Opdracht 5 oef 2

*Unverified author*

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

Title produced by software: Central Tendency

Date of computation: Mon, 18 Oct 2010 10:25:44 +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/Oct/18/t1287397610o0om81ov5bsvn6a.htm/, Retrieved Mon, 18 Oct 2010 12:26:52 +0200

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/Oct/18/t1287397610o0om81ov5bsvn6a.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:

» Textbox « » Textfile « » CSV «

78,1 66,7 79 65,2 66,5 77,2 80,2 77,9 78 86,8 92,9 185,8 91 79,1 84,2 70,1 71,3 79,6 92,3 78,7 82,5 98,2 115,4 205,6 94 83,2 80,3 70,4 71,1 78,8 86,3 77,5 80,1 89,8 99,9 218 85,4 77,5 78,6 68,8 64,8 79,8 94,3 79,9 87,5 99,1 109,9 273,6 91,3 80,6 80,4 71,8 75,5 86,6 91,5 86,8 84,6 88,6 102,1 260,3 79 70,6 79,3 66,8 61,2 72,5 83,5 75,8 83,4 89,4 104,9 251,6 80 76,3 81,1 63,1 63,5 78,8 91,7 83,8 83,8 95,8 108,9 258,2 88,7 79,5 74,3 70,5 59,1 73,2 81,2 75 74,6 89,5 107 246,4 83,6 72,1 68,7 60,1 61,1 72,7 85,3 71,4 75,2 89,8 100,9 222,7

