Index passagiers luchtvervoer Denemarken 2000-2009

*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 13:10:18 +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/t1287407685g13mmz8ynux0hyj.htm/, Retrieved Mon, 18 Oct 2010 15:14:47 +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/t1287407685g13mmz8ynux0hyj.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:

KDGP1W52

Dataseries X:

» Textbox « » Textfile « » CSV «

100.4 97.7 97 96.5 98.4 106.3 103.1 102.4 95 98.1 106.1 99.1 101.2 95.5 99.8 97.1 97.5 96.8 97.7 100.9 94.3 99.5 100.8 97 99.2 101 102.3 97 91.2 97.6 95.7 100.5 94.4 102.9 105.1 98.8 100.7 99.6 107.7 102.9 101.6 102.7 110.5 109.8 94.3 102.5 105 102.3 107.7 100.3 99.5 95 97.7 96.3 97.8 106.4 96.1 106.2 114.7 111.9 121 117.7 115.4 114.3 109.5 108.1 108.2 99.1 101.2 98.1 95.5 97.9 98.2 98.7 95.6 95.8 94.4 96.5 103.3 104.3 104.5 102.3 103.8 103.1 102.2 106.3 102.1 94 102.6 102.6 106.7 107.9 109.3 105.9 109.1 108.5 111.7 109.8 109.1 108.5 108.5 106.2 117.1 109.8 115.2 115.9 119.2 121 118.6 117.6 114.6 110.6 102.5 101.6 107.4 105.8 102.8 104 100.4 100.6

