720252hrmvwitg310cv/10qs91197838198.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2007/Dec/16/t119783720252hrmvwitg310cv/10qs91197838198.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2007/Dec/16/t119783720252hrmvwitg310cv/2rffl1197838198.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2007/Dec/16/t119783720252hrmvwitg310cv/2rffl1197838198.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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