Aantal bezoekers

*Unverified author*

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

Title produced by software: Central Tendency

Date of computation: Mon, 16 Aug 2010 08:41:24 +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/16/t1281948063cthiojn3lek66i6.htm/, Retrieved Mon, 16 Aug 2010 10:41:03 +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/16/t1281948063cthiojn3lek66i6.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 «

556 555 554 552 572 571 556 546 547 547 548 550 555 549 555 550 566 573 543 535 542 541 535 536 548 546 548 548 561 563 527 527 541 534 522 527 539 533 532 519 538 542 503 502 522 511 492 500 509 511 505 493 518 518 474 471 483 461 439 446 461 449 441 424 447 448 404 403 411 386 359 370 385 369 368 352 378 383 334 323 330 303 275 284 301 281 284 272 297 300 240 236 247 218 192 201 223 197 195 175 197 204 142 142 151 127 100 114 139 112 123 108 132 140 76 71 81 57 38 46

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 3 seconds R Server 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 Central Tendency - Ungrouped Data Measure Value S.E. Value/S.E. Arithmetic Mean 391.941666666667 15.0293377703142 26.0784388944153 Geometric Mean 339.229437975558 Harmonic Mean 262.318390830732 Quadratic Mean 424.850689458465 Winsorized Mean ( 1 / 40 ) 392 15.0154448963117 26.1064525697995 Winsorized Mean ( 2 / 40 ) 392.166666666667 14.9787820676969 26.1814789009053 Winsorized Mean ( 3 / 40 ) 392.391666666667 14.9017665555214 26.3318892565309 Winsorized Mean ( 4 / 40 ) 392.458333333333 14.8620354412055 26.4067687690495 Winsorized Mean ( 5 / 40 ) 392.583333333333 14.8169908872972 26.4954832137948 Winsorized Mean ( 6 / 40 ) 393.283333333333 14.6293811620294 26.8831148069408 Winsorized Mean ( 7 / 40 ) 393.75 14.5515660404539 27.0589432714912 Winsorized Mean ( 8 / 40 ) 393.95 14.5015446390641 27.1660716016957 Winsorized Mean ( 9 / 40 ) 394.1 14.477096757714 27.2223089059626 Winsorized Mean ( 10 / 40 ) 394.85 14.3564499115075 27.503317493798 Winsorized Mean ( 11 / 40 ) 395.125 14.2897906911613 27.6508598718943 Winsorized Mean ( 12 / 40 ) 395.425 14.1927638805353 27.8610285726170 Winsorized Mean ( 13 / 40 ) 395.966666666667 14.0553474444206 28.1719586251744 Winsorized Mean ( 14 / 40 ) 396.083333333333 14.0374428435987 28.2162027476359 Winsorized Mean ( 15 / 40 ) 396.208333333333 13.9876941506357 28.3254930417053 Winsorized Mean ( 16 / 40 ) 396.075 13.9754845503606 28.3406989269493 Winsorized Mean ( 17 / 40 ) 397.35 13.7823246220946 28.8304049494672 Winsorized Mean ( 18 / 40 ) 400.95 13.2538449048533 30.2515989041928 Winsorized Mean ( 19 / 40 ) 403.641666666667 12.8750339034844 31.3507265062368 Winsorized Mean ( 20 / 40 ) 403.975 12.7904926969751 31.5840061497818 Winsorized Mean ( 21 / 40 ) 404.325 12.7425386664772 31.7303333804032 Winsorized Mean ( 22 / 40 ) 404.141666666667 12.7253265180373 31.7588445446821 Winsorized Mean ( 23 / 40 ) 404.908333333333 12.6208444131979 32.0825073249388 Winsorized Mean ( 24 / 40 ) 404.908333333333 12.4834680360206 32.4355645534545 Winsorized Mean ( 25 / 40 ) 407.616666666667 12.0742809711823 33.7590840928355 Winsorized Mean ( 26 / 40 ) 408.7 11.9319534278777 34.2525641312945 Winsorized Mean ( 27 / 40 ) 411.4 11.5325043014163 35.6730844617571 Winsorized Mean ( 28 / 40 ) 412.333333333333 11.4136468843550 36.1263439732422 Winsorized Mean ( 29 / 40 ) 413.541666666667 11.1544535567784 37.0741304862364 Winsorized Mean ( 30 / 40 ) 419.541666666667 10.3640450977879 40.4804941225325 Winsorized Mean ( 31 / 40 ) 419.8 10.2220692758420 41.0680057698418 Winsorized Mean ( 32 / 40 ) 421.133333333333 10.0072028214677 42.0830216841322 Winsorized Mean ( 33 / 40 ) 421.958333333333 9.91040674651748 42.5772971913196 Winsorized Mean ( 34 / 40 ) 421.675 9.88329775833107 42.6654149567184 Winsorized Mean ( 35 / 40 ) 425.175 9.41643671789838 45.1524300260888 Winsorized Mean ( 36 / 40 ) 425.775 9.2848817096043 45.8568039223997 Winsorized Mean ( 37 / 40 ) 424.541666666667 9.10271988036295 46.6389905705567 Winsorized Mean ( 38 / 40 ) 425.175 9.03060205409272 47.0815785540354 Winsorized Mean ( 39 / 40 ) 431.675 8.30315118963103 51.9892978149158 Winsorized Mean ( 40 / 40 ) 432.341666666667 