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 1 seconds R Server 'Gwilym Jenkins' @ 72.249.127.135 Central Tendency - Ungrouped Data Measure Value S.E. Value/S.E. Arithmetic Mean 103.460833333333 0.608516007068845 170.021547718511 Geometric Mean 103.253451173400 Harmonic Mean 103.051534285520 Quadratic Mean 103.673568232216 Winsorized Mean ( 1 / 40 ) 103.484166666667 0.605002483770781 171.047507146886 Winsorized Mean ( 2 / 40 ) 103.459166666667 0.597378136879846 173.188739726971 Winsorized Mean ( 3 / 40 ) 103.444166666667 0.594109502202169 174.116330883840 Winsorized Mean ( 4 / 40 ) 103.4175 0.587397601184028 176.060473845211 Winsorized Mean ( 5 / 40 ) 103.413333333333 0.586548482493641 176.308244620605 Winsorized Mean ( 6 / 40 ) 103.418333333333 0.577745525836173 179.003261312419 Winsorized Mean ( 7 / 40 ) 103.348333333333 0.564232682565178 183.166159151717 Winsorized Mean ( 8 / 40 ) 103.348333333333 0.554012588887766 186.545099166095 Winsorized Mean ( 9 / 40 ) 103.333333333333 0.55128489248277 187.440894431119 Winsorized Mean ( 10 / 40 ) 103.3 0.542844979961045 190.293737279127 Winsorized Mean ( 11 / 40 ) 103.3 0.540142112226551 191.245965944372 Winsorized Mean ( 12 / 40 ) 103.28 0.533722197171432 193.508908843127 Winsorized Mean ( 13 / 40 ) 103.0525 0.487349721863633 211.454927286971 Winsorized Mean ( 14 / 40 ) 103.0525 0.481032331908924 214.231961479694 Winsorized Mean ( 15 / 40 ) 102.94 0.458015142924837 224.752394304336 Winsorized Mean ( 16 / 40 ) 102.926666666667 0.456148062682176 225.643108208006 Winsorized Mean ( 17 / 40 ) 102.87 0.437632092903955 235.060457557843 Winsorized Mean ( 18 / 40 ) 102.9 0.43417070569152 237.003553328425 Winsorized Mean ( 19 / 40 ) 102.9 0.43417070569152 237.003553328425 Winsorized Mean ( 20 / 40 ) 102.85 0.427563941849342 240.548816055776 Winsorized Mean ( 21 / 40 ) 102.8325 0.421010127325845 244.251844137734 Winsorized Mean ( 22 / 40 ) 102.869166666667 0.408038616274998 252.10644915367 Winsorized Mean ( 23 / 40 ) 102.888333333333 0.40592975778325 253.463392029198 Winsorized Mean ( 24 / 40 ) 102.788333333333 0.388601931610185 264.508035015231 Winsorized Mean ( 25 / 40 ) 102.788333333333 0.388601931610185 264.508035015231 Winsorized Mean ( 26 / 40 ) 102.788333333333 0.388601931610185 264.508035015231 Winsorized Mean ( 27 / 40 ) 102.743333333333 0.377862062877569 271.906982539878 Winsorized Mean ( 28 / 40 ) 102.743333333333 0.372478889167986 275.836661677212 Winsorized Mean ( 29 / 40 ) 102.743333333333 0.361410118253622 284.284606722694 Winsorized Mean ( 30 / 40 ) 102.693333333333 0.355453183208208 288.908183087448 Winsorized Mean ( 31 / 40 ) 102.719166666667 0.352659554912858 291.270051344698 Winsorized Mean ( 32 / 40 ) 102.6925 0.33750020749034 304.273887010690 Winsorized Mean ( 33 / 40 ) 102.5825 0.306534031952568 334.652891056068 Winsorized Mean ( 34 / 40 ) 102.525833333333 0.294012366194446 348.712656751069 Winsorized Mean ( 35 / 40 ) 102.584166666667 0.281569719198238 364.329541396612 Winsorized Mean ( 36 / 40 ) 102.584166666667 0.281569719198238 364.329541396612 Winsorized Mean ( 37 / 40 ) 102.584166666667 0.274958606085882 373.089492003844 Winsorized Mean ( 38 / 40 ) 102.679166666667 0.265259494092764 387.089506514548 Winsorized Mean ( 39 / 40 ) 102.646666666667 0.261644586839850 392.313358768228 Winsorized Mean ( 40 / 40 ) 102.613333333333 0.250911317525479 408.962554361117 Trimmed Mean ( 1 / 40 ) 103.416101694915 0.591453656423417 174.850726801291 Trimmed Mean ( 2 / 40 ) 103.345689655172 0.576341915324913 179.313159267466 Trimmed Mean ( 3 / 40 ) 103.285964912281 0.563989324153957 183.134609980819 Trimmed Mean ( 4 / 40 ) 103.229464285714 0.551551920696529 187.161825409566 Trimmed Mean ( 5 / 40 ) 103.178181818182 0.539845809108162 191.125280732724 Trimmed Mean ( 6 / 40 ) 103.125925925926 0.52695985761489 195.699775676826 Trimmed Mean ( 7 / 40 ) 103.070754716981 0.514595536323267 200.294692514069 Trimmed Mean ( 8 / 40 ) 103.025 0.50366237120445 204.551711404661 Trimmed Mean ( 9 / 40 ) 102.977450980392 0.49334319788198 208.733902529709 Trimmed Mean ( 10 / 40 ) 102.93 0.482193012195429 213.46223897223 Trimmed Mean ( 11 / 40 ) 102.884693877551 0.471063258379768 218.409506679475 Trimmed Mean ( 12 / 40 ) 102.8375 