Mean olieproductie KT

*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: Sat, 18 Dec 2010 14:16:22 +0000

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2010/Dec/18/t1292681688ngb34tr4ndeipbm.htm/, Retrieved Sat, 18 Dec 2010 15:14:50 +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/2010/Dec/18/t1292681688ngb34tr4ndeipbm.htm/}, year = {2010}, } @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 = {2010}, 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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78.33 78.21 78.94 77.94 77.31 75.75 77.73 77.90 77.45 77.46 77.97 77.23 76.56 76.70 76.51 76.03 76.69 76.38 76.80 76.63 77.17 78.63 78.89 76.94 77.50 79.27 79.77 78.62 78.60 77.88 78.71 79.27 80.12 81.12 81.48 82.81 82.39 82.41 82.20 81.99 81.61 83.51 84.05 82.99 83.54 84.44 84.24 83.88 84.17 84.59 84.76 85.14 85.22 84.77 84.50 84.56 83.79 83.96 84.80 84.89 84.78 84.80 84.44 84.65 84.22 84.08 85.29 85.00 84.63 84.92 84.61 84.50 84.29 84.50 84.41 84.71 84.21 83.86 84.40 83.71 84.42 85.26 85.08 85.65 85.74 85.89 86.08 85.49 85.97 85.84 86.72 85.42 83.87 85.45 85.35 84.27 83.13 83.79 83.70 83.76 83.47 83.78 84.83 84.43 84.90 85.36 85.49 85.29

