*Unverified author*

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

Title produced by software: Central Tendency

Date of computation: Thu, 05 Aug 2010 12:16:15 +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/05/t1281010540h6dmbw2v615n5oe.htm/, Retrieved Thu, 05 Aug 2010 14:15:40 +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/05/t1281010540h6dmbw2v615n5oe.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:

Dataseries X:

» Textbox « » Textfile « » CSV «

390 389 388 386 406 405 390 380 381 381 382 384 394 393 388 381 399 396 378 368 369 373 374 379 385 385 395 387 400 390 365 350 365 374 367 375 382 380 378 363 375 366 341 326 338 345 336 342 347 360 360 334 347 336 305 289 303 308 294 299 306 313 321 287 296 283 248 235 241 244 237 241 251 259 264 229 237 228 197 182 182 176 172 175 185 195 206 175 185 174 140 130 133 130 131 136 149 155 161 131 145 134 93 87 86 80 79 91 108 105 112 78 87 74 32 25 26 25 22 36

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 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 Central Tendency - Ungrouped Data Measure Value S.E. Value/S.E. Arithmetic Mean 264.925 10.7621806602113 24.6162937014662 Geometric Mean 224.297110616496 Harmonic Mean 161.050647188106 Quadratic Mean 289.772971479398 Winsorized Mean ( 1 / 40 ) 264.941666666667 10.7565516211181 24.6307251616320 Winsorized Mean ( 2 / 40 ) 264.858333333333 10.7475897619393 24.6435097728871 Winsorized Mean ( 3 / 40 ) 264.858333333333 10.7402766646768 24.6602896370831 Winsorized Mean ( 4 / 40 ) 264.958333333333 10.6928822358086 24.7789443005399 Winsorized Mean ( 5 / 40 ) 265.083333333333 10.6582944866058 24.8710836115911 Winsorized Mean ( 6 / 40 ) 266.933333333333 10.3321432404048 25.835233515682 Winsorized Mean ( 7 / 40 ) 267.108333333333 10.2898048305129 25.9585422399133 Winsorized Mean ( 8 / 40 ) 266.975 10.2591658990377 26.0230707474028 Winsorized Mean ( 9 / 40 ) 267.05 10.2476399551243 26.0596587281994 Winsorized Mean ( 10 / 40 ) 267.55 10.1717936055576 26.3031290620976 Winsorized Mean ( 11 / 40 ) 267.55 10.1488215291911 26.362666761894 Winsorized Mean ( 12 / 40 ) 267.45 10.1387976154392 26.3788676078051 Winsorized Mean ( 13 / 40 ) 267.883333333333 10.0744232225956 26.5904387193607 Winsorized Mean ( 14 / 40 ) 268 10.0284399506173 26.7239970842627 Winsorized Mean ( 15 / 40 ) 269.375 9.80021767393881 27.4866343751052 Winsorized Mean ( 16 / 40 ) 269.641666666667 9.73080093370485 27.7101205238616 Winsorized Mean ( 17 / 40 ) 270.208333333333 9.65222210546856 27.9944172834817 Winsorized Mean ( 18 / 40 ) 272.758333333333 9.27641202969793 29.4034301689179 Winsorized Mean ( 19 / 40 ) 272.441666666667 9.244688048794 29.4700767866589 Winsorized Mean ( 20 / 40 ) 272.608333333333 9.22314631716649 29.5569780592057 Winsorized Mean ( 21 / 40 ) 272.433333333333 9.20575369141916 29.5938108345516 Winsorized Mean ( 22 / 40 ) 272.8 9.1585673411455 29.7863180821336 Winsorized Mean ( 23 / 40 ) 272.991666666667 9.13402001012067 29.8873515017688 Winsorized Mean ( 24 / 40 ) 273.191666666667 9.0631637848923 30.1430795195447 Winsorized Mean ( 25 / 40 ) 274.025 8.95777100703997 30.5907574311335 Winsorized Mean ( 26 / 40 ) 274.891666666667 8.80094052009681 31.2343511513293 Winsorized Mean ( 27 / 40 ) 275.566666666667 8.66755059056263 31.7929112483875 Winsorized Mean ( 28 / 40 ) 276.966666666667 8.49720610973602 32.5950274819532 Winsorized Mean ( 29 / 40 ) 277.691666666667 8.2514305340959 33.6537604624084 Winsorized Mean ( 30 / 40 ) 280.441666666667 7.9299082462904 35.3650582020110 Winsorized Mean ( 31 / 40 ) 280.7 7.8448416565439 35.781474284551 Winsorized Mean ( 32 / 40 ) 280.966666666667 7.81440827301272 35.9549510149083 Winsorized Mean ( 33 / 40 ) 280.691666666667 7.78695486587022 36.0463970193178 Winsorized Mean ( 34 / 40 ) 279.841666666667 7.64261232995349 36.6159703757170 Winsorized Mean ( 35 / 40 ) 281.3 7.41559980366924 37.9335465029832 Winsorized Mean ( 36 / 40 ) 281 7.38618590998891 38.043992315436 Winsorized Mean ( 37 / 40 ) 281.616666666667 7.25215300141475 38.832146344917 Winsorized Mean ( 38 / 40 ) 281.3 7.22124937784528 38.9544779969829 