Tijdreeks 1 - stap 14

*Unverified author*

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

Title produced by software: Central Tendency

Date of computation: Fri, 13 Aug 2010 13:39:39 +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/13/t12817067597upeylqn9l2tidj.htm/, Retrieved Fri, 13 Aug 2010 15:39:22 +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/13/t12817067597upeylqn9l2tidj.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:

Reuben Vermoet

Dataseries X:

» Textbox « » Textfile « » CSV «

210 209 208 206 226 225 210 200 201 201 202 204 197 196 187 196 221 218 200 191 194 192 199 196 182 178 169 177 207 213 191 182 188 189 194 195 171 165 156 170 201 208 189 175 184 187 193 199 179 188 171 182 212 216 192 182 183 183 187 190 167 167 158 171 201 208 181 169 173 180 181 192 169 168 156 161 195 208 176 164 170 175 170 175 148 151 143 139 166 186 149 142 138 137 130 138 118 113 99 93 125 146 109 97 97 94 92 103 78 72 57 40 70 89 53 46 43 38 29 34

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 162.95 4.35587516572545 37.4092447098082 Geometric Mean 152.013926574878 Harmonic Mean 134.275038848840 Quadratic Mean 169.736756969923 Winsorized Mean ( 1 / 40 ) 162.983333333333 4.34428668453011 37.5167076136372 Winsorized Mean ( 2 / 40 ) 162.983333333333 4.32010451121982 37.7267107566603 Winsorized Mean ( 3 / 40 ) 162.958333333333 4.29975238413709 37.8994692658417 Winsorized Mean ( 4 / 40 ) 162.991666666667 4.26886152131244 38.1815305680274 Winsorized Mean ( 5 / 40 ) 162.991666666667 4.22682337352758 38.5612674727496 Winsorized Mean ( 6 / 40 ) 163.291666666667 4.14198960015664 39.4234854333027 Winsorized Mean ( 7 / 40 ) 163.408333333333 4.07893914081498 40.0614786570912 Winsorized Mean ( 8 / 40 ) 164.275 3.89566236012435 42.1686955423817 Winsorized Mean ( 9 / 40 ) 164.35 3.85797674874247 42.6000493791391 Winsorized Mean ( 10 / 40 ) 164.766666666667 3.75097995288024 43.9262989236049 Winsorized Mean ( 11 / 40 ) 165.775 3.56147418765822 46.5467363415043 Winsorized Mean ( 12 / 40 ) 166.075 3.5076779030733 47.3461374131562 Winsorized Mean ( 13 / 40 ) 166.183333333333 3.48851624116796 47.6372537333222 Winsorized Mean ( 14 / 40 ) 166.183333333333 3.45632986752247 48.0808660350625 Winsorized Mean ( 15 / 40 ) 166.433333333333 3.3786844881129 49.2598033106937 Winsorized Mean ( 16 / 40 ) 166.166666666667 3.3529186527656 49.5588124482551 Winsorized Mean ( 17 / 40 ) 166.166666666667 3.27750873256861 50.6990767150269 Winsorized Mean ( 18 / 40 ) 166.616666666667 3.16135150275895 52.7042521280086 Winsorized Mean ( 19 / 40 ) 167.566666666667 3.00312007064822 55.7975248157486 Winsorized Mean ( 20 / 40 ) 168.233333333333 2.89502938581365 58.1110969573289 Winsorized Mean ( 21 / 40 ) 169.108333333333 2.75667755189408 61.3449814676879 Winsorized Mean ( 22 / 40 ) 170.208333333333 2.54274096779802 66.9389196496613 Winsorized Mean ( 23 / 40 ) 171.166666666667 2.40206882510116 71.2580192865448 Winsorized Mean ( 24 / 40 ) 172.366666666667 2.18547962588186 78.8690338840908 Winsorized Mean ( 25 / 40 ) 172.575 2.15728400998104 79.9964210560836 Winsorized Mean ( 26 / 40 ) 172.141666666667 2.11355820075385 81.4463810862972 Winsorized Mean ( 27 / 40 ) 172.141666666667 2.06101929561114 83.5225885721866 Winsorized Mean ( 28 / 40 ) 172.841666666667 1.96759446732852 87.844151595598 Winsorized Mean ( 29 / 40 ) 173.083333333333 1.93589791749603 89.4072625261185 Winsorized Mean ( 30 / 40 ) 173.583333333333 1.81414390661607 95.6833317909816 Winsorized Mean ( 31 / 40 ) 174.1 1.74872502575055 99.55824811581 Winsorized Mean ( 32 / 40 ) 174.1 1.68875005572177 103.094001039479 Winsorized Mean ( 33 / 40 ) 174.65 1.62066703077772 107.764270317876 Winsorized Mean ( 34 / 40 ) 175.783333333333 1.42212328597871 123.606254863030 Winsorized Mean ( 35 / 40 ) 175.491666666667 1.39275817240373 126.002970324553 Winsorized Mean ( 36 / 40 ) 176.091666666667 1.32298130314758 133.102158169369 Winsorized Mean ( 37 / 40 ) 177.016666666667 1.21866801359419 145.254215825847 Winsorized Mean ( 38 / 40 ) 177.65 1.08301438959380 164.032908248459 Winsorized Mean ( 39 / 40 ) 177.975 1.04890649341720 169.676707234579 Winsorized Mean ( 40 / 40 ) 177.975 0.979871833212798 181.630896988289 Trimmed Mean ( 1 / 40 ) 163.550847457627 4.24669512081701 