SLR Central tendency vrouwen in Belgie

*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: Tue, 07 Dec 2010 18:46:03 +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/07/t1291747473w3286udvxfr8ej4.htm/, Retrieved Tue, 07 Dec 2010 19:44:35 +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/07/t1291747473w3286udvxfr8ej4.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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57619 57077 56161 55614 57029 57667 57275 57514 58519 58759 58170 58277 61050 63191 64035 63358 62149 61789 60973 61229 60566 61922 62945 64810 66641 67675 66585 66573 66193 65545 64835 67184 69421 72359 74730 75067 74927 74845 75335 78121 79944 82779 81484 79939 80611 79088 79992 77800 76277 75425 74524 72844 70768 70172 67726 68032 67096 68261 67363 67322 57465 57031 54046 47435 43623 48866 53075 53778 51237 50393 49947 50660 50307 52235 51783 51602 47498 45981 43588 42791 41325 38917 36971 33628 31445 28478 19247 12209 10467 10127 10344 10117 8142 6404 4519 3482 2373 1772 1178 746 503 293 161 91 55 20 14 8 2 0 1

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 'Gwilym Jenkins' @ 72.249.127.135 Central Tendency - Ungrouped Data Measure Value S.E. Value/S.E. Arithmetic Mean 48356.4054054054 2507.66249325509 19.2834584141488 Geometric Mean 0 Harmonic Mean 0 Quadratic Mean 55046.0059726457 Winsorized Mean ( 1 / 37 ) 48344.7477477477 2506.23175502681 19.2898153376205 Winsorized Mean ( 2 / 37 ) 48329.036036036 2504.36153580822 19.2979469397732 Winsorized Mean ( 3 / 37 ) 48312.4684684685 2502.39014601763 19.3065292178177 Winsorized Mean ( 4 / 37 ) 48310.954954955 2502.15326955377 19.3077520641134 Winsorized Mean ( 5 / 37 ) 48311 2502.07996282628 19.3083357517596 Winsorized Mean ( 6 / 37 ) 48266.8918918919 2496.52344349234 19.3336425570962 Winsorized Mean ( 7 / 37 ) 48208.1801801802 2489.37168980935 19.3656015200656 Winsorized Mean ( 8 / 37 ) 48190.0900900901 2485.96922097953 19.3848297410143 Winsorized Mean ( 9 / 37 ) 48077.3063063063 2470.99641166654 19.4566475610060 Winsorized Mean ( 10 / 37 ) 48019.4684684685 2459.80319784418 19.5216708843023 Winsorized Mean ( 11 / 37 ) 48034.6306306306 2454.6774795755 19.5686117749927 Winsorized Mean ( 12 / 37 ) 48052.3603603604 2443.59503172714 19.6646169829527 Winsorized Mean ( 13 / 37 ) 48105.5315315315 2429.85272694939 19.7977148976954 Winsorized Mean ( 14 / 37 ) 48170.990990991 2415.71232909049 19.9406984063898 Winsorized Mean ( 15 / 37 ) 48305.3153153153 2388.45163620838 20.2245314843382 Winsorized Mean ( 16 / 37 ) 48425.0990990991 2360.07408537205 20.5184656698882 Winsorized Mean ( 17 / 37 ) 48456.4954954955 2286.10177513366 21.1961234720893 Winsorized Mean ( 18 / 37 ) 48659.6846846847 2231.66342656430 21.8042219563537 Winsorized Mean ( 19 / 37 ) 48725.4144144144 2150.32497684779 22.6595584104883 Winsorized Mean ( 20 / 37 ) 48619.8288288288 2140.11103678631 22.7183674085614 Winsorized Mean ( 21 / 37 ) 48518.8018018018 2120.5248015237 22.8805632298848 Winsorized Mean ( 22 / 37 ) 48313.2702702703 2096.28182529545 23.0471254805927 Winsorized Mean ( 23 / 37 ) 48626.7747747748 2033.15794124194 23.9168702973815 Winsorized Mean ( 24 / 37 ) 50082.3423423423 1783.556537862 28.0800419157878 Winsorized Mean ( 25 / 37 ) 52149.9099099099 1465.39977626139 35.5874968419593 Winsorized Mean ( 26 / 37 ) 52771.8018018018 1357.60416009187 38.8712729034587 Winsorized Mean ( 27 / 37 ) 53292.8288288288 1281.64599448522 41.5815514253875 Winsorized Mean ( 28 / 37 ) 54101.2972972973 1162.73758595441 46.5292409489707 Winsorized Mean ( 29 / 37 ) 54586.7207207207 1093.16500183648 49.9345667205012 Winsorized Mean ( 30 / 37 ) 55114.5585585586 996.917557766723 55.284971288925 Winsorized Mean ( 31 / 37 ) 55508.3423423423 944.442391680506 58.7736666961474 Winsorized Mean ( 32 / 37 ) 55734.6486486486 916.158726904166 60.8351446227928 Winsorized Mean ( 33 / 37 ) 55632.0810810811 902.820127431549 61.6203376406216 Winsorized Mean ( 34 / 37 ) 56155.8648648649 795.87938388394 70.55826046256 Winsorized Mean ( 35 / 37 ) 56390.4594594595 719.302027554622 78.3960802267824 Winsorized Mean ( 36 / 37 ) 