opgave 5 oefening 2 stap 1 - Esther Blangenois

*Unverified author*

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

Title produced by software: Central Tendency

Date of computation: Tue, 04 Nov 2008 04:37:19 -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/Nov/04/t1225798896d29w2c5nxvrl1dr.htm/, Retrieved Tue, 04 Nov 2008 11:41:37 +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/Nov/04/t1225798896d29w2c5nxvrl1dr.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 «

1,27 1,23 1,27 1,22 1,29 1,36 1,44 1,62 1,57 1,22 1,14 1,14 1,17 1,16 1,14 1,15 1,16 1,21 1,22 1,22 1,17 0,95 1 1,01 1,01 1 1 1 1,06 1,22 1,24 1,34 1,3 1,05 1 1 1,01 1,02 1,06 1,09 1,09 1,15 1,25 1,37 1,51 1,35 1,32 1,3 1,39 1,4 1,39 1,42 1,44 1,44 1,45 1,39 1,48 1,32 1,29 1,31 1,27 1,38 1,38 1,45 1,5 1,63 1,73 1,84 1,75 1,34 1,36 1,33 1,37 1,39 1,4 1,4 1,43 1,52 1,54 1,85 1,83 1,29 1,2 1,2 1,21 1,21 1,19 1,18 1,17 1,22 1,25 1,3 1,33 1,18 1,18 1,19

