Home » date » 2007 » Dec » 18 » attachments

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

Title produced by software: Central Tendency

Date of computation: Tue, 18 Dec 2007 15:11:04 -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/18/t11980149979k6pds9rdjno0t9.htm/, Retrieved Tue, 18 Dec 2007 22:56:39 +0100

User-defined keywords:

Dataseries X:

» Textbox « » Textfile « » CSV «

0.0994999450560806 1.99825717723176 1.83154705441599 2.18159297723750 1.13479848700392 -6.4383862528326 -6.7562866020035 -0.570920016403313 6.33952556826501 -3.97873832972808 3.65518039778561 5.00044220689015 -7.02743002814152 -5.9679326844558 -1.05781087858395 -1.96859206140589 2.9718426116535 4.82969463140748 8.93178086894453 -2.3305923824111 -6.69827566269135 -3.16986370774535 2.51301553536254 -4.01863051311034 2.37376209991675 0.367785790036479 4.42223875795675 1.23811104913759 1.88126219634435 2.93148171890854 7.20586257017581 -1.63005325257356 0.594309441143565 -3.55972260988365 3.69863370335997 -0.539244385059902 0.241041065595866 1.76753139714410 -2.24578453534221 4.66129717830692 4.73336932470008 -3.33297550033502 -9.3234256467695 -1.20867773502832 10.8835489931251 -14.8850604685332 3.91093285769709 0.298941929863830 -1.03448704490873 1.49547922744095 8.15870856495184 -1.23772534016017 3.14896856264022 3.9043154716677 -3.35785658770864 -3.49374770512858 -9.25346292379078 -0.951641054666695 0.932209604490978 1.22123149867532 -2.04888656736102 1.74289907816103 15.0494923575221 -4.98550826411743 2.44257438021663 8.2713433232319 -1.78033952689222 -10.3398446324173 -5.03214663708356 1.10826186805551 0.638187445170956 3.54782757037275 -1.63760150600390 -0.753651967078596 -5.08799233544858 -0.378034251565197 3.30634354460385 -3.43422164024012 0.323260117792316 -2.4808409451107 1.74276457243367 8.8891156147163 10.9117556027005 -4.66216798511671 8.46303294471807 8.64074012324824 -1.44365618249944 -4.0770642141639 8.06322775217745 9.0889200099688 2.35269823813752 -0.290884375500326 0.103410219717261

