Central Tendency omzet product A

*Unverified author*

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

Title produced by software: Central Tendency

Date of computation: Sun, 15 Aug 2010 11:35:55 +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/15/t1281872126ggaddedk352pzon.htm/, Retrieved Sun, 15 Aug 2010 13:35:29 +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/15/t1281872126ggaddedk352pzon.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:

Sebastien Delforge

Dataseries X:

» Textbox « » Textfile « » CSV «

75 74 73 71 91 90 75 65 66 66 67 69 75 79 75 77 100 100 94 83 83 83 84 88 89 98 94 84 111 98 98 83 79 78 80 94 98 104 94 90 115 104 114 99 96 98 104 111 117 125 117 118 151 145 155 133 124 125 131 133 136 141 130 137 177 183 191 166 156 153 164 164 168 173 164 165 205 207 215 190 169 175 188 188 196 201 194 197 237 236 244 222 195 199 207 204 212 222 214 217 258 256 251 223 198 206 214 212 227 238 228 235 275 278 278 251 225 232 238 239

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 150.45 5.63827766875914 26.6836805206705 Geometric Mean 137.660704489102 Harmonic Mean 125.639721357737 Quadratic Mean 162.536867612654 Winsorized Mean ( 1 / 40 ) 150.458333333333 5.63722243018294 26.6901537409179 Winsorized Mean ( 2 / 40 ) 150.408333333333 5.62781825861563 26.7258689640649 Winsorized Mean ( 3 / 40 ) 150.008333333333 5.55036143160743 27.0267684693625 Winsorized Mean ( 4 / 40 ) 150.008333333333 5.53125187598548 27.1201414610335 Winsorized Mean ( 5 / 40 ) 149.883333333333 5.48818674465113 27.3101737070831 Winsorized Mean ( 6 / 40 ) 149.983333333333 5.47624080478639 27.3880091617307 Winsorized Mean ( 7 / 40 ) 149.633333333333 5.40776924932714 27.6700662388565 Winsorized Mean ( 8 / 40 ) 149.366666666667 5.35205834030776 27.9082657865941 Winsorized Mean ( 9 / 40 ) 149.291666666667 5.34154736644484 27.9491421539205 Winsorized Mean ( 10 / 40 ) 149.291666666667 5.34154736644484 27.9491421539205 Winsorized Mean ( 11 / 40 ) 149.2 5.32880497531914 27.9987728376313 Winsorized Mean ( 12 / 40 ) 149.3 5.29181493649663 28.2133827035988 Winsorized Mean ( 13 / 40 ) 149.3 5.26456363358834 28.359425470224 Winsorized Mean ( 14 / 40 ) 149.066666666667 5.20394610739794 28.6449289808657 Winsorized Mean ( 15 / 40 ) 148.566666666667 5.13798036231631 28.9153823467884 Winsorized Mean ( 16 / 40 ) 148.566666666667 5.10560373927351 29.0987460550173 Winsorized Mean ( 17 / 40 ) 148.708333333333 5.02187645346958 29.6121050988006 Winsorized Mean ( 18 / 40 ) 148.408333333333 4.98386044775049 29.7777866955161 Winsorized Mean ( 19 / 40 ) 148.25 4.96401970147568 29.8649096730879 Winsorized Mean ( 20 / 40 ) 148.25 4.96401970147568 29.8649096730879 Winsorized Mean ( 21 / 40 ) 147.55 4.83726561762554 30.5027698835417 Winsorized Mean ( 22 / 40 ) 147.183333333333 4.79334832261577 30.7057454261981 Winsorized Mean ( 23 / 40 ) 147.758333333333 4.68702535723314 31.5249699055519 Winsorized Mean ( 24 / 40 ) 147.958333333333 4.66569211262623 31.7119796509784 Winsorized Mean ( 25 / 40 ) 147.75 4.59436157298327 32.1589839312671 Winsorized Mean ( 26 / 40 ) 147.75 4.59436157298327 32.1589839312671 Winsorized Mean ( 27 / 40 ) 146.85 4.44041866575336 33.0712059051048 Winsorized Mean ( 28 / 40 ) 147.55 4.36735486483594 33.7847517700036 Winsorized Mean ( 29 / 40 ) 147.308333333333 4.33980010630118 33.9435756774716 Winsorized Mean ( 30 / 40 ) 147.058333333333 4.31147735137821 34.1085714589976 Winsorized Mean ( 31 / 40 ) 146.8 4.28239180269867 34.2799086966984 Winsorized Mean ( 32 / 40 ) 146.533333333333 4.13824367225313 35.4095468847902 Winsorized Mean ( 33 / 40 ) 146.533333333333 4.02156186706196 36.4369213199215 Winsorized Mean ( 34 / 40 ) 146.25 3.99059205256212 36.6486972543589 Winsorized Mean ( 35 / 40 ) 145.958333333333 3.95889941404109 36.8684116640248 Winsorized Mean ( 36 / 40 ) 145.658333333333 3.92648651280006 37.0963539180634 Winsorized Mean ( 37 / 40 ) 145.35 3.89335514507915 37.3328387942490 Winsorized Mean ( 38 / 40 ) 145.35 3.82717780041199 37.9783766472394 Winsorized Mean ( 39 / 40 ) 144.7 3.69061949663028 39.2075097777265 Winsorized Mean ( 40 / 40 ) 144.366666666667 