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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 13:09:11 -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/t1197834767ikr6hh0ngqrsikc.htm/, Retrieved Sun, 16 Dec 2007 20:52:50 +0100

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0.102699932769213 0.436932488054518 2.07818217715273 -2.41674270534766 4.05475642121066 -8.41930819188496 -4.46408821931718 -0.497214712516617 4.43917439850286 4.7034626725198 0.594864366867658 0.611494767896805 1.09360599733639 -4.37382959146232 1.83754098351412 -3.06393847738758 0.905218718869551 -2.46114236076518 5.63279287212732 -1.66214129260618 0.247564759120579 -3.41283905023266 0.969424788755817 1.03882497000754 0.816918947075734 -0.83166265607997 -0.178479942397197 -1.60265251085676 3.12985086246874 2.37353836989163 7.69658751276572 5.95185918989862 7.29098470532286 -5.79154345962503 -5.0780157845163 -5.25171136388928 -1.96928620348858 1.60185107642628 -2.54871994983663 0.340673892574567 3.53850575846085 -5.94725691713775 -3.16530996523464 8.1429750584661 -0.750744339756636 -0.954828226692257 5.21659241693973 1.89571043835886 5.56930909920179 -1.25079494259955 6.7254869856398 0.0435781801445501 -4.08871481641208 -5.01460899576298 -9.46383140546756 0.87163037558112 3.77891243785822 -3.28120816303436 1.12756908217732 -1.14657060797886 -0.75499264648937 0.666040477269945 5.46251057914886 -6.98015410477424 4.79597059971475 -2.39231272386021 5.2755871166014 -5.68067940168861 3.72169062406606 -2.36541998047136 -1.35449161653810 6.52892106237346 1.93774442031135 7.71226634333905 -1.28258376835628 4.23051944205953 4.63764350603921 -7.29008148943365 4.37579358256312 -13.5459822963796 12.1562686576056 13.0476986449097 7.78485323846206 0.607420821421272 -3.28744792674001 4.26375546351946 -1.68951118531521 -11.3487058537159 6.68155532637687 9.97957381014564 -7.62124318004157 8.22961700873518 21.0563835168561