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 2 seconds R Server 'Gwilym Jenkins' @ 72.249.127.135 Central Tendency - Ungrouped Data Measure Value S.E. Value/S.E. Arithmetic Mean 0.556708497714817 0.526289797748209 1.05779838426806 Geometric Mean NaN Harmonic Mean 3.42257853047415 Quadratic Mean 5.07859939974617 Winsorized Mean ( 1 / 31 ) 0.561089993212605 0.500971483880143 1.12000385504346 Winsorized Mean ( 2 / 31 ) 0.582341872267926 0.495875743932743 1.17437055430344 Winsorized Mean ( 3 / 31 ) 0.526707476778326 0.483259739594033 1.08990555931846 Winsorized Mean ( 4 / 31 ) 0.615692154396605 0.462782680516274 1.33041312978642 Winsorized Mean ( 5 / 31 ) 0.627975927079927 0.459753594784636 1.36589671990296 Winsorized Mean ( 6 / 31 ) 0.615694343069869 0.456003028839288 1.35019792442401 Winsorized Mean ( 7 / 31 ) 0.621880102417181 0.450084053491747 1.38169770200175 Winsorized Mean ( 8 / 31 ) 0.645859796773364 0.440214215141026 1.46714888924352 Winsorized Mean ( 9 / 31 ) 0.720115176521154 0.424859992792763 1.69494701486852 Winsorized Mean ( 10 / 31 ) 0.715853336262082 0.422020964802536 1.69625065095292 Winsorized Mean ( 11 / 31 ) 0.619960917989065 0.402570131881086 1.54000724070655 Winsorized Mean ( 12 / 31 ) 0.549896824710345 0.376988116752107 1.45865824484843 Winsorized Mean ( 13 / 31 ) 0.444501828199735 0.335287365847508 1.32573390314355 Winsorized Mean ( 14 / 31 ) 0.427594363231913 0.330238369276828 1.29480521651157 Winsorized Mean ( 15 / 31 ) 0.418492246566567 0.327057838295446 1.27956647896793 Winsorized Mean ( 16 / 31 ) 0.47818146350442 0.314979282845886 1.51813623798993 Winsorized Mean ( 17 / 31 ) 0.446542541298864 0.307068044264702 1.45421364951258 Winsorized Mean ( 18 / 31 ) 0.359101282839922 0.291933385586878 1.23007953378821 Winsorized Mean ( 19 / 31 ) 0.37335080610379 0.289560014122138 1.28937279974820 Winsorized Mean ( 20 / 31 ) 0.33446893923624 0.283018702370115 1.18179094326721 Winsorized Mean ( 21 / 31 ) 0.361488597594535 0.276599908869299 1.30690063880443 Winsorized Mean ( 22 / 31 ) 0.499087937109368 0.251437586242734 1.98493767207722 Winsorized Mean ( 23 / 31 ) 0.476524327963197 0.238887916857063 1.99476111740018 Winsorized Mean ( 24 / 31 ) 0.457797325409715 0.230909689344202 1.98258170417139 Winsorized Mean ( 25 / 31 ) 0.463112383741562 0.218237133152033 2.12206042598139 Winsorized Mean ( 26 / 31 ) 0.474276619692792 0.214031297930738 2.21592180339098 Winsorized Mean ( 27 / 31 ) 0.407440399005987 0.192439944992239 2.11723402343738 Winsorized Mean ( 28 / 31 ) 0.429207197294024 0.184651634851386 2.32441590695618 Winsorized Mean ( 29 / 31 ) 0.410103360958361 0.181833913004382 2.25537334693159 Winsorized Mean ( 30 / 31 ) 0.463436653956713 0.173779228299162 2.6668127053649 Winsorized Mean ( 31 / 31 ) 0.47504518110313 0.158962685433049 2.98840686925365 Trimmed Mean ( 1 / 31 ) 0.567136905477902 0.484352230252854 1.17091833185496 Trimmed Mean ( 2 / 31 ) 0.573455589080965 0.465260640337124 1.23254696263463 Trimmed Mean ( 3 / 31 ) 0.568706023929313 0.446424646319113 1.27391269415442 Trimmed Mean ( 4 / 31 ) 0.584023141125556 0.430301167339041 1.35724275334209 Trimmed Mean ( 5 / 31 ) 0.575152001865894 0.418919682574045 1.37294098556526 Trimmed Mean ( 6 / 31 ) 0.563022063483413 0.406643560424842 1.38455915272627 Trimmed Mean ( 7 / 31 ) 0.552687628881007 0.393377054331120 1.40498186865721 Trimmed Mean ( 8 / 31 ) 0.540749038827456 0.379336886237320 1.42551135533167 Trimmed Mean ( 9 / 31 ) 0.52445687134584 0.365132884153196 1.43634521596745 Trimmed Mean ( 10 / 31 ) 0.496760946868969 0.3516918901341 1.41248905875980 Trimmed Mean ( 11 / 31 ) 0.468062929666772 0.336337575505359 1.39164626183527 Trimmed Mean ( 12 / 31 ) 0.449450923192499 0.322189417618896 1.39498971292762 Trimmed Mean ( 13 / 31 ) 0.449450923192499 0.310463965346318 1.44767500695658 Trimmed Mean ( 14 / 31 ) 0.437098124990891 0.304227206306314 1.43674896896234 Trimmed Mean ( 15 / 31 ) 0.438100222319218 0.297573803419004 1.47224055775617 Trimmed Mean ( 16 / 31 ) 0.440093164117029 0.290053187298136 1.51728435814316 Trimmed Mean ( 17 / 31 ) 0.436340821062974 0.2830188124127 1.54173787015507 Trimmed Mean ( 18 / 31 ) 0.435361708594514 0.275780939022562 1.57865046851152 Trimmed Mean ( 19 / 31 ) 0.442525566771461 0.269500017482139 1.64202425998280 Trimmed Mean ( 20 / 31 ) 0.448914099782477 0.262069201073118 1.71296015687562 Trimmed Mean ( 21 / 31 ) 0.459348805596987 0.253921320240807 1.80902023178425 Trimmed Mean ( 22 / 31 ) 0.468193314191961 0.244866979326627 1.91203124030635 Trimmed Mean ( 23 / 31 ) 0.465414590854128 0.238368864295213 1.95249741290761 Trimmed Mean ( 24 / 31 ) 0.464416324621140 0.232417735720430 1.99819657988483 Trimmed Mean ( 25 / 31 ) 0.465012804201239 0.22619636771055 2.05579253507858 Trimmed Mean ( 26 / 31 ) 0.465012804201239 0.220586435696142 2.10807524376428 Trimmed Mean ( 27 / 31 ) 0.464351407150209 0.213880379837001 2.17107996303398 Trimmed Mean ( 28 / 31 ) 0.469649428929401 0.209670694831470 2.23993834382481 Trimmed Mean ( 29 / 31 ) 0.473487314176431 0.205437968447942 2.30477023187860 Trimmed Mean ( 30 / 31 ) 0.479646883297936 0.199873264438779 2.39975508802905 Trimmed Mean ( 31 / 31 ) 0.481267906232059 0.193937653046555 2.4815599171788 Median 0.367785790036479 Midrange 0.0822159444944495 Midmean - Weighted Average at Xnp 0.403655265772613 Midmean - Weighted Average at X(n+1)p 0.465414590854128 Midmean - Empirical Distribution Function 0.465414590854128 Midmean - Empirical Distribution Function - Averaging 0.465414590854128 Midmean - Empirical Distribution Function - Interpolation 0.465414590854128 Midmean - Closest Observation 0.404034267188194 Midmean - True Basic - Statistics Graphics Toolkit 0.465414590854128 Midmean - MS Excel (old versions) 0.465414590854128 Number of observations 93

Charts produced by software:

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2007/Dec/18/t11980149979k6pds9rdjno0t9/1s5j91198015861.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2007/Dec/18/t11980149979k6pds9rdjno0t9/1s5j91198015861.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2007/Dec/18/t11980149979k6pds9rdjno0t9/2rtq21198015861.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2007/Dec/18/t11980149979k6pds9rdjno0t9/2rtq21198015861.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