Central Tendency: Diesel

*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: Fri, 12 Dec 2008 04:41:04 -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/12/t1229082135jtqingx3zitfw32.htm/, Retrieved Fri, 12 Dec 2008 12:42:19 +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/12/t1229082135jtqingx3zitfw32.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:

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0,73 0,74 0,75 0,74 0,76 0,76 0,78 0,79 0,89 0,88 0,88 0,84 0,76 0,77 0,76 0,77 0,78 0,79 0,78 0,76 0,78 0,76 0,74 0,73 0,72 0,71 0,73 0,75 0,75 0,72 0,72 0,72 0,74 0,78 0,74 0,74 0,75 0,78 0,81 0,75 0,7 0,71 0,71 0,73 0,74 0,74 0,75 0,74 0,74 0,73 0,76 0,8 0,83 0,81 0,83 0,88 0,89 0,93 0,91 0,9 0,86 0,88 0,93 0,98 0,97 1,03 1,06 1,06 1,08 1,09 1,04 1 1,01 1,02 1,04 1,06 1,06 1,06 1,06 1,06 1,02 0,98 0,99 0,99 0,94 0,96 0,98 1,01 1,01 1,02 1,04 1,03 1,05 1,08 1,17 1,11 1,11 1,11 1,2 1,21 1,31 1,37 1,37 1,26

