Central Tendency: werkelijk begonnen woongebouwen

*Unverified author*

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

Title produced by software: Central Tendency

Date of computation: Mon, 20 Oct 2008 16:39:27 -0600

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2008/Oct/21/t1224542410m6bstfygjq4q5wz.htm/, Retrieved Mon, 20 Oct 2008 22:40:10 +0000

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/2008/Oct/21/t1224542410m6bstfygjq4q5wz.htm/}, year = {2008}, } @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 = {2008}, note = {{ISBN} 3-900051-07-0}, url = {http://www.R-project.org}, }

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)

Feedback Forum:

Post a new message

Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords:

Dataseries X:

» Textbox « » Textfile « » CSV «

2752 2373 1415 2466 2318 2346 1644 1421 1423 1930 2694 4938 1727 1899 1364 1992 2051 2082 1746 1271 1363 1664 2179 2305 2098 2231 1407 1966 2293 2045 1532 1333 1583 1712 2641 2267 2126 2231 1517 2010 2628 2115 1829 1636 1787 2122 2620 2555 2337 2524 1801 2417 2389 2267 2135 1760 1905 2176 2344 2673 2766 2785 2003 2588 2739 2703 2464 1974 2164 2385 2936 2700 2855 2764 1808 2588 2600 2526 2259 1738 1902 2137 2460 2495 2525 2465 1828 2273 2377 2344 2071 1611 1671 2256 1983 1921 2027