Winsorized Mean ( 39 / 40 ) 284.55 6.8608095209613 41.474697574774 Winsorized Mean ( 40 / 40 ) 284.55 6.72222837619615 42.3297133146518 Trimmed Mean ( 1 / 40 ) 265.788135593220 10.6807670526018 24.8847422927808 Trimmed Mean ( 2 / 40 ) 266.663793103448 10.5951952560380 25.1683698751546 Trimmed Mean ( 3 / 40 ) 267.614035087719 10.5036978190207 25.4780782633624 Trimmed Mean ( 4 / 40 ) 268.598214285714 10.4032780868324 25.818613329743 Trimmed Mean ( 5 / 40 ) 269.590909090909 10.3046771525575 26.1619947039293 Trimmed Mean ( 6 / 40 ) 270.592592592593 10.2020691424147 26.5233051075506 Trimmed Mean ( 7 / 40 ) 271.283018867925 10.1597549573652 26.7017285364014 Trimmed Mean ( 8 / 40 ) 271.971153846154 10.1179697352224 26.8800125878391 Trimmed Mean ( 9 / 40 ) 272.705882352941 10.0734979884360 27.0716172938137 Trimmed Mean ( 10 / 40 ) 273.46 10.0224437028989 27.2847628888057 Trimmed Mean ( 11 / 40 ) 274.183673469388 9.9740600540327 27.4896754164349 Trimmed Mean ( 12 / 40 ) 274.9375 9.91963112663956 27.7165044233998 Trimmed Mean ( 13 / 40 ) 275.734042553192 9.85618591121948 27.9757347352101 Trimmed Mean ( 14 / 40 ) 276.521739130435 9.79025713641628 28.2445839039173 Trimmed Mean ( 15 / 40 ) 277.333333333333 9.71827885071347 28.5372891222372 Trimmed Mean ( 16 / 40 ) 278.056818181818 9.66355872759884 28.7737495077974 Trimmed Mean ( 17 / 40 ) 278.790697674419 9.60611575998715 29.0222088344677 Trimmed Mean ( 18 / 40 ) 279.511904761905 9.54655371891318 29.2788280453656 Trimmed Mean ( 19 / 40 ) 280.060975609756 9.52111945183297 29.4147108464058 Trimmed Mean ( 20 / 40 ) 280.6625 9.48991709674877 29.5748105213853 Trimmed Mean ( 21 / 40 ) 281.282051282051 9.4510657160342 29.7619400534738 Trimmed Mean ( 22 / 40 ) 281.947368421053 9.40240534243517 29.9867276672875 Trimmed Mean ( 23 / 40 ) 282.621621621622 9.34626782277265 30.2389816963087 Trimmed Mean ( 24 / 40 ) 283.319444444444 9.27831761546406 30.5356483994727 Trimmed Mean ( 25 / 40 ) 284.042857142857 9.2020214656093 30.8674412686832 Trimmed Mean ( 26 / 40 ) 284.75 9.12070012465205 31.2201910059907 Trimmed Mean ( 27 / 40 ) 285.439393939394 9.0396208634906 31.5764785105349 Trimmed Mean ( 28 / 40 ) 286.125 8.95512124030554 31.9509912062606 Trimmed Mean ( 29 / 40 ) 286.758064516129 8.87189769655656 32.3220661829124 Trimmed Mean ( 30 / 40 ) 287.383333333333 8.79872524365723 32.6619283333686 Trimmed Mean ( 31 / 40 ) 287.862068965517 8.74895027065488 32.9024694460825 Trimmed Mean ( 32 / 40 ) 288.357142857143 8.69125656224678 33.1778426734879 Trimmed Mean ( 33 / 40 ) 288.870370370370 8.61592330391602 33.5275002087212 Trimmed Mean ( 34 / 40 ) 289.442307692308 8.51750099050961 33.9820691555904 Trimmed Mean ( 35 / 40 ) 290.12 8.40736508991384 34.507838888554 Trimmed Mean ( 36 / 40 ) 290.75 8.29960372462539 35.0317930405916 Trimmed Mean ( 37 / 40 ) 291.456521739130 8.1571939454988 35.7299978015060 Trimmed Mean ( 38 / 40 ) 292.181818181818 7.99129234926951 36.5625239838118 Trimmed Mean ( 39 / 40 ) 293 7.77163907961119 37.7011846533999 Trimmed Mean ( 40 / 40 ) 293.65 7.56175854597939 38.8335594444674 Median 301 Midrange 214 Midmean - Weighted Average at Xnp 286.758064516129 Midmean - Weighted Average at X(n+1)p 288.819672131148 Midmean - Empirical Distribution Function 286.758064516129 Midmean - Empirical Distribution Function - Averaging 288.819672131148 Midmean - Empirical Distribution Function - Interpolation 288.819672131148 Midmean - Closest Observation 286.758064516129 Midmean - True Basic - Statistics Graphics Toolkit 288.819672131148 Midmean - MS Excel (old versions) 286.758064516129 Number of observations 120

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Aug/05/t1281010540h6dmbw2v615n5oe/1abfg1281010571.png (open in new window) http://www.freestatistics.org/blog/date/2010/Aug/05/t1281010540h6dmbw2v615n5oe/1abfg1281010571.ps (open in new window) http://www.freestatistics.org/blog/date/2010/Aug/05/t1281010540h6dmbw2v615n5oe/2k2w11281010571.png (open in new window) http://www.freestatistics.org/blog/date/2010/Aug/05/t1281010540h6dmbw2v615n5oe/2k2w11281010571.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