38.5125003808049 Trimmed Mean ( 2 / 40 ) 164.137931034483 4.13765928642914 39.6692718447913 Trimmed Mean ( 3 / 40 ) 164.745614035088 4.02982999567663 40.8815295463664 Trimmed Mean ( 4 / 40 ) 165.383928571429 3.91712007977644 42.220796198024 Trimmed Mean ( 5 / 40 ) 166.036363636364 3.80035394674693 43.6897104751227 Trimmed Mean ( 6 / 40 ) 166.712962962963 3.68009555720080 45.3012592666942 Trimmed Mean ( 7 / 40 ) 167.358490566038 3.56531127765907 46.9407795091381 Trimmed Mean ( 8 / 40 ) 168.009615384615 3.44915309258221 48.7103966901148 Trimmed Mean ( 9 / 40 ) 168.558823529412 3.3561220679189 50.2242827043337 Trimmed Mean ( 10 / 40 ) 169.12 3.25741671211462 51.9184418042149 Trimmed Mean ( 11 / 40 ) 169.653061224490 3.16467530658204 53.6083625614411 Trimmed Mean ( 12 / 40 ) 170.09375 3.09233198940144 55.0050093531271 Trimmed Mean ( 13 / 40 ) 170.521276595745 3.01861564808876 56.4898935390169 Trimmed Mean ( 14 / 40 ) 170.956521739130 2.93718734980009 58.2041597553408 Trimmed Mean ( 15 / 40 ) 171.411111111111 2.84834728540750 60.1791473916385 Trimmed Mean ( 16 / 40 ) 171.863636363636 2.75796470898254 62.3153863440985 Trimmed Mean ( 17 / 40 ) 172.360465116279 2.65622222251884 64.8893242647572 Trimmed Mean ( 18 / 40 ) 172.880952380952 2.54880107269613 67.8283426011268 Trimmed Mean ( 19 / 40 ) 173.390243902439 2.44165621331200 71.01337320017 Trimmed Mean ( 20 / 40 ) 173.85 2.34224413649319 74.2236888509362 Trimmed Mean ( 21 / 40 ) 174.282051282051 2.24304879069130 77.698733975527 Trimmed Mean ( 22 / 40 ) 174.671052631579 2.14904206794274 81.2785637085224 Trimmed Mean ( 23 / 40 ) 175 2.07272443840383 84.4299400140063 Trimmed Mean ( 24 / 40 ) 175.277777777778 2.00510130151856 87.4159214025903 Trimmed Mean ( 25 / 40 ) 175.485714285714 1.95823291038683 89.6143218484916 Trimmed Mean ( 26 / 40 ) 175.691176470588 1.90653620814503 92.1520271789264 Trimmed Mean ( 27 / 40 ) 175.939393939394 1.84995165159260 95.1048605988862 Trimmed Mean ( 28 / 40 ) 176.203125 1.78940606105470 98.4701733356954 Trimmed Mean ( 29 / 40 ) 176.435483870968 1.73199294452509 101.868477252571 Trimmed Mean ( 30 / 40 ) 176.666666666667 1.66734449493301 105.956907647789 Trimmed Mean ( 31 / 40 ) 176.879310344828 1.60931152895310 109.909925556733 Trimmed Mean ( 32 / 40 ) 177.071428571429 1.54979201429404 114.254962561598 Trimmed Mean ( 33 / 40 ) 177.277777777778 1.48611478476789 119.289424743504 Trimmed Mean ( 34 / 40 ) 177.461538461538 1.42018988874965 124.956204707089 Trimmed Mean ( 35 / 40 ) 177.58 1.37709839880816 128.952295750028 Trimmed Mean ( 36 / 40 ) 177.729166666667 1.32680346398142 133.952896183542 Trimmed Mean ( 37 / 40 ) 177.847826086957 1.27743984280469 139.222075378893 Trimmed Mean ( 38 / 40 ) 177.909090909091 1.23669159933208 143.858898212923 Trimmed Mean ( 39 / 40 ) 177.928571428571 1.21182369797041 146.827110021508 Trimmed Mean ( 40 / 40 ) 177.925 1.18504976634652 150.141373850094 Median 178.5 Midrange 127.5 Midmean - Weighted Average at Xnp 176.114754098361 Midmean - Weighted Average at X(n+1)p 176.666666666667 Midmean - Empirical Distribution Function 176.114754098361 Midmean - Empirical Distribution Function - Averaging 176.666666666667 Midmean - Empirical Distribution Function - Interpolation 176.666666666667 Midmean - Closest Observation 176.114754098361 Midmean - True Basic - Statistics Graphics Toolkit 176.666666666667 Midmean - MS Excel (old versions) 177.046875 Number of observations 120

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Aug/13/t12817067597upeylqn9l2tidj/1d0x81281706777.png (open in new window) http://www.freestatistics.org/blog/date/2010/Aug/13/t12817067597upeylqn9l2tidj/1d0x81281706777.ps (open in new window) http://www.freestatistics.org/blog/date/2010/Aug/13/t12817067597upeylqn9l2tidj/2nreb1281706777.png (open in new window) http://www.freestatistics.org/blog/date/2010/Aug/13/t12817067597upeylqn9l2tidj/2nreb1281706777.ps (open in new window)

Parameters (Session):

par1 = 0.01 ; par2 = 0.99 ; par3 = 0.01 ;

Parameters (R input):

par1 = 0.01 ; par2 = 0.99 ; par3 = 0.01 ;

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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• 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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