Thomas Van den Bosch opgave 5 vraag 2 stap 1

*Unverified author*

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

Title produced by software: Central Tendency

Date of computation: Wed, 22 Apr 2009 14:24:18 -0600

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2009/Apr/22/t12404319042euf39vigkp8ohh.htm/, Retrieved Wed, 22 Apr 2009 22:25:04 +0200

BibTeX entries for LaTeX users:

@Manual{KEY, author = {{YOUR NAME}}, publisher = {Office for Research Development and Education}, title = {Statistical Computations at FreeStatistics.org, URL http://www.freestatistics.org/blog/date/2009/Apr/22/t12404319042euf39vigkp8ohh.htm/}, year = {2009}, } @Manual{R, title = {R: A Language and Environment for Statistical Computing}, author = {{R Development Core Team}}, organization = {R Foundation for Statistical Computing}, address = {Vienna, Austria}, year = {2009}, note = {{ISBN} 3-900051-07-0}, url = {http://www.R-project.org}, }

Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords:

Dataseries X:

» Textbox « » Textfile « » CSV «

36.80 35.40 33.00 28.73 26.70 26.46 24.60 28.00 31.60 33.50 34.50 35.00 34.76 33.50 32.74 34.40 31.93 29.24 25.75 26.03 26.08 23.80 20.61 19.70 18.18 19.60 20.60 20.03 23.00 23.60 22.56 22.55 23.75 24.92 24.50 30.58 28.07 27.70 27.00 25.23 26.86 25.60 24.55 23.96 23.50 23.64 21.55 21.05 21.89 21.98 21.45 22.15 22.58 23.80 23.30 22.38 23.00 21.96 22.40 20.80 20.40 16.00 12.78 9.75 7.50 11.24 12.24 12.75 12.52 14.49 14.21 14.32 22.15 22.58 23.80 23.30 22.38 23.00 21.96 22.40 20.80 20.40 16.00 12.78 9.75 7.50 11.24 12.24 12.75 12.52 14.49 14.21 14.32