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 'Gwilym Jenkins' @ 72.249.127.135 Central Tendency - Ungrouped Data Measure Value S.E. Value/S.E. Arithmetic Mean 94.2277777777778 4.32924518263754 21.7654057006701 Geometric Mean 88.0608238229212 Harmonic Mean 84.4194794770544 Quadratic Mean 104.327882356717 Winsorized Mean ( 1 / 36 ) 94.1138888888889 4.28236752434816 21.9770695424406 Winsorized Mean ( 2 / 36 ) 94.0935185185185 4.26696971948063 22.0516021215101 Winsorized Mean ( 3 / 36 ) 93.912962962963 4.20166219490054 22.3513834779348 Winsorized Mean ( 4 / 36 ) 93.7907407407407 4.129619210476 22.7117164950252 Winsorized Mean ( 5 / 36 ) 92.712037037037 3.76105287413463 24.650554017635 Winsorized Mean ( 6 / 36 ) 92.5231481481482 3.67201314315533 25.1968455833586 Winsorized Mean ( 7 / 36 ) 91.7453703703704 3.41655570173104 26.8531756481788 Winsorized Mean ( 8 / 36 ) 90.375 2.95953473330861 30.5368945269871 Winsorized Mean ( 9 / 36 ) 84.525 1.35184714279136 62.5255602682034 Winsorized Mean ( 10 / 36 ) 84.025 1.24673969069396 67.3957848837152 Winsorized Mean ( 11 / 36 ) 84.1166666666667 1.20295622077017 69.9249608708225 Winsorized Mean ( 12 / 36 ) 83.9166666666667 1.16167639158577 72.2375588197281 Winsorized Mean ( 13 / 36 ) 83.8203703703704 1.09680832730806 76.4220769330719 Winsorized Mean ( 14 / 36 ) 83.4962962962963 1.02889705767336 81.1512635531353 Winsorized Mean ( 15 / 36 ) 83.3435185185185 0.999468769547976 83.3878166660593 Winsorized Mean ( 16 / 36 ) 83.2101851851852 0.973651617804648 85.4619698294183 Winsorized Mean ( 17 / 36 ) 83.162962962963 0.944167016176209 88.08077547526 Winsorized Mean ( 18 / 36 ) 83.0462962962963 0.916760049926612 90.5867312858412 Winsorized Mean ( 19 / 36 ) 82.6416666666667 0.851439972024182 97.0610605351279 Winsorized Mean ( 20 / 36 ) 82.437962962963 0.80302486892055 102.659290083729 Winsorized Mean ( 21 / 36 ) 82.437962962963 0.78780919811096 104.642041703291 Winsorized Mean ( 22 / 36 ) 82.2953703703704 0.747590318710775 110.080840148237 Winsorized Mean ( 23 / 36 ) 82.2101851851852 0.725598712951917 113.299794662994 Winsorized Mean ( 24 / 36 ) 82.187962962963 0.694880300512105 118.276432505560 Winsorized Mean ( 25 / 36 ) 82.3962962962963 0.658899359605459 125.051413535497 Winsorized Mean ( 26 / 36 ) 82.4203703703704 0.644447701936918 127.893031696214 Winsorized Mean ( 27 / 36 ) 82.4453703703704 0.623558752587755 132.217485566875 Winsorized Mean ( 28 / 36 ) 82.1861111111111 0.578637019349378 142.033966654124 Winsorized Mean ( 29 / 36 ) 82.2666666666667 0.569619999279426 144.423768074742 Winsorized Mean ( 30 / 36 ) 82.2666666666667 0.550145517110281 149.536193803385 Winsorized Mean ( 31 / 36 ) 82.3814814814815 0.531042503750366 155.131615453907 Winsorized Mean ( 32 / 36 ) 82.4407407407408 0.477547163010096 172.633714796035 Winsorized Mean ( 33 / 36 ) 82.5018518518518 0.464486416918032 177.619514472069 Winsorized Mean ( 34 / 36 ) 82.1555555555556 0.422746572807615 194.337602809954 Winsorized Mean ( 35 / 36 ) 82.0583333333333 0.382953048536211 214.277791094733 Winsorized Mean ( 36 / 36 ) 82.0916666666667 0.379582591704669 216.268260085377 Trimmed Mean ( 1 / 36 ) 92.8669811320755 4.054681436121 22.9036442431144 Trimmed Mean ( 2 / 36 ) 91.5721153846154 3.78793051436377 24.1747083367489 Trimmed Mean ( 3 / 36 ) 90.2372549019608 3.4808890903874 25.9236225455026 Trimmed Mean ( 4 / 36 ) 88.914 3.14255413717099 28.2935459880550 Trimmed Mean ( 5 / 36 ) 87.5704081632653 2.75448459351994 31.7919397223273 Trimmed Mean ( 6 / 36 ) 86.4135416666667 2.41422848260263 35.7934397217904 Trimmed Mean ( 7 / 36 ) 85.2436170212766 2.00790906910935 42.453923005133 Trimmed Mean ( 8 / 36 ) 84.1532608695652 1.55517757314426 54.1116733695071 Trimmed Mean ( 9 / 36 ) 83.22 1.09054751507978 76.310292627563 Trimmed Mean ( 10 / 36 ) 83.0420454545455 1.03586384324999 80.1669505077075 Trimmed Mean ( 11 / 36 ) 82.9186046511628 0.994411899050767 83.3845660237112 Trimmed Mean ( 12 / 36 ) 82.7785714285714 0.954327149446908 86.7402457077185 Trimmed Mean ( 13 / 36 ) 82.6536585365854 0.915450363497418 90.2874277320864 Trimmed Mean ( 14 / 36 ) 82.5325 0.881656910724261 93.6106766658262 Trimmed Mean ( 15 / 36 ) 82.4371794871795 0.854155010794527 96.5131368959567 Trimmed Mean ( 16 / 36 ) 82.3513157894737 0.826950630531851 99.5843194853236 Trimmed Mean ( 17 / 36 ) 82.272972972973 0.799322411345939 102.928395107098 Trimmed Mean ( 18 / 36 ) 82.1944444444444 0.771534578603946 106.533714397054 Trimmed Mean ( 19 / 36 ) 82.1214285714286 0.743189625387919 110.498620763932 Trimmed Mean ( 20 / 36 ) 82.0779411764706 0.720570832600593 113.906832559743 Trimmed Mean ( 21 / 36 ) 82.0484848484848 0.701398012644027 116.978496330765 Trimmed Mean ( 22 / 36 ) 82.0171875 0.680771747402176 120.476779203863 Trimmed Mean ( 23 / 36 ) 81.9951612903226 0.662429176320128 123.779513676942 Trimmed Mean ( 24 / 36 ) 81.9783333333333 0.643740357468968 127.346891308248 Trimmed Mean ( 25 / 36 ) 81.9620689655172 0.625964845512385 130.937175710606 Trimmed Mean ( 26 / 36 ) 81.9285714285714 0.60988988938985 134.333381900354 Trimmed Mean ( 27 / 36 ) 81.8907407407407 0.592300165880928 138.258851606000 Trimmed Mean ( 28 / 36 ) 81.8480769230769 0.57390784457259 142.61536533628 Trimmed Mean ( 29 / 36 ) 81.822 0.559163296217424 146.329346996668 Trimmed Mean ( 30 / 36 ) 81.7875 0.541844965199509 150.942622434234 Trimmed Mean ( 31 / 36 ) 81.75 0.523346256648336 156.206333687282 Trimmed Mean ( 32 / 36 ) 81.7 0.50296163043649 162.437838308059 Trimmed Mean ( 33 / 36 ) 81.6404761904762 0.48748637699551 167.472323418852 Trimmed Mean ( 34 / 36 ) 81.57 0.46920828025133 173.846036894974 Trimmed Mean ( 35 / 36 ) 81.521052631579 0.455426548764077 178.999342161339 Trimmed Mean ( 36 / 36 ) 81.475 0.445940685784663 182.703670235066 Median 80.35 Midrange 166.35 Midmean - Weighted Average at Xnp 81.7581818181818 Midmean - Weighted Average at X(n+1)p 81.8907407407408 Midmean - Empirical Distribution Function 81.7581818181818 Midmean - Empirical Distribution Function - Averaging 81.8907407407408 Midmean - Empirical Distribution Function - Interpolation 81.8907407407408 Midmean - Closest Observation 81.7581818181818 Midmean - True Basic - Statistics Graphics Toolkit 81.8907407407408 Midmean - MS Excel (old versions) 81.9285714285714 Number of observations 108

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Oct/18/t1287397610o0om81ov5bsvn6a/1ujua1287397542.png (open in new window) http://www.freestatistics.org/blog/date/2010/Oct/18/t1287397610o0om81ov5bsvn6a/1ujua1287397542.ps (open in new window) http://www.freestatistics.org/blog/date/2010/Oct/18/t1287397610o0om81ov5bsvn6a/2ujua1287397542.png (open in new window) http://www.freestatistics.org/blog/date/2010/Oct/18/t1287397610o0om81ov5bsvn6a/2ujua1287397542.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 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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