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 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 2165.62886597938 50.7808471915563 42.6465682585043 Geometric Mean 2113.27173113653 Harmonic Mean 2062.66475972915 Quadratic Mean 2222.04929098038 Winsorized Mean ( 1 / 32 ) 2145.62886597938 42.4425306804902 50.5537448304343 Winsorized Mean ( 2 / 32 ) 2144.57731958763 42.0117518410221 51.0470814857469 Winsorized Mean ( 3 / 32 ) 2142.44329896907 41.6410006063946 51.4503318308847 Winsorized Mean ( 4 / 32 ) 2143.43298969072 41.1784730986827 52.0522697515778 Winsorized Mean ( 5 / 32 ) 2143.74226804124 41.0857431480037 52.1772786321232 Winsorized Mean ( 6 / 32 ) 2143.37113402062 40.9014255867898 52.403335660576 Winsorized Mean ( 7 / 32 ) 2142.57731958763 40.7306097138959 52.6036151837092 Winsorized Mean ( 8 / 32 ) 2147.36082474227 38.9144724400192 55.1815478946067 Winsorized Mean ( 9 / 32 ) 2148.47422680412 38.6400059896871 55.602326443157 Winsorized Mean ( 10 / 32 ) 2153.11340206186 37.6964752090848 57.117101535874 Winsorized Mean ( 11 / 32 ) 2153.90721649485 36.8499094337242 58.4508143871757 Winsorized Mean ( 12 / 32 ) 2153.0412371134 35.8083803398224 60.1267417481883 Winsorized Mean ( 13 / 32 ) 2152.37113402062 35.4019789220219 60.798045746582 Winsorized Mean ( 14 / 32 ) 2154.10309278350 34.8131163210729 61.8761926659117 Winsorized Mean ( 15 / 32 ) 2152.09278350515 34.2280954438534 62.8750374684263 Winsorized Mean ( 16 / 32 ) 2156.87628865979 32.9879776657357 65.3837076802717 Winsorized Mean ( 17 / 32 ) 2159.50515463918 32.6217785986822 66.198265312438 Winsorized Mean ( 18 / 32 ) 2155.42268041237 31.5164545301924 68.3903920203811 Winsorized Mean ( 19 / 32 ) 2151.30927835052 30.5621211240289 70.3913602599751 Winsorized Mean ( 20 / 32 ) 2153.98969072165 30.1398034553865 71.4666137060257 Winsorized Mean ( 21 / 32 ) 2159.61855670103 29.3269702880395 73.6393338790197 Winsorized Mean ( 22 / 32 ) 2156.21649484536 28.0681516986338 76.8207510774682 Winsorized Mean ( 23 / 32 ) 2151 26.9985203871024 79.6710326773154 Winsorized Mean ( 24 / 32 ) 2155.70103092783 26.3199328844546 81.9037434628514 Winsorized Mean ( 25 / 32 ) 2155.70103092783 26.2549789295018 82.1063706322592 Winsorized Mean ( 26 / 32 ) 2173.39175257732 23.7738962650499 91.4192494299905 Winsorized Mean ( 27 / 32 ) 2162.25773195876 22.2047992472656 97.3779455459404 Winsorized Mean ( 28 / 32 ) 2155.0412371134 21.1495854593969 101.895199849220 Winsorized Mean ( 29 / 32 ) 2158.62886597938 20.4272098430816 105.674190580192 Winsorized Mean ( 30 / 32 ) 2158.93814432990 19.8062718642789 109.002752215252 Winsorized Mean ( 31 / 32 ) 2169.16494845361 18.2998582258205 118.534522054001 Winsorized Mean ( 32 / 32 ) 2162.89690721650 16.9766015731725 127.404586712716 Trimmed Mean ( 1 / 32 ) 2145.86315789474 41.6475980240218 51.5242957506704 Trimmed Mean ( 2 / 32 ) 2146.10752688172 40.7449003637118 52.6718069678502 Trimmed Mean ( 3 / 32 ) 2146.92307692308 39.9761382757949 53.7051143387457 Trimmed Mean ( 4 / 32 ) 2148.55056179775 39.2538034540187 54.73483771616 Trimmed Mean ( 5 / 32 ) 2149.97701149425 38.5806486036081 55.7268239210781 Trimmed Mean ( 6 / 32 ) 2151.4 37.8322228640445 56.8668673720643 Trimmed Mean ( 7 / 32 ) 2151.4 37.0148823060589 58.1225676259368 Trimmed Mean ( 8 / 32 ) 2154.74074074074 36.1076270873901 59.6755011212919 Trimmed Mean ( 9 / 32 ) 2155.87341772152 35.4435124232166 60.8256143459798 Trimmed Mean ( 10 / 32 ) 2156.90909090909 34.7227874626901 62.1179706043678 Trimmed Mean ( 11 / 32 ) 2157.4 34.0580744087571 63.3447438662383 Trimmed Mean ( 12 / 32 ) 2157.82191780822 33.4283084314961 64.5507361591508 Trimmed Mean ( 13 / 32 ) 2158.3661971831 32.8631896072432 65.6773193040089 Trimmed Mean ( 14 / 32 ) 2158.3661971831 32.2579813788786 66.9095245555669 Trimmed Mean ( 15 / 32 ) 2159.5223880597 31.632875099629 68.2682930735256 Trimmed Mean ( 16 / 32 ) 2160.26153846154 30.9781039057853 69.735111775453 Trimmed Mean ( 17 / 32 ) 2160.5873015873 30.3934317536498 71.0873098865464 Trimmed Mean ( 18 / 32 ) 2160.68852459016 29.7417347749377 72.6483690659128 Trimmed Mean ( 19 / 32 ) 2161.16949152542 29.1280266414857 74.1955340169652 Trimmed Mean ( 20 / 32 ) 2162.05263157895 28.5283179572784 75.7861937327204 Trimmed Mean ( 21 / 32 ) 2162.76363636364 27.8551564314844 77.643205547361 Trimmed Mean ( 22 / 32 ) 2163.03773584906 27.1583402348819 79.6454318320554 Trimmed Mean ( 23 / 32 ) 2163.62745098039 26.5054187694622 81.629627126404 Trimmed Mean ( 24 / 32 ) 2164.71428571429 25.8652315682971 83.6920512386816 Trimmed Mean ( 25 / 32 ) 2164.71428571429 25.1722626143396 85.996015490524 Trimmed Mean ( 26 / 32 ) 2166.33333333333 24.283365050623 89.2105904110582 Trimmed Mean ( 27 / 32 ) 2165.72093023256 23.6466074487064 91.5869616785571 Trimmed Mean ( 28 / 32 ) 2165.72093023256 23.1268107479566 93.6454642983538 Trimmed Mean ( 29 / 32 ) 2167 22.6345728176981 95.7384978039265 Trimmed Mean ( 30 / 32 ) 2167.75675675676 22.1108796547585 98.0402765789658 Trimmed Mean ( 31 / 32 ) 2167.75675675676 21.5154541180604 100.753474449657 Trimmed Mean ( 32 / 32 ) 2168.51515151515 21.052834024841 103.003479196979 Median 2164 Midrange 3104.5 Midmean - Weighted Average at Xnp 2158.45833333333 Midmean - Weighted Average at X(n+1)p 2164.71428571429 Midmean - Empirical Distribution Function 2164.71428571429 Midmean - Empirical Distribution Function - Averaging 2164.71428571429 Midmean - Empirical Distribution Function - Interpolation 2164.71428571429 Midmean - Closest Observation 2157.58 Midmean - True Basic - Statistics Graphics Toolkit 2164.71428571429 Midmean - MS Excel (old versions) 2164.71428571429 Number of observations 97

Charts produced by software:

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Oct/21/t1224542410m6bstfygjq4q5wz/1ppia1224542361.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Oct/21/t1224542410m6bstfygjq4q5wz/1ppia1224542361.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Oct/21/t1224542410m6bstfygjq4q5wz/29tpc1224542361.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Oct/21/t1224542410m6bstfygjq4q5wz/29tpc1224542361.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