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: Sun, 15 Aug 2010 13:10:19 +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/15/t1281877859zzu6k1hc7abbms9.htm/, Retrieved Sun, 15 Aug 2010 15:11:02 +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/t1281877859zzu6k1hc7abbms9.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:

Magali De Reu

Dataseries X:

» Textbox « » Textfile « » CSV «

333 332 331 329 349 348 333 323 324 324 325 327 329 333 329 333 355 358 338 326 320 322 322 324 326 330 331 333 364 363 341 327 313 321 312 312 312 314 312 319 356 351 329 313 298 303 278 275 276 276 273 287 320 313 281 266 258 259 237 231 237 236 229 243 271 262 227 208 212 222 200 193 204 203 190 209 240 234 210 195 202 204 180 169 178 181 163 174 194 187 160 143 151 154 141 127 134 138 120 129 151 152 124 99 104 109 96 87 94 89 63 76 100 104 80 55 60 71 62 61

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 237.233333333333 8.39303043307999 28.2655156829064 Geometric Mean 214.169787983089 Harmonic Mean 185.668751880872 Quadratic Mean 254.287960129194 Winsorized Mean ( 1 / 40 ) 237.266666666667 8.38447389092707 28.2983368728019 Winsorized Mean ( 2 / 40 ) 237.2 8.37121585565447 28.3351909794298 Winsorized Mean ( 3 / 40 ) 237.175 8.36078667659573 28.367545922912 Winsorized Mean ( 4 / 40 ) 237.175 8.35096450676671 28.4009110334285 Winsorized Mean ( 5 / 40 ) 237.341666666667 8.27409050265497 28.6849251395678 Winsorized Mean ( 6 / 40 ) 237.491666666667 8.22086567641477 28.8888878634786 Winsorized Mean ( 7 / 40 ) 237.666666666667 8.1760678752703 29.068577987901 Winsorized Mean ( 8 / 40 ) 237.666666666667 8.04990851361043 29.5241450588948 Winsorized Mean ( 9 / 40 ) 237.591666666667 8.00241118979817 29.6900098022405 Winsorized Mean ( 10 / 40 ) 237.591666666667 7.8949288392751 30.0942125639833 Winsorized Mean ( 11 / 40 ) 237.775 7.86703634505026 30.2242152662231 Winsorized Mean ( 12 / 40 ) 238.075 7.82190741726452 30.4369493653838 Winsorized Mean ( 13 / 40 ) 238.183333333333 7.80575618364461 30.5138064435575 Winsorized Mean ( 14 / 40 ) 238.65 7.7369176651935 30.8456171213542 Winsorized Mean ( 15 / 40 ) 238.525 7.72415689832333 30.8803929205239 Winsorized Mean ( 16 / 40 ) 239.058333333333 7.61397336827808 31.3973167189311 Winsorized Mean ( 17 / 40 ) 240.616666666667 7.39526481225142 32.5365856092195 Winsorized Mean ( 18 / 40 ) 241.066666666667 7.29832233257855 33.0304220177538 Winsorized Mean ( 19 / 40 ) 241.383333333333 7.21850042363461 33.4395399552797 Winsorized Mean ( 20 / 40 ) 241.716666666667 7.17430232930224 33.6920101177525 Winsorized Mean ( 21 / 40 ) 242.591666666667 7.05998206480504 34.3615131653122 Winsorized Mean ( 22 / 40 ) 243.325 6.9659954627544 34.9303988641686 Winsorized Mean ( 23 / 40 ) 243.516666666667 6.85389728766624 35.5296638461275 Winsorized Mean ( 24 / 40 ) 243.916666666667 6.80382969408179 35.8499077187123 Winsorized Mean ( 25 / 40 ) 245.375 6.57801770115821 37.3022711624501 Winsorized Mean ( 26 / 40 ) 245.375 6.57801770115821 37.3022711624501 Winsorized Mean ( 27 / 40 ) 245.375 6.52781231987206 37.5891627970103 Winsorized Mean ( 28 / 40 ) 245.608333333333 6.44802855495886 38.0904537316988 Winsorized Mean ( 29 / 40 ) 247.058333333333 6.27694523102122 39.3596445787593 Winsorized Mean ( 30 / 40 ) 247.808333333333 6.19006043233255 40.0332655944610 Winsorized