0.458867909939157 224.111335250346 Trimmed Mean ( 13 / 40 ) 102.790425531915 0.446033047695003 230.454729897510 Trimmed Mean ( 14 / 40 ) 102.764130434783 0.438715771044707 234.238514357649 Trimmed Mean ( 15 / 40 ) 102.736666666667 0.431249527311616 238.230212812339 Trimmed Mean ( 16 / 40 ) 102.718181818182 0.425928040336381 241.163229678561 Trimmed Mean ( 17 / 40 ) 102.7 0.420028661649877 244.507123862913 Trimmed Mean ( 18 / 40 ) 102.685714285714 0.415633749614416 247.058171722041 Trimmed Mean ( 19 / 40 ) 102.668292682927 0.410905529967907 249.858629770559 Trimmed Mean ( 20 / 40 ) 102.65 0.405351855284120 253.236783455821 Trimmed Mean ( 21 / 40 ) 102.634615384615 0.399711963072785 256.771437601246 Trimmed Mean ( 22 / 40 ) 102.619736842105 0.393923225830324 260.506946818888 Trimmed Mean ( 23 / 40 ) 102.601351351351 0.388722421820986 263.945030159853 Trimmed Mean ( 24 / 40 ) 102.580555555556 0.382774847753004 267.991891728864 Trimmed Mean ( 25 / 40 ) 102.565714285714 0.377996712082087 271.340228651091 Trimmed Mean ( 26 / 40 ) 102.55 0.372216034205141 275.512042943 Trimmed Mean ( 27 / 40 ) 102.533333333333 0.365233477922675 280.733666356404 Trimmed Mean ( 28 / 40 ) 102.51875 0.358339389483707 286.094001967544 Trimmed Mean ( 29 / 40 ) 102.503225806452 0.350733670428677 292.253736805962 Trimmed Mean ( 30 / 40 ) 102.486666666667 0.343095469135953 298.711804398839 Trimmed Mean ( 31 / 40 ) 102.472413793103 0.33466575594155 306.193304734173 Trimmed Mean ( 32 / 40 ) 102.455357142857 0.324676858762610 315.561008977755 Trimmed Mean ( 33 / 40 ) 102.438888888889 0.314881503192672 325.325202815129 Trimmed Mean ( 34 / 40 ) 102.428846153846 0.308029015430969 332.529862521348 Trimmed Mean ( 35 / 40 ) 102.422 0.301483271949384 339.726975024988 Trimmed Mean ( 36 / 40 ) 102.410416666667 0.295207577878081 346.909850359470 Trimmed Mean ( 37 / 40 ) 102.397826086957 0.287005009810586 356.780622590998 Trimmed Mean ( 38 / 40 ) 102.384090909091 0.27761714823068 368.795989590733 Trimmed Mean ( 39 / 40 ) 102.361904761905 0.267173278518611 383.129275986987 Trimmed Mean ( 40 / 40 ) 102.34 0.254114853903425 402.731278506426 Median 102.35 Midrange 106.1 Midmean - Weighted Average at Xnp 102.414754098361 Midmean - Weighted Average at X(n+1)p 102.414754098361 Midmean - Empirical Distribution Function 102.414754098361 Midmean - Empirical Distribution Function - Averaging 102.414754098361 Midmean - Empirical Distribution Function - Interpolation 102.414754098361 Midmean - Closest Observation 102.414754098361 Midmean - True Basic - Statistics Graphics Toolkit 102.414754098361 Midmean - MS Excel (old versions) 102.503225806452 Number of observations 120

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Oct/18/t1287407685g13mmz8ynux0hyj/1omnp1287407416.png (open in new window) http://www.freestatistics.org/blog/date/2010/Oct/18/t1287407685g13mmz8ynux0hyj/1omnp1287407416.ps (open in new window) http://www.freestatistics.org/blog/date/2010/Oct/18/t1287407685g13mmz8ynux0hyj/2omnp1287407416.png (open in new window) http://www.freestatistics.org/blog/date/2010/Oct/18/t1287407685g13mmz8ynux0hyj/2omnp1287407416.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

Disclaimer

Information provided on this web site is provided "AS IS" without warranty of any kind, either express or implied, including, without limitation, warranties of merchantability, fitness for a particular purpose, and noninfringement. We use reasonable efforts to include accurate and timely information and periodically update the information, and software without notice. However, we make no warranties or representations as to the accuracy or completeness of such information (or software), and we assume no liability or responsibility for errors or omissions in the content of this web site, or any software bugs in online applications. Your use of this web site is AT YOUR OWN RISK. Under no circumstances and under no legal theory shall we be liable to you or any other person for any direct, indirect, special, incidental, exemplary, or consequential damages arising from your access to, or use of, this web site.

Privacy Policy

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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