7.88758106079823 54.8129601881915 Trimmed Mean ( 1 / 40 ) 393.406779661017 14.9053473973441 26.3936672640798 Trimmed Mean ( 2 / 40 ) 394.862068965517 14.7808524004510 26.7144315001394 Trimmed Mean ( 3 / 40 ) 396.280701754386 14.6612979516291 27.0290326996835 Trimmed Mean ( 4 / 40 ) 397.669642857143 14.5564095374429 27.3192123259676 Trimmed Mean ( 5 / 40 ) 399.090909090909 14.4489469385183 27.6207609308194 Trimmed Mean ( 6 / 40 ) 400.537037037037 14.3376760906777 27.93598031535 Trimmed Mean ( 7 / 40 ) 401.905660377359 14.2524569739288 28.1990439341471 Trimmed Mean ( 8 / 40 ) 403.25 14.1690143978585 28.459989430242 Trimmed Mean ( 9 / 40 ) 404.617647058824 14.0805917589499 28.7358410772503 Trimmed Mean ( 10 / 40 ) 406.02 13.9813582958874 29.0400969210145 Trimmed Mean ( 11 / 40 ) 407.387755102041 13.8852457287827 29.3396143690543 Trimmed Mean ( 12 / 40 ) 408.78125 13.7826900329709 29.6590323820759 Trimmed Mean ( 13 / 40 ) 410.202127659574 13.6764469955524 29.9933255905553 Trimmed Mean ( 14 / 40 ) 411.630434782609 13.5709080566804 30.3318269539068 Trimmed Mean ( 15 / 40 ) 413.111111111111 13.4486626826303 30.7176349693615 Trimmed Mean ( 16 / 40 ) 414.647727272727 13.3112706679484 31.1501236520672 Trimmed Mean ( 17 / 40 ) 416.267441860465 13.1508185512804 31.6533484389027 Trimmed Mean ( 18 / 40 ) 417.857142857143 12.9890741727395 32.1698942742285 Trimmed Mean ( 19 / 40 ) 419.231707317073 12.8703293481951 32.5735026645504 Trimmed Mean ( 20 / 40 ) 420.4625 12.7777984840152 32.9057075462562 Trimmed Mean ( 21 / 40 ) 421.730769230769 12.6750765990657 33.2724434392654 Trimmed Mean ( 22 / 40 ) 423.039473684211 12.5557205916369 33.6929665324019 Trimmed Mean ( 23 / 40 ) 424.432432432432 12.4120464511367 34.1952017423816 Trimmed Mean ( 24 / 40 ) 425.847222222222 12.2520902966081 34.7571077190083 Trimmed Mean ( 25 / 40 ) 427.342857142857 12.0753652296875 35.3896423846648 Trimmed Mean ( 26 / 40 ) 428.735294117647 11.9184862727541 35.9722941576688 Trimmed Mean ( 27 / 40 ) 430.136363636364 11.7461075507493 36.6194811155909 Trimmed Mean ( 28 / 40 ) 431.4375 11.5921060262152 37.2182154842541 Trimmed Mean ( 29 / 40 ) 432.758064516129 11.4178297090040 37.9019547099097 Trimmed Mean ( 30 / 40 ) 434.083333333333 11.2389127202639 38.6232497873816 Trimmed Mean ( 31 / 40 ) 435.086206896552 11.1365686190419 39.0682464033506 Trimmed Mean ( 32 / 40 ) 436.142857142857 11.0216265732019 39.5715509182012 Trimmed Mean ( 33 / 40 ) 437.185185185185 10.9033962125846 40.0962394341488 Trimmed Mean ( 34 / 40 ) 438.25 10.7619544881134 40.7221569728853 Trimmed Mean ( 35 / 40 ) 439.42 10.577685021221 41.5421710060787 Trimmed Mean ( 36 / 40 ) 440.4375 10.4218174322152 42.2611030047934 Trimmed Mean ( 37 / 40 ) 441.5 10.2357595197845 43.1330961954149 Trimmed Mean ( 38 / 40 ) 442.75 10.0146892641301 44.2100586770886 Trimmed Mean ( 39 / 40 ) 444.071428571429 9.7308370816837 45.635480775575 Trimmed Mean ( 40 / 40 ) 445.025 9.5233510249066 46.7298746876092 Median 448.5 Midrange 305.5 Midmean - Weighted Average at Xnp 431.016393442623 Midmean - Weighted Average at X(n+1)p 434.083333333333 Midmean - Empirical Distribution Function 431.016393442623 Midmean - Empirical Distribution Function - Averaging 434.083333333333 Midmean - Empirical Distribution Function - Interpolation 434.083333333333 Midmean - Closest Observation 431.016393442623 Midmean - True Basic - Statistics Graphics Toolkit 434.083333333333 Midmean - MS Excel (old versions) 432.758064516129 Number of observations 120

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Aug/16/t1281948063cthiojn3lek66i6/1dqsf1281948079.png (open in new window) http://www.freestatistics.org/blog/date/2010/Aug/16/t1281948063cthiojn3lek66i6/1dqsf1281948079.ps (open in new window) http://www.freestatistics.org/blog/date/2010/Aug/16/t1281948063cthiojn3lek66i6/2oz9i1281948079.png (open in new window) http://www.freestatistics.org/blog/date/2010/Aug/16/t1281948063cthiojn3lek66i6/2oz9i1281948079.ps (open in new window)

Parameters (Session):

par1 = 0 ;

Parameters (R input):

par1 = 0 ;

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 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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