Central Tendency Uitvoer naar Amerika

*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: Mon, 20 Oct 2008 12:01:54 -0600

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2008/Oct/20/t1224525799wpkqd7ntv82b6ys.htm/, Retrieved Mon, 20 Oct 2008 18:03:21 +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/Oct/20/t1224525799wpkqd7ntv82b6ys.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}, }

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Dataseries X:

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1045,9 1401,9 1027,6 1703,8 1481,3 1422,7 1304,7 1246,1 1417,8 1459,1 1156,4 1304,5 1336,9 1372,3 975,5 1180,8 1361,3 1428,1 1355,9 1781,2 1697 1852 1844,1 1967,2 1747,1 1863,9 1559,3 1675 2237,5 1965,2 1871,5 1752,2 1360,7 1444,3 1621,6 1368 1553,9 1695,3 1397,1 1848,4 1809,2 1551,1 1546,6 1467,9 1662,4 1972,3 1673,5 1762 2019,8 1754,3 1400,4 1453,6 1740,9 1694,6 1541,2 1482,3 1632,1 1837,3 1797 2066,2 1983,8 1601,7 1660,3 1954 1991,9 1881,4 2345,5 1773,1 1719,2 2240,9 1816,4 2171,3 1823,3 2022,5 1991 1920 2168,4 2013,5 1790,8 1855,7 2074 2535,8 1837,2 1805,1 1785,7 2250 1959,7 1890,8 2405,7 2090,3 1666,5 1803,5 1793,8 1488,8 1545 1369,9 1451,6