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 2 seconds R Server 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 Central Tendency - Ungrouped Data Measure Value S.E. Value/S.E. Arithmetic Mean 22.2781720430108 0.71331789249994 31.2317583468056 Geometric Mean 21.0814932244761 Harmonic Mean 19.7049932783306 Quadratic Mean 23.3051198629820 Winsorized Mean ( 1 / 31 ) 22.2631182795699 0.710138493668112 31.350389365 Winsorized Mean ( 2 / 31 ) 22.3029032258065 0.698222306611151 31.9424100528304 Winsorized Mean ( 3 / 31 ) 22.2951612903226 0.696704367378076 32.0008921061117 Winsorized Mean ( 4 / 31 ) 22.3480645161290 0.682589349573454 32.7401306951159 Winsorized Mean ( 5 / 31 ) 22.342688172043 0.681552248549702 32.7820621523688 Winsorized Mean ( 6 / 31 ) 22.3491397849462 0.659538398368678 33.8860327772049 Winsorized Mean ( 7 / 31 ) 22.3491397849462 0.659538398368678 33.8860327772049 Winsorized Mean ( 8 / 31 ) 22.3302150537634 0.647745776078582 34.4737331811708 Winsorized Mean ( 9 / 31 ) 22.3050537634409 0.643274909543827 34.6742169366722 Winsorized Mean ( 10 / 31 ) 22.242688172043 0.624155907608765 35.6364297780311 Winsorized Mean ( 11 / 31 ) 22.2036559139785 0.617635891945879 35.9494261967602 Winsorized Mean ( 12 / 31 ) 22.0759139784946 0.595883616683703 37.0473585116413 Winsorized Mean ( 13 / 31 ) 21.8886021505376 0.568150991481168 38.5260300144405 Winsorized Mean ( 14 / 31 ) 22.0270967741935 0.521021234862175 42.2767735753041 Winsorized Mean ( 15 / 31 ) 21.9206451612903 0.506549110240878 43.2744717503628 Winsorized Mean ( 16 / 31 ) 21.9275268817204 0.50183775533215 43.694454330578 Winsorized Mean ( 17 / 31 ) 21.872688172043 0.49472011580524 44.2122474370009 Winsorized Mean ( 18 / 31 ) 21.7701075268817 0.47239785745937 46.0842638956171 Winsorized Mean ( 19 / 31 ) 21.7415053763441 0.468980271692687 46.3591043987259 Winsorized Mean ( 20 / 31 ) 22.0318279569892 0.411577710678054 53.5301776199029 Winsorized Mean ( 21 / 31 ) 21.9776344086021 0.404976534387631 54.2689083006618 Winsorized Mean ( 22 / 31 ) 22.4034408602151 0.314408380307914 71.2558642307 Winsorized Mean ( 23 / 31 ) 22.7422580645161 0.264197255889334 86.0805990885927 Winsorized Mean ( 24 / 31 ) 22.6958064516129 0.251191937558988 90.3524479016495 Winsorized Mean ( 25 / 31 ) 22.7441935483871 0.234523594896894 96.9804064208821 Winsorized Mean ( 26 / 31 ) 22.7441935483871 0.208105746990217 109.291520668366 Winsorized Mean ( 27 / 31 ) 22.6541935483871 0.196620662596304 115.217766277698 Winsorized Mean ( 28 / 31 ) 22.6180645161290 0.177243137870079 127.610381919036 Winsorized Mean ( 29 / 31 ) 22.6055913978495 0.174967669648683 129.198676779768 Winsorized Mean ( 30 / 31 ) 22.6507526881720 0.165487665061470 136.872755318400 Winsorized Mean ( 31 / 31 ) 22.4707526881720 0.144410283499287 155.603549440320 Trimmed Mean ( 1 / 31 ) 22.280989010989 0.692203751136753 32.1884834839434 Trimmed Mean ( 2 / 31 ) 22.2996629213483 0.671694312522392 33.1991242230519 Trimmed Mean ( 3 / 31 ) 22.2979310344828 0.655492700170469 34.0170546959317 Trimmed Mean ( 4 / 31 ) 22.2989411764706 0.63753312702482 34.9769137182458 Trimmed Mean ( 5 / 31 ) 22.2851807228916 0.621731591801064 35.8437322741389 Trimmed Mean ( 6 / 31 ) 22.2719753086420 0.603753879923967 36.8891630335308 Trimmed Mean ( 7 / 31 ) 22.2568354430380 0.5886730120384 37.8084861848331 Trimmed Mean ( 8 / 31 ) 22.2409090909091 0.571089339979735 38.9447106326627 Trimmed Mean ( 9 / 31 ) 22.2270666666667 0.55317601497493 40.1808214111995 Trimmed Mean ( 10 / 31 ) 22.2160273972603 0.533069774337519 41.675646353931 Trimmed Mean ( 11 / 31 ) 22.2125352112676 0.513322499667003 43.2720857271541 Trimmed Mean ( 12 / 31 ) 22.2136231884058 0.491168985519758 45.2260298253547 Trimmed Mean ( 13 / 31 ) 22.2136231884058 0.469061894353315 47.3575522885551 Trimmed Mean ( 14 / 31 ) 22.2670769230769 0.447856096129367 49.7192672278483 Trimmed Mean ( 15 / 31 ) 22.2923809523810 0.431618414130555 51.6483547099962 Trimmed Mean ( 16 / 31 ) 22.3301639344262 0.414515748269014 53.8704838782972 Trimmed Mean ( 17 / 31 ) 22.3698305084746 0.394464435919717 56.7093721803286 Trimmed Mean ( 18 / 31 ) 22.4175438596491 0.370907263394716 60.4397542783965 Trimmed Mean ( 19 / 31 ) 22.4783636363636 0.345769114264928 65.0097498851234 Trimmed Mean ( 20 / 31 ) 22.5464150943396 0.314053984610305 71.791526932277 Trimmed Mean ( 21 / 31 ) 22.5933333333333 0.288065851222464 78.4311407876153 Trimmed Mean ( 22 / 31 ) 22.6489795918367 0.2550752264819 88.7933332618012 Trimmed Mean ( 23 / 31 ) 22.6710638297872 0.236829238599366 95.7274699858278 Trimmed Mean ( 24 / 31 ) 22.6646666666667 0.225346781022432 100.57683790216 Trimmed Mean ( 25 / 31 ) 22.6618604651163 0.213391444833228 106.198542696157 Trimmed Mean ( 26 / 31 ) 22.6618604651163 0.201633889664002 112.391128807163 Trimmed Mean ( 27 / 31 ) 22.6461538461538 0.192570373902131 117.599365817627 Trimmed Mean ( 28 / 31 ) 22.6454054054054 0.183275828243682 123.559149192856 Trimmed Mean ( 29 / 31 ) 22.648 0.175704010084186 128.898594796718 Trimmed Mean ( 30 / 31 ) 22.6521212121212 0.165619679774905 136.771917702703 Trimmed Mean ( 31 / 31 ) 22.6522580645161 0.154226972577474 146.876111784773 Median 22.56 Midrange 22.15 Midmean - Weighted Average at Xnp 22.5980434782609 Midmean - Weighted Average at X(n+1)p 22.6710638297872 Midmean - Empirical Distribution Function 22.6710638297872 Midmean - Empirical Distribution Function - Averaging 22.6710638297872 Midmean - Empirical Distribution Function - Interpolation 22.6710638297872 Midmean - Closest Observation 22.5775 Midmean - True Basic - Statistics Graphics Toolkit 22.6710638297872 Midmean - MS Excel (old versions) 22.6710638297872 Number of observations 93

Charts produced by software:

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Apr/22/t12404319042euf39vigkp8ohh/1qdex1240431853.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Apr/22/t12404319042euf39vigkp8ohh/1qdex1240431853.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Apr/22/t12404319042euf39vigkp8ohh/2ct621240431853.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Apr/22/t12404319042euf39vigkp8ohh/2ct621240431853.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