3.65556506289223 39.4922985045835 Trimmed Mean ( 1 / 40 ) 150.093220338983 5.58330154677928 26.8825208671676 Trimmed Mean ( 2 / 40 ) 149.715517241379 5.52308506822383 27.1072263765668 Trimmed Mean ( 3 / 40 ) 149.350877192982 5.46125763507871 27.3473414317012 Trimmed Mean ( 4 / 40 ) 149.116071428571 5.42304216721983 27.4967567705668 Trimmed Mean ( 5 / 40 ) 148.872727272727 5.38561561582821 27.6426573844582 Trimmed Mean ( 6 / 40 ) 148.648148148148 5.35409889815434 27.7634296593569 Trimmed Mean ( 7 / 40 ) 148.396226415094 5.3204867614915 27.8914755486572 Trimmed Mean ( 8 / 40 ) 148.192307692308 5.29545433531937 27.9848145802904 Trimmed Mean ( 9 / 40 ) 148.019607843137 5.2760890060166 28.0547973459778 Trimmed Mean ( 10 / 40 ) 147.85 5.25459635255486 28.1372707016997 Trimmed Mean ( 11 / 40 ) 147.673469387755 5.22892261450078 28.2416628194552 Trimmed Mean ( 12 / 40 ) 147.5 5.20043436107597 28.3630154250196 Trimmed Mean ( 13 / 40 ) 147.308510638298 5.17194680628513 28.4822168819067 Trimmed Mean ( 14 / 40 ) 147.108695652174 5.14183576566065 28.6101506070318 Trimmed Mean ( 15 / 40 ) 146.922222222222 5.11410933609827 28.7287995947138 Trimmed Mean ( 16 / 40 ) 146.772727272727 5.08939744686793 28.8389202857507 Trimmed Mean ( 17 / 40 ) 146.616279069767 5.06332454343874 28.9565240805587 Trimmed Mean ( 18 / 40 ) 146.440476190476 5.04163250223299 29.046241693661 Trimmed Mean ( 19 / 40 ) 146.280487804878 5.01918254626931 29.1442852409515 Trimmed Mean ( 20 / 40 ) 146.125 4.99345695303085 29.2632942217129 Trimmed Mean ( 21 / 40 ) 145.961538461538 4.96143778599777 29.4192016018971 Trimmed Mean ( 22 / 40 ) 145.842105263158 4.9374349698255 29.5380306078871 Trimmed Mean ( 23 / 40 ) 145.743243243243 4.91218934392954 29.6697120243038 Trimmed Mean ( 24 / 40 ) 145.597222222222 4.8922929601318 29.7605281222365 Trimmed Mean ( 25 / 40 ) 145.428571428571 4.86822508706954 29.8730171320227 Trimmed Mean ( 26 / 40 ) 145.264705882353 4.84535283487249 29.9802121399433 Trimmed Mean ( 27 / 40 ) 145.090909090909 4.81483368738411 30.1341476178249 Trimmed Mean ( 28 / 40 ) 144.96875 4.79474377129177 30.2349316073971 Trimmed Mean ( 29 / 40 ) 144.790322580645 4.7753961960868 30.3200648983415 Trimmed Mean ( 30 / 40 ) 144.616666666667 4.75139537438914 30.4366728658651 Trimmed Mean ( 31 / 40 ) 144.448275862069 4.72179257424682 30.5918300286857 Trimmed Mean ( 32 / 40 ) 144.285714285714 4.68540939774635 30.7946866617706 Trimmed Mean ( 33 / 40 ) 144.129629629630 4.65685148524439 30.95001635468 Trimmed Mean ( 34 / 40 ) 143.961538461538 4.63306380216355 31.0726432030379 Trimmed Mean ( 35 / 40 ) 143.8 4.60221774400835 31.2458053918057 Trimmed Mean ( 36 / 40 ) 143.645833333333 4.56255667246774 31.4836271952848 Trimmed Mean ( 37 / 40 ) 143.5 4.51179345640253 31.8055339604174 Trimmed Mean ( 38 / 40 ) 143.363636363636 4.44690201556509 32.2389915185523 Trimmed Mean ( 39 / 40 ) 143.214285714286 4.36974814550585 32.7740366138898 Trimmed Mean ( 40 / 40 ) 143.1 4.29143452197633 33.345493043687 Median 139 Midrange 171.5 Midmean - Weighted Average at Xnp 142.983870967742 Midmean - Weighted Average at X(n+1)p 142.983870967742 Midmean - Empirical Distribution Function 142.983870967742 Midmean - Empirical Distribution Function - Averaging 142.983870967742 Midmean - Empirical Distribution Function - Interpolation 142.983870967742 Midmean - Closest Observation 142.983870967742 Midmean - True Basic - Statistics Graphics Toolkit 142.983870967742 Midmean - MS Excel (old versions) 143.984126984127 Number of observations 120

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Aug/15/t1281872126ggaddedk352pzon/1d9tp1281872153.png (open in new window) http://www.freestatistics.org/blog/date/2010/Aug/15/t1281872126ggaddedk352pzon/1d9tp1281872153.ps (open in new window) http://www.freestatistics.org/blog/date/2010/Aug/15/t1281872126ggaddedk352pzon/25isa1281872153.png (open in new window) http://www.freestatistics.org/blog/date/2010/Aug/15/t1281872126ggaddedk352pzon/25isa1281872153.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 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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