Central tendency - invoer

*The author of this computation has been verified*

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

Title produced by software: Central Tendency

Date of computation: Sun, 21 Dec 2008 08:41:24 -0700

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2008/Dec/21/t12298741477bx29y1yxmo374v.htm/, Retrieved Sun, 21 Dec 2008 16:42:29 +0100

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/Dec/21/t12298741477bx29y1yxmo374v.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}, }

Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords:

Dataseries X:

» Textbox « » Textfile « » CSV «

14532,2 15167 16071,1 14827,5 15082 14772,7 16083 14272,5 15223,3 14897,3 13062,6 12603,8 13629,8 14421,1 13978,3 12927,9 13429,9 13470,1 14785,8 14292 14308,8 14013 13240,9 12153,4 14289,7 15669,2 14169,5 14569,8 14469,1 14264,9 15320,9 14433,5 13691,5 14194,1 13519,2 11857,9 14616 15643,4 14077,2 14887,5 14159,9 14643 17192,5 15386,1 14287,1 17526,6 14497 14398,3 16629,6 16670,7 16614,8 16869,2 15663,9 16359,9 18447,7 16889 16505 18320,9 15052,1 15699,8 18135,3 16768,7 18883 19021 18101,9 17776,1 21489,9 17065,3 18690 18953,1 16398,9 16895,7 18553 19270 19422,1 17579,4 18637,3 18076,7 20438,6 18075,2 19563 19899,2 19227,5 17789,6 19220,8 22058,6 21230,8 19504,4 23913,1 23165,7 23574,3 25002 22603,9 23408,6