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 1.289375 0.0199543406986875 64.6162666795002 Geometric Mean 1.27533576727848 Harmonic Mean 1.26183278422323 Quadratic Mean 1.30396111266147 Winsorized Mean ( 1 / 32 ) 1.28979166666667 0.0198370440100958 65.0193479436876 Winsorized Mean ( 2 / 32 ) 1.28958333333333 0.0197766679086051 65.2073109227979 Winsorized Mean ( 3 / 32 ) 1.28708333333333 0.0190974627842371 67.3955146751578 Winsorized Mean ( 4 / 32 ) 1.28625 0.0188880880033171 68.0984755987005 Winsorized Mean ( 5 / 32 ) 1.28104166666667 0.0177002819673910 72.3740824596306 Winsorized Mean ( 6 / 32 ) 1.28041666666667 0.0175718554040028 72.8674711479241 Winsorized Mean ( 7 / 32 ) 1.2775 0.0167423719210827 76.3034058747265 Winsorized Mean ( 8 / 32 ) 1.275 0.0162983423976882 78.2288142492852 Winsorized Mean ( 9 / 32 ) 1.273125 0.0159854048700572 79.6429624616347 Winsorized Mean ( 10 / 32 ) 1.273125 0.0156386782235248 81.408734280681 Winsorized Mean ( 11 / 32 ) 1.27541666666667 0.0148891493714667 85.6608147884425 Winsorized Mean ( 12 / 32 ) 1.27416666666667 0.0143030074946430 89.0838284985792 Winsorized Mean ( 13 / 32 ) 1.27010416666667 0.0137142636015588 92.6119114789584 Winsorized Mean ( 14 / 32 ) 1.27447916666667 0.0130349309647519 97.7741401249473 Winsorized Mean ( 15 / 32 ) 1.27291666666667 0.0128169609621038 99.3150147238745 Winsorized Mean ( 16 / 32 ) 1.28125 0.011654991024856 109.931444586061 Winsorized Mean ( 17 / 32 ) 1.28125 0.011654991024856 109.931444586061 Winsorized Mean ( 18 / 32 ) 1.279375 0.011390027667357 112.324134529242 Winsorized Mean ( 19 / 32 ) 1.279375 0.0108658208892146 117.743059916431 Winsorized Mean ( 20 / 32 ) 1.27520833333333 0.0103162484326981 123.611634757793 Winsorized Mean ( 21 / 32 ) 1.27739583333333 0.0100418475178444 127.207252556205 Winsorized Mean ( 22 / 32 ) 1.27739583333333 0.0100418475178444 127.207252556205 Winsorized Mean ( 23 / 32 ) 1.27739583333333 0.00944657738965044 135.223137507224 Winsorized Mean ( 24 / 32 ) 1.27739583333333 0.00944657738965044 135.223137507224 Winsorized Mean ( 25 / 32 ) 1.27739583333333 0.00944657738965044 135.223137507224 Winsorized Mean ( 26 / 32 ) 1.28010416666667 0.00912810244263376 140.237708188704 Winsorized Mean ( 27 / 32 ) 1.27729166666667 0.00877656264722042 145.534387209233 Winsorized Mean ( 28 / 32 ) 1.27729166666667 0.00877656264722042 145.534387209233 Winsorized Mean ( 29 / 32 ) 1.27729166666667 0.0080588286101177 158.495946304535 Winsorized Mean ( 30 / 32 ) 1.27729166666667 0.0080588286101177 158.495946304535 Winsorized Mean ( 31 / 32 ) 1.27729166666667 0.00730668878654291 174.811286477552 Winsorized Mean ( 32 / 32 ) 1.27729166666667 0.00730668878654291 174.811286477552 Trimmed Mean ( 1 / 32 ) 1.28702127659574 0.0191364890021653 67.2548280120829 Trimmed Mean ( 2 / 32 ) 1.28413043478261 0.0183284730244855 70.0620522542768 Trimmed Mean ( 3 / 32 ) 1.28122222222222 0.0174281673784632 73.5144547558963 Trimmed Mean ( 4 / 32 ) 1.27909090909091 0.0166943106925498 76.6183721297179 Trimmed Mean ( 5 / 32 ) 1.27709302325581 0.0159177659988189 80.2306695142131 Trimmed Mean ( 6 / 32 ) 1.27619047619048 0.0153874280537252 82.937218080543 Trimmed Mean ( 7 / 32 ) 1.27536585365854 0.0148069938815896 86.1326656752573 Trimmed Mean ( 8 / 32 ) 1.275 0.0143365956448365 88.9332468869071 Trimmed Mean ( 9 / 32 ) 1.275 0.0138888000885162 91.800586938696 Trimmed Mean ( 10 / 32 ) 1.27526315789474 0.0134314029576547 94.9463851181644 Trimmed Mean ( 11 / 32 ) 1.27554054054054 0.0129649970082093 98.3834041560426 Trimmed Mean ( 12 / 32 ) 1.27555555555556 0.0125626581209755 101.535482640079 Trimmed Mean ( 13 / 32 ) 1.27571428571429 0.0121967504557557 104.594604140013 Trimmed Mean ( 14 / 32 ) 1.27632352941176 0.0118668061916728 107.554089010688 Trimmed Mean ( 15 / 32 ) 1.27651515151515 0.0115943327210639 110.098199027535 Trimmed Mean ( 16 / 32 ) 1.276875 0.0113036090422905 112.961709417124 Trimmed Mean ( 17 / 32 ) 1.27645161290323 0.0111456317471712 114.524832854557 Trimmed Mean ( 18 / 32 ) 1.276 0.0109498084496828 116.53171887559 Trimmed Mean ( 19 / 32 ) 1.27568965517241 0.0107524306653275 118.641979183928 Trimmed Mean ( 20 / 32 ) 1.27535714285714 0.0105927084873667 120.399531845721 Trimmed Mean ( 21 / 32 ) 1.27537037037037 0.0104801331567274 121.694099807471 Trimmed Mean ( 22 / 32 ) 1.27519230769231 0.0103756385422552 122.902537756981 Trimmed Mean ( 23 / 32 ) 1.275 0.0102349939931988 124.572618298285 Trimmed Mean ( 24 / 32 ) 1.27479166666667 0.0101495448633821 125.600870169647 Trimmed Mean ( 25 / 32 ) 1.27456521739130 0.0100275298432567 127.106599263668 Trimmed Mean ( 26 / 32 ) 1.27431818181818 0.00985839340006884 129.262257053901 Trimmed Mean ( 27 / 32 ) 1.27380952380952 0.00968704476853221 131.496194582213 Trimmed Mean ( 28 / 32 ) 1.2735 0.00952426052045714 133.711168154698 Trimmed Mean ( 29 / 32 ) 1.27315789473684 0.00929296574824172 137.002322964306 Trimmed Mean ( 30 / 32 ) 1.27277777777778 0.00913402075194719 139.344743387675 Trimmed Mean ( 31 / 32 ) 1.27235294117647 0.0088969022982357 143.010780440827 Trimmed Mean ( 32 / 32 ) 1.271875 0.00874639902861412 145.416987704199 Median 1.27 Midrange 1.4 Midmean - Weighted Average at Xnp 1.275 Midmean - Weighted Average at X(n+1)p 1.275 Midmean - Empirical Distribution Function 1.275 Midmean - Empirical Distribution Function - Averaging 1.275 Midmean - Empirical Distribution Function - Interpolation 1.275 Midmean - Closest Observation 1.275 Midmean - True Basic - Statistics Graphics Toolkit 1.275 Midmean - MS Excel (old versions) 1.275 Number of observations 96

Charts produced by software:

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Nov/04/t1225798896d29w2c5nxvrl1dr/1t5x21225798631.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Nov/04/t1225798896d29w2c5nxvrl1dr/1t5x21225798631.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Nov/04/t1225798896d29w2c5nxvrl1dr/24rza1225798631.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Nov/04/t1225798896d29w2c5nxvrl1dr/24rza1225798631.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