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 4 seconds R Server 'Gwilym Jenkins' @ 72.249.127.135 Central Tendency - Ungrouped Data Measure Value S.E. Value/S.E. Arithmetic Mean 82.3346296296296 0.311980864773583 263.909229463106 Geometric Mean 82.2701188575152 Harmonic Mean 82.2043712907687 Quadratic Mean 82.3978504978538 Winsorized Mean ( 1 / 36 ) 82.3312962962963 0.310756095448344 264.938636770785 Winsorized Mean ( 2 / 36 ) 82.3357407407407 0.309332072334004 266.172660725067 Winsorized Mean ( 3 / 36 ) 82.3371296296296 0.308446768472398 266.941132297834 Winsorized Mean ( 4 / 36 ) 82.3371296296296 0.307922814782736 267.395352590957 Winsorized Mean ( 5 / 36 ) 82.3357407407407 0.306871015364799 268.307323332125 Winsorized Mean ( 6 / 36 ) 82.334074074074 0.305781320456977 269.258023842102 Winsorized Mean ( 7 / 36 ) 82.3243518518519 0.304640391227522 270.234526420259 Winsorized Mean ( 8 / 36 ) 82.3317592592593 0.303370155944665 271.3904372132 Winsorized Mean ( 9 / 36 ) 82.3400925925926 0.301075132884763 273.486859587664 Winsorized Mean ( 10 / 36 ) 82.3586111111111 0.297285296002573 277.035602562725 Winsorized Mean ( 11 / 36 ) 82.3586111111111 0.295707682011554 278.513600156973 Winsorized Mean ( 12 / 36 ) 82.3663888888889 0.294167941402412 279.997842376082 Winsorized Mean ( 13 / 36 ) 82.3760185185185 0.290799822662879 283.273964076712 Winsorized Mean ( 14 / 36 ) 82.3773148148148 0.290594710340906 283.478369988825 Winsorized Mean ( 15 / 36 ) 82.3787037037037 0.289328608135295 284.723671933548 Winsorized Mean ( 16 / 36 ) 82.4068518518519 0.283465537788415 290.712065017802 Winsorized Mean ( 17 / 36 ) 82.4178703703704 0.278689636789677 295.733531105679 Winsorized Mean ( 18 / 36 ) 82.4112037037037 0.277276371481491 297.216828334054 Winsorized Mean ( 19 / 36 ) 82.4041666666667 0.274953507036188 299.702184398111 Winsorized Mean ( 20 / 36 ) 82.3949074074074 0.272816562352518 302.015781948537 Winsorized Mean ( 21 / 36 ) 82.4376851851852 0.265469196316959 310.53578467446 Winsorized Mean ( 22 / 36 ) 82.4600925925926 0.261670403481806 315.129611508877 Winsorized Mean ( 23 / 36 ) 82.5048148148148 0.252162110627319 327.189578995681 Winsorized Mean ( 24 / 36 ) 82.5025925925926 0.25094671457174 328.765382457346 Winsorized Mean ( 25 / 36 ) 82.5049074074074 0.250612109604218 329.21357047632 Winsorized Mean ( 26 / 36 ) 82.5193518518519 0.247423352902633 333.514807247500 Winsorized Mean ( 27 / 36 ) 82.5618518518519 0.240764623252898 342.915212112077 Winsorized Mean ( 28 / 36 ) 82.5722222222222 0.238696896937018 345.929181660076 Winsorized Mean ( 29 / 36 ) 82.6474074074074 0.225028722845343 367.274925451224 Winsorized Mean ( 30 / 36 ) 82.6307407407407 0.223611546294619 369.528059306342 Winsorized Mean ( 31 / 36 ) 82.7685185185185 0.203136099923139 407.453517862338 Winsorized Mean ( 32 / 36 ) 82.8662962962963 0.188405875285331 439.828620900487 Winsorized Mean ( 33 / 36 ) 83.1657407407408 0.147076224383414 565.460128510884 Winsorized Mean ( 34 / 36 ) 83.2696296296296 0.131641257451104 632.549637111746 Winsorized Mean ( 35 / 36 ) 83.2923148148148 0.124532883281369 668.83792152009 Winsorized Mean ( 36 / 36 ) 83.4189814814815 0.108744124090974 767.112542206823 Trimmed Mean ( 1 / 36 ) 82.3553773584906 0.308917309816385 266.593598809472 Trimmed Mean ( 2 / 36 ) 82.3803846153846 0.30678574439273 268.527420589419 Trimmed Mean ( 3 / 36 ) 82.4040196078431 0.305142562256409 270.050887029649 Trimmed Mean ( 4 / 36 ) 82.4281 0.303563039731304 271.535362384566 Trimmed Mean ( 5 / 36 ) 82.4531632653061 0.301855005402478 273.154865049752 Trimmed Mean ( 6 / 36 ) 82.4795833333333 0.300104766672461 274.835965612478 Trimmed Mean ( 7 / 36 ) 82.5074468085106 0.298269543485871 276.620421395519 Trimmed Mean ( 8 / 36 ) 82.538152173913 0.296302421395265 278.56050512597 Trimmed Mean ( 9 / 36 ) 82.5691111111111 0.294200015380351 280.656379315151 Trimmed Mean ( 10 / 36 ) 82.6003409090909 0.292098685070379 282.782309989479 Trimmed Mean ( 11 / 36 ) 82.6306976744186 0.290220011391786 284.717436534279 Trimmed Mean ( 12 / 36 ) 82.6625 0.288178487981267 286.844797399914 Trimmed Mean ( 13 / 36 ) 82.695 0.285935510613934 289.208569521306 Trimmed Mean ( 14 / 36 ) 82.728125 0.283711895548341 291.592020983498 Trimmed Mean ( 15 / 36 ) 82.7628205128205 0.281018430989809 294.510293226361 Trimmed Mean ( 16 / 36 ) 82.7992105263158 0.277920900217076 297.923655477669 Trimmed Mean ( 17 / 36 ) 82.835 0.275030290142945 301.185007502072 Trimmed Mean ( 18 / 36 ) 82.8718055555556 0.272160854581236 304.495683933193 Trimmed Mean ( 19 / 36 ) 82.9112857142857 0.268786701200755 308.46498485191 Trimmed Mean ( 20 / 36 ) 82.9536764705882 0.264919596563156 313.127747236367 Trimmed Mean ( 21 / 36 ) 82.999393939394 0.260405625746029 318.731186016474 Trimmed Mean ( 22 / 36 ) 83.04453125 0.255993912851534 324.400413763598 Trimmed Mean ( 23 / 36 ) 83.0908064516129 0.251101886697977 330.90474764753 Trimmed Mean ( 24 / 36 ) 83.1366666666667 0.246526681915816 337.231921594013 Trimmed Mean ( 25 / 36 ) 83.1858620689655 0.240888157293848 345.329811990263 Trimmed Mean ( 26 / 36 ) 83.2383928571429 0.233773224665489 356.064698924569 Trimmed Mean ( 27 / 36 ) 83.2937037037037 0.225298667569088 369.703490049099 Trimmed Mean ( 28 / 36 ) 83.35 0.215829802786221 386.183923276611 Trimmed Mean ( 29 / 36 ) 83.41 0.203961380898344 408.949967060541 Trimmed Mean ( 30 / 36 ) 83.4691666666667 0.191720197581675 435.369709188349 Trimmed Mean ( 31 / 36 ) 83.5347826086957 0.175418819500145 476.201942566524 Trimmed Mean ( 32 / 36 ) 83.5954545454545 0.159548932941248 523.948690877411 Trimmed Mean ( 33 / 36 ) 83.6540476190476 0.142383501505698 587.526270490684 Trimmed Mean ( 34 / 36 ) 83.694 0.132889389130923 629.801977022746 Trimmed Mean ( 35 / 36 ) 83.7294736842105 0.124659962743848 671.662912785067 Trimmed Mean ( 36 / 36 ) 83.7669444444444 0.115170556370427 727.329510982146 Median 83.875 Midrange 81.235 Midmean - Weighted Average at Xnp 83.2103636363637 Midmean - Weighted Average at X(n+1)p 83.2937037037037 Midmean - Empirical Distribution Function 83.2103636363637 Midmean - Empirical Distribution Function - Averaging 83.2937037037037 Midmean - Empirical Distribution Function - Interpolation 83.2937037037037 Midmean - Closest Observation 83.2103636363637 Midmean - True Basic - Statistics Graphics Toolkit 83.2937037037037 Midmean - MS Excel (old versions) 83.2383928571429 Number of observations 108

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Dec/18/t1292681688ngb34tr4ndeipbm/1xvj91292681777.png (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/18/t1292681688ngb34tr4ndeipbm/1xvj91292681777.ps (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/18/t1292681688ngb34tr4ndeipbm/2xvj91292681777.png (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/18/t1292681688ngb34tr4ndeipbm/2xvj91292681777.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

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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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