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 1705.44226804124 31.2374475764110 54.5960825982819 Geometric Mean 1677.09101893079 Harmonic Mean 1647.58025843055 Quadratic Mean 1732.68809374515 Winsorized Mean ( 1 / 32 ) 1704.63814432990 30.7654087006117 55.4076222720877 Winsorized Mean ( 2 / 32 ) 1703.77422680412 30.3957558262221 56.0530304475697 Winsorized Mean ( 3 / 32 ) 1704.23814432990 29.0593256291475 58.6468580200115 Winsorized Mean ( 4 / 32 ) 1704.86907216495 28.7920298399432 59.2132295514568 Winsorized Mean ( 5 / 32 ) 1708.05979381443 28.1507270137007 60.6755126779899 Winsorized Mean ( 6 / 32 ) 1707.57731958763 26.7871249151978 63.7461961667572 Winsorized Mean ( 7 / 32 ) 1707.38247422680 26.7472055100988 63.8340507602618 Winsorized Mean ( 8 / 32 ) 1703.59690721649 25.2438236914559 67.4856918681895 Winsorized Mean ( 9 / 32 ) 1703.84742268041 24.7427551136014 68.8624777175193 Winsorized Mean ( 10 / 32 ) 1703.53814432990 24.545975536561 69.401932784969 Winsorized Mean ( 11 / 32 ) 1698.65051546392 23.8030257272234 71.3627979455226 Winsorized Mean ( 12 / 32 ) 1699.14536082474 23.6340802846946 71.8938642992216 Winsorized Mean ( 13 / 32 ) 1698.55567010309 23.4782766803399 72.3458409332666 Winsorized Mean ( 14 / 32 ) 1695.78453608247 23.0007108221721 73.727483867489 Winsorized Mean ( 15 / 32 ) 1699.48041237113 22.4316393091198 75.7626488617884 Winsorized Mean ( 16 / 32 ) 1698.83711340206 22.1954951022537 76.5397259928465 Winsorized Mean ( 17 / 32 ) 1697.08453608247 21.8918663176108 77.5212360362929 Winsorized Mean ( 18 / 32 ) 1699.08865979381 21.3583689583843 79.5514237582654 Winsorized Mean ( 19 / 32 ) 1699.65670103093 21.1759522939757 80.263530888028 Winsorized Mean ( 20 / 32 ) 1699.63608247423 20.877038153149 81.411743850162 Winsorized Mean ( 21 / 32 ) 1701.90927835052 20.2468702813764 84.0578941188742 Winsorized Mean ( 22 / 32 ) 1695.85360824742 19.0532386838163 89.0060548964765 Winsorized Mean ( 23 / 32 ) 1689.40412371134 18.1648982546816 93.0037757451207 Winsorized Mean ( 24 / 32 ) 1688.43917525773 17.7148525228692 95.312065007486 Winsorized Mean ( 25 / 32 ) 1688.15567010309 17.1228636995621 98.590732235185 Winsorized Mean ( 26 / 32 ) 1689.71030927835 16.4185098799011 102.914961323429 Winsorized Mean ( 27 / 32 ) 1687.70618556701 16.1317058843416 104.620441115604 Winsorized Mean ( 28 / 32 ) 1688.51443298969 15.7678829903851 107.085677514179 Winsorized Mean ( 29 / 32 ) 1703.10412371134 13.6437798880611 124.826414504211 Winsorized Mean ( 30 / 32 ) 1702.94948453608 13.3517350028111 127.545183017604 Winsorized Mean ( 31 / 32 ) 1701.28762886598 13.051027370138 130.356605699770 Winsorized Mean ( 32 / 32 ) 1702.73917525773 12.8646553341225 132.357931948736 Trimmed Mean ( 1 / 32 ) 1704.38526315789 29.6754186951643 57.4342448430435 Trimmed Mean ( 2 / 32 ) 1704.12150537634 28.4271807772287 59.946904996693 Trimmed Mean ( 3 / 32 ) 1704.30659340659 27.2229477824106 62.605512343075 Trimmed Mean ( 4 / 32 ) 1704.33146067416 26.431283388469 64.4816006708814 Trimmed Mean ( 5 / 32 ) 1704.18160919540 25.6160192028116 66.5279642282729 Trimmed Mean ( 6 / 32 ) 1703.29647058824 24.8671771025701 68.4957710946691 Trimmed Mean ( 7 / 32 ) 1703.29647058824 24.3549897082192 69.9362426752912 Trimmed Mean ( 8 / 32 ) 1701.62098765432 23.7713985287466 71.5827041306198 Trimmed Mean ( 9 / 32 ) 1701.31772151899 23.4123057160173 72.6676706752144 Trimmed Mean ( 10 / 32 ) 1700.96363636364 23.0878410349206 73.6735684289801 Trimmed Mean ( 11 / 32 ) 1700.63066666667 22.7410570462232 74.7823930615882 Trimmed Mean ( 12 / 32 ) 1700.8698630137 22.4602839636218 75.7278877581664 Trimmed Mean ( 13 / 32 ) 1701.0661971831 22.1524948014942 76.788922079709 Trimmed Mean ( 14 / 32 ) 1701.0661971831 21.8089243663715 77.998628846 Trimmed Mean ( 15 / 32 ) 1701.91194029851 21.4729946753451 79.2582481405172 Trimmed Mean ( 16 / 32 ) 1702.15384615385 21.1590346084629 80.445723429794 Trimmed Mean ( 17 / 32 ) 1702.47301587302 20.8133722137989 81.7970773013087 Trimmed Mean ( 18 / 32 ) 1702.97704918033 20.4384932814149 83.3220446210132 Trimmed Mean ( 19 / 32 ) 1703.33220338983 20.0652936873076 84.8894728347424 Trimmed Mean ( 20 / 32 ) 1703.66140350877 19.6333611651575 86.7738024670062 Trimmed Mean ( 21 / 32 ) 1704.01636363636 19.1478375256844 88.9926270447322 Trimmed Mean ( 22 / 32 ) 1704.2 18.6536460869375 91.3601551169875 Trimmed Mean ( 23 / 32 ) 1704.92156862745 18.2420619994014 93.4610116270517 Trimmed Mean ( 24 / 32 ) 1706.25714285714 17.8663069342656 95.5013898023171 Trimmed Mean ( 25 / 32 ) 1706.25714285714 17.4574673392888 97.7379541771866 Trimmed Mean ( 26 / 32 ) 1709.48222222222 17.0326621135877 100.364946525798 Trimmed Mean ( 27 / 32 ) 1711.19767441860 16.6120213208063 103.009600178839 Trimmed Mean ( 28 / 32 ) 1711.19767441860 16.0967657139111 106.306925554602 Trimmed Mean ( 29 / 32 ) 1715.45384615385 15.4796204215781 110.820149295299 Trimmed Mean ( 30 / 32 ) 1716.57027027027 15.1823163813588 113.063792582923 Trimmed Mean ( 31 / 32 ) 1716.57027027027 14.8174899900031 115.847574145715 Trimmed Mean ( 32 / 32 ) 1719.39696969697 14.3548181680327 119.778387268322 Median 1740.9 Midrange 1755.65 Midmean - Weighted Average at Xnp 1702.60833333333 Midmean - Weighted Average at X(n+1)p 1706.25714285714 Midmean - Empirical Distribution Function 1706.25714285714 Midmean - Empirical Distribution Function - Averaging 1706.25714285714 Midmean - Empirical Distribution Function - Interpolation 1706.25714285714 Midmean - Closest Observation 1701.204 Midmean - True Basic - Statistics Graphics Toolkit 1706.25714285714 Midmean - MS Excel (old versions) 1706.25714285714 Number of observations 97

Charts produced by software:

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Oct/20/t1224525799wpkqd7ntv82b6ys/1umn81224525709.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Oct/20/t1224525799wpkqd7ntv82b6ys/1umn81224525709.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Oct/20/t1224525799wpkqd7ntv82b6ys/2xhfg1224525709.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Oct/20/t1224525799wpkqd7ntv82b6ys/2xhfg1224525709.ps (open in new window)

Parameters (Session):

par1 = grey ; par2 = grey ; par3 = TRUE ; par4 = Uitvoer naar Amerika ; par5 = Invoer vanuit Amerika ;

Parameters (R input):

par1 = grey ; par2 = grey ; par3 = TRUE ; par4 = Uitvoer naar Amerika ; par5 = Invoer vanuit Amerika ;

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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