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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 1 seconds R Server 'Gwilym Jenkins' @ 72.249.127.135 Central Tendency - Ungrouped Data Measure Value S.E. Value/S.E. Arithmetic Mean 0.788495676552535 0.561495878581719 1.40427687295621 Geometric Mean NaN Harmonic Mean 2.3176438308393 Quadratic Mean 5.44309347936021 Winsorized Mean ( 1 / 31 ) 0.726007413872076 0.527248116168653 1.37697488451499 Winsorized Mean ( 2 / 31 ) 0.74737181088163 0.513056132034637 1.45670573689035 Winsorized Mean ( 3 / 31 ) 0.710850145272683 0.490266720743805 1.44992534715434 Winsorized Mean ( 4 / 31 ) 0.669908562925712 0.469141632228401 1.42794524490115 Winsorized Mean ( 5 / 31 ) 0.683054785524574 0.46495788036079 1.46906809062909 Winsorized Mean ( 6 / 31 ) 0.679945467115244 0.45730769199855 1.48684458847327 Winsorized Mean ( 7 / 31 ) 0.75222688698185 0.442900034989169 1.69841234489911 Winsorized Mean ( 8 / 31 ) 0.76427287639599 0.440484822742034 1.73507198644976 Winsorized Mean ( 9 / 31 ) 0.735749771605045 0.432156935682122 1.70250598996804 Winsorized Mean ( 10 / 31 ) 0.721069160649805 0.415026456157139 1.73740529056006 Winsorized Mean ( 11 / 31 ) 0.736417581307983 0.411022898392666 1.79167044996227 Winsorized Mean ( 12 / 31 ) 0.724904358695068 0.406690490569484 1.78244727994498 Winsorized Mean ( 13 / 31 ) 0.72119431301359 0.382862759398782 1.88368885536451 Winsorized Mean ( 14 / 31 ) 0.686750144639072 0.373841716742484 1.83700778667280 Winsorized Mean ( 15 / 31 ) 0.722497080465638 0.365695629713832 1.97567873871234 Winsorized Mean ( 16 / 31 ) 0.820402843240088 0.346996864248909 2.36429468899060 Winsorized Mean ( 17 / 31 ) 0.80915499631609 0.339040715840555 2.38660125026583 Winsorized Mean ( 18 / 31 ) 0.798944363550409 0.337251606779009 2.36898608484298 Winsorized Mean ( 19 / 31 ) 0.736689000442022 0.322127791942214 2.28694641961901 Winsorized Mean ( 20 / 31 ) 0.738595142517745 0.31655251974536 2.33324676458707 Winsorized Mean ( 21 / 31 ) 0.840072417598149 0.299762603723001 2.80245903646616 Winsorized Mean ( 22 / 31 ) 0.813840015380646 0.290807395215295 2.79855336821174 Winsorized Mean ( 23 / 31 ) 0.80914574987515 0.287345919290032 2.8159291486525 Winsorized Mean ( 24 / 31 ) 0.786537198247741 0.282692562779788 2.78230594577205 Winsorized Mean ( 25 / 31 ) 0.784832015970569 0.280616192509805 2.79681656625409 Winsorized Mean ( 26 / 31 ) 0.846441044567146 0.260786888044991 3.24571933394565 Winsorized Mean ( 27 / 31 ) 0.847582312740965 0.240706230844551 3.52123129412606 Winsorized Mean ( 28 / 31 ) 0.838594637576151 0.237485650923756 3.53113813114284 Winsorized Mean ( 29 / 31 ) 0.80002274045983 0.227860360493126 3.51102200807746 Winsorized Mean ( 30 / 31 ) 0.748250481855491 0.201652243672233 3.71059834608983 Winsorized Mean ( 31 / 31 ) 0.520115600390394 0.167454605025951 3.10600953798667 Trimmed Mean ( 1 / 31 ) 0.723293370317685 0.504057277533036 1.43494281812106 Trimmed Mean ( 2 / 31 ) 0.720457347277702 0.477164852812603 1.50987094508540 Trimmed Mean ( 3 / 31 ) 0.706072030523879 0.454965117137456 1.55192563985198 Trimmed Mean ( 4 / 31 ) 0.704329423968433 0.439545999761438 1.60240207930616 Trimmed Mean ( 5 / 31 ) 0.713971412152086 0.429157007843109 1.66366015025694 Trimmed Mean ( 6 / 31 ) 0.72107078567396 0.418374468262429 1.72350571168617 Trimmed Mean ( 7 / 31 ) 0.72913967728991 0.407856549329568 1.78773561069073 Trimmed Mean ( 8 / 31 ) 0.725156169866255 0.399009891726599 1.81738895426465 Trimmed Mean ( 9 / 31 ) 0.719093080354146 0.389182432452197 1.84770179841679 Trimmed Mean ( 10 / 31 ) 0.716735283875708 0.3793750886409 1.88925236615665 Trimmed Mean ( 11 / 31 ) 0.716167607058819 0.371181357112445 1.92942774020265 Trimmed Mean ( 12 / 31 ) 0.713686384917617 0.362214080065321 1.97034412574164 Trimmed Mean ( 13 / 31 ) 0.713686384917617 0.35233775695859 2.02557452564329 Trimmed Mean ( 14 / 31 ) 0.711419654186518 0.344847874155025 2.06299562069129 Trimmed Mean ( 15 / 31 ) 0.714020860975534 0.337389808197380 2.1163083283115 Trimmed Mean ( 16 / 31 ) 0.713159343584737 0.329756987270378 2.16268152340922 Trimmed Mean ( 17 / 31 ) 0.70259404118225 0.323626626062473 2.17100196522959 Trimmed Mean ( 18 / 31 ) 0.692366828770024 0.317395487425381 2.18140098457700 Trimmed Mean ( 19 / 31 ) 0.6823549997452 0.309935541158975 2.20160294361078 Trimmed Mean ( 20 / 31 ) 0.67733706323596 0.303326157355083 2.23303215634993 Trimmed Mean ( 21 / 31 ) 0.671751767772032 0.295961181381104 2.26972930921988 Trimmed Mean ( 22 / 31 ) 0.656539114289206 0.289595019885136 2.26709393880327 Trimmed Mean ( 23 / 31 ) 0.642391160902838 0.283049873243450 2.26953346963813 Trimmed Mean ( 24 / 31 ) 0.627407415227065 0.275155379560737 2.28019316296367 Trimmed Mean ( 25 / 31 ) 0.613067231292062 0.265761382181753 2.30683339414900 Trimmed Mean ( 26 / 31 ) 0.613067231292062 0.253738957724906 2.41613363903200 Trimmed Mean ( 27 / 31 ) 0.574649263237139 0.242328301918379 2.37136669009752 Trimmed Mean ( 28 / 31 ) 0.549241081451498 0.231864559055369 2.36880135407128 Trimmed Mean ( 29 / 31 ) 0.52178201949273 0.218145054897922 2.3919039546273 Trimmed Mean ( 30 / 31 ) 0.494742952564892 0.201769807857826 2.45201677008835 Trimmed Mean ( 31 / 31 ) 0.469392199635833 0.187248009289306 2.50679407176288 Median 0.607420821421272 Midrange 3.75520061023825 Midmean - Weighted Average at Xnp 0.561230238692832 Midmean - Weighted Average at X(n+1)p 0.642391160902838 Midmean - Empirical Distribution Function 0.642391160902838 Midmean - Empirical Distribution Function - Averaging 0.642391160902838 Midmean - Empirical Distribution Function - Interpolation 0.642391160902838 Midmean - Closest Observation 0.577734212534754 Midmean - True Basic - Statistics Graphics Toolkit 0.642391160902838 Midmean - MS Excel (old versions) 0.642391160902838 Number of observations 93

Charts produced by software:

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2007/Dec/16/t1197834767ikr6hh0ngqrsikc/1r0x31197835748.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2007/Dec/16/t1197834767ikr6hh0ngqrsikc/1r0x31197835748.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2007/Dec/16/t1197834767ikr6hh0ngqrsikc/2dtaf1197835748.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2007/Dec/16/t1197834767ikr6hh0ngqrsikc/2dtaf1197835748.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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