56402.7837837838 716.125501151676 78.7610323792081 Winsorized Mean ( 37 / 37 ) 56600.4504504505 637.694595661907 88.7579271260735 Trimmed Mean ( 1 / 37 ) 48484.2385321101 2494.57402926404 19.4358788167189 Trimmed Mean ( 2 / 37 ) 48628.9439252336 2481.00036005723 19.6005388423692 Trimmed Mean ( 3 / 37 ) 48787.4666666667 2466.33105601236 19.7813941270106 Trimmed Mean ( 4 / 37 ) 48958.0970873786 2450.10939003393 19.9820045939666 Trimmed Mean ( 5 / 37 ) 49135.900990099 2431.41674470598 20.2087532287851 Trimmed Mean ( 6 / 37 ) 49320.8787878788 2409.87760057159 20.4661343697209 Trimmed Mean ( 7 / 37 ) 49320.8787878788 2386.31853922244 20.6681874096949 Trimmed Mean ( 8 / 37 ) 49741.1789473684 2360.59106506804 21.0714933575057 Trimmed Mean ( 9 / 37 ) 49972.5913978495 2331.53705274858 21.4333249986048 Trimmed Mean ( 10 / 37 ) 50229.4615384615 2300.52773800605 21.8338865072748 Trimmed Mean ( 11 / 37 ) 50505.0898876404 2266.4303831071 22.2839802466828 Trimmed Mean ( 12 / 37 ) 50791.632183908 2227.71574836735 22.7998712228579 Trimmed Mean ( 13 / 37 ) 51089.7294117647 2184.51043027876 23.3872673270986 Trimmed Mean ( 14 / 37 ) 51089.7294117647 2136.41504632539 23.9137659602419 Trimmed Mean ( 15 / 37 ) 51712.4691358025 2082.52554932873 24.8316133036021 Trimmed Mean ( 16 / 37 ) 52031.6202531646 2023.84208393079 25.7093281468417 Trimmed Mean ( 17 / 37 ) 52356.5584415584 1959.41721448013 26.7204748711211 Trimmed Mean ( 18 / 37 ) 52696.0933333333 1894.87963421706 27.8097312260717 Trimmed Mean ( 19 / 37 ) 53037.0684931507 1827.17274327384 29.0268496442878 Trimmed Mean ( 20 / 37 ) 53391.8450704225 1759.25365218765 30.3491455049869 Trimmed Mean ( 21 / 37 ) 53775.6811594203 1678.45987430618 32.0387052336592 Trimmed Mean ( 22 / 37 ) 54190.4029850746 1582.62709775745 34.240790557587 Trimmed Mean ( 23 / 37 ) 54646.6 1466.99063460515 37.2508172246842 Trimmed Mean ( 24 / 37 ) 55107.746031746 1334.77838340492 41.2860642012874 Trimmed Mean ( 25 / 37 ) 55488.7704918033 1226.41580955234 45.244663400138 Trimmed Mean ( 26 / 37 ) 55740.0338983051 1162.33249944044 47.9553259718186 Trimmed Mean ( 27 / 37 ) 55962.350877193 1104.64676917267 50.6608559758031 Trimmed Mean ( 28 / 37 ) 55962.350877193 1048.48225168710 53.3746286950921 Trimmed Mean ( 29 / 37 ) 56316.0188679245 1003.24752522630 56.1337231858326 Trimmed Mean ( 30 / 37 ) 56445.8039215686 960.828180767277 58.7470320411433 Trimmed Mean ( 31 / 37 ) 56445.8039215686 926.981388824869 60.8920573832931 Trimmed Mean ( 32 / 37 ) 56625.4042553191 894.732962741232 63.2874909200098 Trimmed Mean ( 33 / 37 ) 56694.0666666667 859.18743936326 65.9856791070903 Trimmed Mean ( 34 / 37 ) 56777.1395348837 815.228393750599 69.6456845346991 Trimmed Mean ( 35 / 37 ) 56826.6097560976 783.492197945533 72.5298987087655 Trimmed Mean ( 36 / 37 ) 56862.0769230769 759.263410349154 74.8911064961347 Trimmed Mean ( 37 / 37 ) 56900.3513513514 726.70794598868 78.2987879318408 Median 57465 Midrange 41389.5 Midmean - Weighted Average at Xnp 55759.5 Midmean - Weighted Average at X(n+1)p 55962.350877193 Midmean - Empirical Distribution Function 55962.350877193 Midmean - Empirical Distribution Function - Averaging 55962.350877193 Midmean - Empirical Distribution Function - Interpolation 56161.8909090909 Midmean - Closest Observation 55759.5 Midmean - True Basic - Statistics Graphics Toolkit 55962.350877193 Midmean - MS Excel (old versions) 55962.350877193 Number of observations 111

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Dec/07/t1291747473w3286udvxfr8ej4/1nq4u1291747559.png (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/07/t1291747473w3286udvxfr8ej4/1nq4u1291747559.ps (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/07/t1291747473w3286udvxfr8ej4/2nq4u1291747559.png (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/07/t1291747473w3286udvxfr8ej4/2nq4u1291747559.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')

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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 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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