"Tijdreeks A stap 16"

*Unverified author*

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

Title produced by software: Central Tendency

Date of computation: Thu, 19 Aug 2010 16:04:19 +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/Aug/19/t1282236111gwgxbxen5cgkbjv.htm/, Retrieved Thu, 19 Aug 2010 18:41:53 +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/Aug/19/t1282236111gwgxbxen5cgkbjv.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:

ellen aerts

Dataseries X:

» Textbox « » Textfile « » CSV «

25 24 23 21 41 40 25 15 16 16 17 19 18 19 20 21 46 47 30 16 15 18 30 31 32 36 30 31 61 57 45 33 31 36 46 49 34 40 41 48 75 77 71 54 50 56 66 66 48 63 71 70 88 92 91 80 81 81 98 106 85 93 96 92 115 109 119 107 107 106 132 143 120 123 132 136 158 151 155 138 143 139 168 182 154 158 167 170 197 190 196 174 180 171 200 215 184 186 197 186 211 205 218 199 213 207 236 248 211 220 235 223 245 236 253 246 255 248 274 288

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 'George Udny Yule' @ 72.249.76.132 Central Tendency - Ungrouped Data Measure Value S.E. Value/S.E. Arithmetic Mean 111.433333333333 7.0625430598656 15.7780748929627 Geometric Mean 81.4519655127159 Harmonic Mean 55.4537548306887 Quadratic Mean 135.47342912911 Winsorized Mean ( 1 / 40 ) 111.316666666667 7.03895705578887 15.8143693425604 Winsorized Mean ( 2 / 40 ) 111.016666666667 6.97882936389641 15.9076344868080 Winsorized Mean ( 3 / 40 ) 110.966666666667 6.97021407277817 15.9201231853182 Winsorized Mean ( 4 / 40 ) 110.8 6.9421035083358 15.9605802285944 Winsorized Mean ( 5 / 40 ) 110.841666666667 6.93734460126592 15.9775350710473 Winsorized Mean ( 6 / 40 ) 110.791666666667 6.91516111149595 16.0215597121062 Winsorized Mean ( 7 / 40 ) 110.733333333333 6.90560334870969 16.0352872503202 Winsorized Mean ( 8 / 40 ) 110.2 6.8024299497524 16.2000933216535 Winsorized Mean ( 9 / 40 ) 110.2 6.8024299497524 16.2000933216535 Winsorized Mean ( 10 / 40 ) 110.2 6.78015724101478 16.2533103706466 Winsorized Mean ( 11 / 40 ) 109.191666666667 6.60511108261111 16.5313899041197 Winsorized Mean ( 12 / 40 ) 108.891666666667 6.56204812592147 16.5941584970280 Winsorized Mean ( 13 / 40 ) 108.891666666667 6.50715826303085 16.7341352807282 Winsorized Mean ( 14 / 40 ) 108.658333333333 6.44532592714981 16.8584699302217 Winsorized Mean ( 15 / 40 ) 108.533333333333 6.39708369013272 16.9660643178300 Winsorized Mean ( 16 / 40 ) 108.266666666667 6.3606891146378 17.0212165247180 Winsorized Mean ( 17 / 40 ) 108.975 6.28431713129778 17.3407862339206 Winsorized Mean ( 18 / 40 ) 108.375 6.20330243777085 17.4705330083736 Winsorized Mean ( 19 / 40 ) 108.058333333333 6.16121300028823 17.5384836278633 Winsorized Mean ( 20 / 40 ) 107.391666666667 6.03463736739243 17.7958773872556 Winsorized Mean ( 21 / 40 ) 107.216666666667 6.01212807084503 17.8333969940858 Winsorized Mean ( 22 / 40 ) 106.85 5.96532522516726 17.9118482172955 Winsorized Mean ( 23 / 40 ) 107.041666666667 5.9449198687253 18.0055692978782 Winsorized Mean ( 24 / 40 ) 107.041666666667 5.89837365223357 18.1476578083744 Winsorized Mean ( 25 / 40 ) 106 5.71999539675825 18.5314834449123 Winsorized Mean ( 26 / 40 ) 105.566666666667 5.56823892991122 18.9587171088489 Winsorized Mean ( 27 / 40 ) 105.566666666667 5.56823892991122 18.9587171088489 Winsorized Mean ( 28 / 40 ) 106.033333333333 5.41484800324312 19.5819593218179 Winsorized Mean ( 29 / 40 ) 105.55 5.35662173002196 19.7045834706658 Winsorized Mean ( 30 / 40 ) 105.3 5.27119703741787 19.9764871721779 Winsorized Mean ( 31 / 40 ) 103.75 5.08896001218346 20.3872696487323 Winsorized Mean ( 32 / 40 ) 104.016666666667 4.88707182831281 21.2840470369303 Winsorized Mean ( 33 / 40 ) 104.016666666667 4.82760188526889 21.5462395488880 Winsorized Mean ( 34 / 40 ) 103.45 4.76278832839172 21.7204697893707 Winsorized Mean ( 35 / 40 ) 103.45 4.70010802069085 22.0101324362316 Winsorized Mean ( 36 / 40 ) 101.05 4.36817254381612 23.1332437046364 Winsorized Mean ( 37 / 40 ) 101.05 4.36817254381612 23.1332437046364 Winsorized Mean ( 38 / 40 ) 100.416666666667 4.23232166610016 23.7261424317011 Winsorized Mean ( 39 / 40 ) 100.416666666667 4.16401456212344 24.1153495427401 Winsorized Mean ( 40 / 40 ) 100.75 3.92144949048723 25.6920305219798 Trimmed Mean ( 1 / 40 ) 110.754237288136 6.97541196460877 15.8778059059552 Trimmed Mean ( 2 / 40 ) 110.172413793103 6.90420939178756 15.9572816438840 Trimmed Mean ( 3 / 40 ) 109.728070175439 6.85889548720581 15.9979212950713 Trimmed Mean ( 4 / 40 ) 109.285714285714 6.81085736777732 16.0458086822891 Trimmed Mean ( 5 / 40 ) 108.872727272727 6.76503187196301 16.0934537092041 Trimmed Mean ( 6 / 40 ) 108.435185185185 6.71395834159659 16.1507086681445 Trimmed Mean ( 7 / 40 ) 107.990566037736 6.66074978151372 16.2129744518332 Trimmed Mean ( 8 / 40 ) 107.538461538462 6.60200202561704 16.2887653050077 Trimmed Mean ( 9 / 40 ) 107.147058823529 6.55414254645735 16.3479903075109 Trimmed Mean ( 10 / 40 ) 106.74 6.49903831269665 16.4239684187537 Trimmed Mean ( 11 / 40 ) 106.316326530612 6.43927430004413 16.5106068753561 Trimmed Mean ( 12 / 40 ) 105.989583333333 6.39742777928403 16.5675310437338 Trimmed Mean ( 13 / 40 ) 105.680851063830 6.35472814831042 16.6302709726345 Trimmed Mean ( 14 / 40 ) 105.358695652174 6.31210815763093 16.6915225501645 Trimmed Mean ( 15 / 40 ) 105.044444444444 6.27017415411041 16.7530345828724 Trimmed Mean ( 16 / 40 ) 104.727272727273 6.22676930898827 16.8188779012738 Trimmed Mean ( 17 / 40 ) 104.418604651163 6.17998324579206 16.8962601512328 Trimmed Mean ( 18 / 40 ) 104.035714285714 6.13337713638442 16.9622235796579 Trimmed Mean ( 19 / 40 ) 103.682926829268 6.08805401593379 17.0305530400859 Trimmed Mean ( 20 / 40 ) 103.3375 6.03887573758979 17.1120427858387 Trimmed Mean ( 21 / 40 ) 103.025641025641 5.99552986882034 17.1837424347470 Trimmed Mean ( 22 / 40 ) 102.710526315789 5.94547788613768 17.2754029672311 Trimmed Mean ( 23 / 40 ) 102.405405405405 5.89064604418015 17.3844098995865 Trimmed Mean ( 24 / 40 ) 102.069444444444 5.82636493202765 17.5185464067598 Trimmed Mean ( 25 / 40 ) 101.714285714286 5.75432658744769 17.6761405819687 Trimmed Mean ( 26 / 40 ) 101.411764705882 5.6907899381661 17.8203317654988 Trimmed Mean ( 27 / 40 ) 101.121212121212 5.63263530598394 17.9527355541347 Trimmed Mean ( 28 / 40 ) 100.8125 5.56027019691475 18.1308635065861 Trimmed Mean ( 29 / 40 ) 100.451612903226 5.49095103972463 18.2940281522276 Trimmed Mean ( 30 / 40 ) 100.1 5.41282740949421 18.4931076546839 Trimmed Mean ( 31 / 40 ) 99.7413793103448 5.32753921945225 18.721847968038 Trimmed Mean ( 32 / 40 ) 99.4642857142857 5.24911645538105 18.9487671991581 Trimmed Mean ( 33 / 40 ) 99.1481481481482 5.1793418207627 19.1430014815179 Trimmed Mean ( 34 / 40 ) 98.8076923076923 5.09798694940498 19.3817075815043 Trimmed Mean ( 35 / 40 ) 98.48 5.00377327012081 19.6811475428067 Trimmed Mean ( 36 / 40 ) 98.125 4.89206415193696 20.0579953476588 Trimmed Mean ( 37 / 40 ) 97.9130434782609 4.80999624242389 20.3561579975206 Trimmed Mean ( 38 / 40 ) 97.6818181818182 4.69962131613681 20.7850402427987 Trimmed Mean ( 39 / 40 ) 97.4761904761905 4.58057785551171 21.2803260966080 Trimmed Mean ( 40 / 40 ) 97.25 4.43467542824119 21.9294515627201 Median 92.5 Midrange 151.5 Midmean - Weighted Average at Xnp 98.1612903225806 Midmean - Weighted Average at X(n+1)p 100.1 Midmean - Empirical Distribution Function 98.1612903225806 Midmean - Empirical Distribution Function - Averaging 100.1 Midmean - Empirical Distribution Function - Interpolation 100.1 Midmean - Closest Observation 98.1612903225806 Midmean - True Basic - Statistics Graphics Toolkit 100.1 Midmean - MS Excel (old versions) 99.4920634920635 Number of observations 120

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Aug/19/t1282236111gwgxbxen5cgkbjv/1h5ub1282233854.png (open in new window) http://www.freestatistics.org/blog/date/2010/Aug/19/t1282236111gwgxbxen5cgkbjv/1h5ub1282233854.ps (open in new window) http://www.freestatistics.org/blog/date/2010/Aug/19/t1282236111gwgxbxen5cgkbjv/2awtw1282233854.png (open in new window) http://www.freestatistics.org/blog/date/2010/Aug/19/t1282236111gwgxbxen5cgkbjv/2awtw1282233854.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.

FreeStatistics.org is powered by