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 'George Udny Yule' @ 72.249.76.132 Central Tendency - Ungrouped Data Measure Value S.E. Value/S.E. Arithmetic Mean 0.89548076923077 0.016163997908118 55.3997083098504 Geometric Mean 0.88144733319954 Harmonic Mean 0.868442645649414 Quadratic Mean 0.91038294985386 Winsorized Mean ( 1 / 34 ) 0.895576923076923 0.0161529903930659 55.4434133422982 Winsorized Mean ( 2 / 34 ) 0.894423076923077 0.0158413689963355 56.461223593111 Winsorized Mean ( 3 / 34 ) 0.892980769230769 0.0154916199176079 57.642827153008 Winsorized Mean ( 4 / 34 ) 0.891442307692308 0.0150288608765362 59.3153609588649 Winsorized Mean ( 5 / 34 ) 0.890961538461538 0.0149310834253526 59.6715933519403 Winsorized Mean ( 6 / 34 ) 0.88923076923077 0.0145954228682230 60.9253172901756 Winsorized Mean ( 7 / 34 ) 0.885192307692308 0.0138997670643860 63.683967047214 Winsorized Mean ( 8 / 34 ) 0.885961538461538 0.0138132206257155 64.1386655920187 Winsorized Mean ( 9 / 34 ) 0.885961538461538 0.0138132206257155 64.1386655920187 Winsorized Mean ( 10 / 34 ) 0.884038461538462 0.0135194927666347 65.3899134233953 Winsorized Mean ( 11 / 34 ) 0.88298076923077 0.0133655726637713 66.063818696237 Winsorized Mean ( 12 / 34 ) 0.88298076923077 0.0133655726637713 66.063818696237 Winsorized Mean ( 13 / 34 ) 0.881730769230769 0.0128822743740682 68.4452716676863 Winsorized Mean ( 14 / 34 ) 0.881730769230769 0.0128822743740682 68.4452716676863 Winsorized Mean ( 15 / 34 ) 0.881730769230769 0.0128822743740682 68.4452716676863 Winsorized Mean ( 16 / 34 ) 0.881730769230769 0.0128822743740682 68.4452716676863 Winsorized Mean ( 17 / 34 ) 0.881730769230769 0.0128822743740682 68.4452716676863 Winsorized Mean ( 18 / 34 ) 0.881730769230769 0.0128822743740682 68.4452716676863 Winsorized Mean ( 19 / 34 ) 0.881730769230769 0.0128822743740682 68.4452716676863 Winsorized Mean ( 20 / 34 ) 0.879807692307692 0.0126272320686990 69.6754195631362 Winsorized Mean ( 21 / 34 ) 0.877788461538462 0.0123665065456785 70.9811180947626 Winsorized Mean ( 22 / 34 ) 0.877788461538461 0.0123665065456785 70.9811180947626 Winsorized Mean ( 23 / 34 ) 0.88 0.0121318066210054 72.5365996583181 Winsorized Mean ( 24 / 34 ) 0.877692307692308 0.0118399132956694 74.1299607331867 Winsorized Mean ( 25 / 34 ) 0.877692307692308 0.0118399132956694 74.1299607331867 Winsorized Mean ( 26 / 34 ) 0.875192307692308 0.0115313489404939 75.8967846874314 Winsorized Mean ( 27 / 34 ) 0.875192307692308 0.0115313489404939 75.8967846874314 Winsorized Mean ( 28 / 34 ) 0.875192307692308 0.0115313489404939 75.8967846874314 Winsorized Mean ( 29 / 34 ) 0.875192307692308 0.0109038680514998 80.2643890735571 Winsorized Mean ( 30 / 34 ) 0.875192307692308 0.0109038680514998 80.2643890735571 Winsorized Mean ( 31 / 34 ) 0.875192307692308 0.0109038680514998 80.2643890735571 Winsorized Mean ( 32 / 34 ) 0.872115384615385 0.0105378802792116 82.7600391642172 Winsorized Mean ( 33 / 34 ) 0.868942307692308 0.0101674904296057 85.4628104848884 Winsorized Mean ( 34 / 34 ) 0.868942307692308 0.0101674904296057 85.4628104848884 Trimmed Mean ( 1 / 34 ) 0.892745098039216 0.015685437271386 56.9155378070203 Trimmed Mean ( 2 / 34 ) 0.8898 0.0151510775694388 58.7284961034596 Trimmed Mean ( 3 / 34 ) 0.88734693877551 0.0147320202979028 60.232535716899 Trimmed Mean ( 4 / 34 ) 0.8853125 0.0144048246098130 61.4594432060561 Trimmed Mean ( 5 / 34 ) 0.883617021276596 0.0141864331643334 62.2860595782544 Trimmed Mean ( 6 / 34 ) 0.88195652173913 0.0139629904054078 63.1638707849828 Trimmed Mean ( 7 / 34 ) 0.880555555555556 0.0137884508215283 63.8618193554214 Trimmed Mean ( 8 / 34 ) 0.879772727272727 0.0137354247559710 64.0513666597954 Trimmed Mean ( 9 / 34 ) 0.878837209302326 0.0136843631539395 64.222002837547 Trimmed Mean ( 10 / 34 ) 0.877857142857143 0.0136193555405733 64.4565846189949 Trimmed Mean ( 11 / 34 ) 0.877073170731707 0.0135877796878914 64.5486746825386 Trimmed Mean ( 12 / 34 ) 0.876375 0.013567976713151 64.5914286653041 Trimmed Mean ( 13 / 34 ) 0.875641025641026 0.0135364848353611 64.6874750935049 Trimmed Mean ( 14 / 34 ) 0.875 0.0135601324839566 64.527393153071 Trimmed Mean ( 15 / 34 ) 0.875 0.0135759018934544 64.4524398354616 Trimmed Mean ( 16 / 34 ) 0.873611111111111 0.0135823368043041 64.3196471784054 Trimmed Mean ( 17 / 34 ) 0.872857142857143 0.0135776927898888 64.2861166741931 Trimmed Mean ( 18 / 34 ) 0.872058823529412 0.0135598676178099 64.3117505353833 Trimmed Mean ( 19 / 34 ) 0.871212121212121 0.0135263106324199 64.4087027784204 Trimmed Mean ( 20 / 34 ) 0.8703125 0.0134739032558651 64.5924557623017 Trimmed Mean ( 21 / 34 ) 0.869516129032258 0.0134353681710962 64.7184444787204 Trimmed Mean ( 22 / 34 ) 0.868833333333333 0.0134123892188319 64.7784163699508 Trimmed Mean ( 23 / 34 ) 0.868103448275862 0.0133691070978873 64.9335398332658 Trimmed Mean ( 24 / 34 ) 0.867142857142857 0.0133307434095619 65.048349555725 Trimmed Mean ( 25 / 34 ) 0.866296296296296 0.0133105053435806 65.0836518926078 Trimmed Mean ( 26 / 34 ) 0.865384615384615 0.0132656508166147 65.2349912829571 Trimmed Mean ( 27 / 34 ) 0.8646 0.0132394278191919 65.3049370265591 Trimmed Mean ( 28 / 34 ) 0.86375 0.0131838641167772 65.5156934529407 Trimmed Mean ( 29 / 34 ) 0.862826086956522 0.0130907757599731 65.9109973906003 Trimmed Mean ( 30 / 34 ) 0.862826086956522 0.0130549040920780 66.0921046122511 Trimmed Mean ( 31 / 34 ) 0.860714285714286 0.0129790005375111 66.3159141743391 Trimmed Mean ( 32 / 34 ) 0.8595 0.0128499725630756 66.8873023487829 Trimmed Mean ( 33 / 34 ) 0.858421052631579 0.0127316448961779 67.4242063481745 Trimmed Mean ( 34 / 34 ) 0.8575 0.0126263455985730 67.9135537123991 Median 0.85 Midrange 1.035 Midmean - Weighted Average at Xnp 0.859090909090909 Midmean - Weighted Average at X(n+1)p 0.859090909090909 Midmean - Empirical Distribution Function 0.859090909090909 Midmean - Empirical Distribution Function - Averaging 0.859090909090909 Midmean - Empirical Distribution Function - Interpolation 0.859090909090909 Midmean - Closest Observation 0.859090909090909 Midmean - True Basic - Statistics Graphics Toolkit 0.859090909090909 Midmean - MS Excel (old versions) 0.865087719298245 Number of observations 104

Charts produced by software:

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/12/t1229082135jtqingx3zitfw32/109yj1229082062.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/12/t1229082135jtqingx3zitfw32/109yj1229082062.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/12/t1229082135jtqingx3zitfw32/222z61229082062.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/12/t1229082135jtqingx3zitfw32/222z61229082062.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

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Software written by Ed van Stee & Patrick Wessa

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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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