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 1 seconds R Server 'George Udny Yule' @ 72.249.76.132 Central Tendency - Ungrouped Data Measure Value S.E. Value/S.E. Arithmetic Mean 16607.7148936170 298.238529583932 55.6860138654325 Geometric Mean 16375.8836397957 Harmonic Mean 16160.3349871955 Quadratic Mean 16854.9159741842 Winsorized Mean ( 1 / 31 ) 16599.2744680851 294.412616633651 56.3809888919952 Winsorized Mean ( 2 / 31 ) 16601.6489361702 291.034992560797 57.0434805453923 Winsorized Mean ( 3 / 31 ) 16606.7042553191 288.208758980276 57.6204009693392 Winsorized Mean ( 4 / 31 ) 16602.1 284.840194951140 58.2856643629522 Winsorized Mean ( 5 / 31 ) 16581.7010638298 276.384138930462 59.9951253642733 Winsorized Mean ( 6 / 31 ) 16558.9585106383 266.902120602623 62.0413148957033 Winsorized Mean ( 7 / 31 ) 16519.6021276596 257.429786399316 64.1712925249253 Winsorized Mean ( 8 / 31 ) 16501.7297872340 252.387124784277 65.3826133220487 Winsorized Mean ( 9 / 31 ) 16436.4702127660 236.47216949924 69.5069963098502 Winsorized Mean ( 10 / 31 ) 16385.6510638298 225.595903820325 72.6327508006531 Winsorized Mean ( 11 / 31 ) 16379.8702127660 214.992149914574 76.1882246364548 Winsorized Mean ( 12 / 31 ) 16376.8191489362 213.276838961097 76.7866742057416 Winsorized Mean ( 13 / 31 ) 16374.3159574468 210.442986486141 77.8087986245394 Winsorized Mean ( 14 / 31 ) 16363.9797872340 205.523389311993 79.6210097644547 Winsorized Mean ( 15 / 31 ) 16358.7297872340 204.319299900101 80.0645352408335 Winsorized Mean ( 16 / 31 ) 16361.7765957447 203.666327582976 80.3361890496048 Winsorized Mean ( 17 / 31 ) 16338.4468085106 196.832230737753 83.0069686619514 Winsorized Mean ( 18 / 31 ) 16326.9 194.77198274968 83.8257113241141 Winsorized Mean ( 19 / 31 ) 16315.6819148936 192.393603555321 84.8036608982284 Winsorized Mean ( 20 / 31 ) 16275.1712765957 186.524990671754 87.2546419543144 Winsorized Mean ( 21 / 31 ) 16263.9117021277 184.833815902095 87.9920788452611 Winsorized Mean ( 22 / 31 ) 16248.1138297872 181.674682898627 89.4352122736525 Winsorized Mean ( 23 / 31 ) 16244.2478723404 175.685421049566 92.4621279062047 Winsorized Mean ( 24 / 31 ) 16217.6946808511 170.699042049699 95.0075318883703 Winsorized Mean ( 25 / 31 ) 16171.6308510638 163.872630690772 98.6841474558358 Winsorized Mean ( 26 / 31 ) 16172.2393617021 161.564626911326 100.097649286674 Winsorized Mean ( 27 / 31 ) 16173.0148936170 159.729748269294 101.252365754376 Winsorized Mean ( 28 / 31 ) 16183.0531914894 158.493767899019 102.105296668826 Winsorized Mean ( 29 / 31 ) 16106.5425531915 146.066558897672 110.268515084791 Winsorized Mean ( 30 / 31 ) 16116.9787234043 143.871427147532 112.023485433818 Winsorized Mean ( 31 / 31 ) 16061.0138297872 134.919019252744 119.041880964908 Trimmed Mean ( 1 / 31 ) 16568.1010869565 285.917005002133 57.9472392236094 Trimmed Mean ( 2 / 31 ) 16535.5422222222 276.157132589572 59.8772954627884 Trimmed Mean ( 3 / 31 ) 16535.5422222222 266.991128526216 61.9329275601701 Trimmed Mean ( 4 / 31 ) 16461.4441860465 257.616090057759 63.8991306108083 Trimmed Mean ( 5 / 31 ) 16422.0940476190 247.913429054690 66.2412444143812 Trimmed Mean ( 6 / 31 ) 16422.0940476190 239.209165448084 68.6516087995933 Trimmed Mean ( 7 / 31 ) 16351.5325 231.618585388542 70.596806696536 Trimmed Mean ( 8 / 31 ) 16322.5974358974 225.083449326586 72.5179815963016 Trimmed Mean ( 9 / 31 ) 16294.9026315789 218.556487764073 74.5569385666966 Trimmed Mean ( 10 / 31 ) 16274.9216216216 214.250285645519 75.9621933412438 Trimmed Mean ( 11 / 31 ) 16260.4652777778 211.256254735674 76.9703377451381 Trimmed Mean ( 12 / 31 ) 16260.4652777778 209.512205443958 77.6110644404785 Trimmed Mean ( 13 / 31 ) 16230.8058823529 207.622231987479 78.1747008833417 Trimmed Mean ( 14 / 31 ) 16215.0833333333 205.720497708772 78.8209415878832 Trimmed Mean ( 15 / 31 ) 16199.4625 204.114940841921 79.3644131741726 Trimmed Mean ( 16 / 31 ) 16183.3645161290 202.234361706858 80.0228229245586 Trimmed Mean ( 17 / 31 ) 16165.895 199.913487552056 80.8644539092968 Trimmed Mean ( 18 / 31 ) 16149.4448275862 198.067205716833 81.5351777652392 Trimmed Mean ( 19 / 31 ) 16132.8964285714 195.980454945250 82.3189048779296 Trimmed Mean ( 20 / 31 ) 16116.15 193.637894674617 83.2282855950332 Trimmed Mean ( 21 / 31 ) 16101.7769230769 191.584977711934 84.0450911933578 Trimmed Mean ( 22 / 31 ) 16087.262 189.118724655780 85.0643532483676 Trimmed Mean ( 23 / 31 ) 16072.94375 186.387127488717 86.2341942094312 Trimmed Mean ( 24 / 31 ) 16072.94375 183.786330127901 87.4545116539105 Trimmed Mean ( 25 / 31 ) 16043.4840909091 181.183890792469 88.5480713585377 Trimmed Mean ( 26 / 31 ) 16032.0119047619 178.938269652237 89.5952103254366 Trimmed Mean ( 27 / 31 ) 16019.3375 176.146423127491 90.9433028248639 Trimmed Mean ( 28 / 31 ) 16005.2578947368 172.516336976879 92.775317255211 Trimmed Mean ( 29 / 31 ) 15988.6777777778 167.570776712746 95.4144755513427 Trimmed Mean ( 30 / 31 ) 15977.4411764706 163.843998567615 97.5161819544889 Trimmed Mean ( 31 / 31 ) 15977.4411764706 158.830335637869 100.594392829962 Median 15885.45 Midrange 18429.95 Midmean - Weighted Average at Xnp 16022.4170212766 Midmean - Weighted Average at X(n+1)p 16072.94375 Midmean - Empirical Distribution Function 16072.94375 Midmean - Empirical Distribution Function - Averaging 16072.94375 Midmean - Empirical Distribution Function - Interpolation 16057.7239130435 Midmean - Closest Observation 16072.94375 Midmean - True Basic - Statistics Graphics Toolkit 16072.94375 Midmean - MS Excel (old versions) 16072.94375 Number of observations 94

Charts produced by software:

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/21/t12298741477bx29y1yxmo374v/13k3d1229874080.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/21/t12298741477bx29y1yxmo374v/13k3d1229874080.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/21/t12298741477bx29y1yxmo374v/216qt1229874081.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/21/t12298741477bx29y1yxmo374v/216qt1229874081.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