Mean ( 31 / 40 ) 249.1 5.98690681581804 41.6074623613402 Winsorized Mean ( 32 / 40 ) 250.166666666667 5.81081688782465 43.0518929603234 Winsorized Mean ( 33 / 40 ) 251.266666666667 5.69071844121791 44.1537688539888 Winsorized Mean ( 34 / 40 ) 251.55 5.60008065668206 44.9189958897911 Winsorized Mean ( 35 / 40 ) 251.55 5.53846809610208 45.4186962234266 Winsorized Mean ( 36 / 40 ) 253.35 5.34825883339799 47.3705570152885 Winsorized Mean ( 37 / 40 ) 253.966666666667 5.22012553018479 48.6514481688482 Winsorized Mean ( 38 / 40 ) 253.333333333333 4.95831832730822 51.0925916026983 Winsorized Mean ( 39 / 40 ) 253.333333333333 4.89177457064884 51.787614019125 Winsorized Mean ( 40 / 40 ) 253.666666666667 4.85787260404815 52.2176449121539 Trimmed Mean ( 1 / 40 ) 237.703389830508 8.32407403299257 28.5561359603925 Trimmed Mean ( 2 / 40 ) 238.155172413793 8.25620118990552 28.8456115513482 Trimmed Mean ( 3 / 40 ) 238.657894736842 8.1874847118672 29.1491102744807 Trimmed Mean ( 4 / 40 ) 239.1875 8.11424549362562 29.4774788596057 Trimmed Mean ( 5 / 40 ) 239.736363636364 8.03478340295482 29.8373150355490 Trimmed Mean ( 6 / 40 ) 240.268518518519 7.96520868580077 30.164748721127 Trimmed Mean ( 7 / 40 ) 240.792452830189 7.8983287435889 30.4865067848234 Trimmed Mean ( 8 / 40 ) 241.307692307692 7.83127093797266 30.8133499937574 Trimmed Mean ( 9 / 40 ) 241.843137254902 7.77757860800495 31.0949139113797 Trimmed Mean ( 10 / 40 ) 242.41 7.7233490275929 31.3866431691681 Trimmed Mean ( 11 / 40 ) 243 7.677145636027 31.6523889894259 Trimmed Mean ( 12 / 40 ) 243.59375 7.62704643411288 31.9381495975293 Trimmed Mean ( 13 / 40 ) 244.180851063830 7.57479237145098 32.2359794288402 Trimmed Mean ( 14 / 40 ) 244.782608695652 7.51558066421003 32.5700194878264 Trimmed Mean ( 15 / 40 ) 245.366666666667 7.45566086281916 32.9101163775156 Trimmed Mean ( 16 / 40 ) 245.988636363636 7.38661230591783 33.3019557783696 Trimmed Mean ( 17 / 40 ) 246.593023255814 7.32014400946336 33.6869087461972 Trimmed Mean ( 18 / 40 ) 247.095238095238 7.27040265369661 33.9864585037259 Trimmed Mean ( 19 / 40 ) 247.585365853659 7.22259643015358 34.2792745306959 Trimmed Mean ( 20 / 40 ) 248.075 7.1743383896436 34.5781013560922 Trimmed Mean ( 21 / 40 ) 248.564102564103 7.12094250029008 34.9060679192364 Trimmed Mean ( 22 / 40 ) 249.013157894737 7.07033569319056 35.2194250316235 Trimmed Mean ( 23 / 40 ) 249.432432432432 7.01991352419023 35.5321232338407 Trimmed Mean ( 24 / 40 ) 249.861111111111 6.97102502986198 35.8428079142987 Trimmed Mean ( 25 / 40 ) 250.285714285714 6.91618388468433 36.1884123468672 Trimmed Mean ( 26 / 40 ) 250.632352941176 6.87652623051921 36.4475237262714 Trimmed Mean ( 27 / 40 ) 251 6.82484833374008 36.7773740493438 Trimmed Mean ( 28 / 40 ) 251.390625 6.76518050429583 37.1594852259107 Trimmed Mean ( 29 / 40 ) 251.790322580645 6.69988741141477 37.5812766870774 Trimmed Mean ( 30 / 40 ) 252.116666666667 6.64095713554024 37.9639051300934 Trimmed Mean ( 31 / 40 ) 252.413793103448 6.57701521578552 38.3781677283685 Trimmed Mean ( 32 / 40 ) 252.642857142857 6.52330629714581 38.7292648290021 Trimmed Mean ( 33 / 40 ) 252.814814814815 6.47707746954772 39.0322357580923 Trimmed Mean ( 34 / 40 ) 252.923076923077 6.4310853155773 39.328210482677 Trimmed Mean ( 35 / 40 ) 253.02 6.38016633395867 39.6572732991759 Trimmed Mean ( 36 / 40 ) 253.125 6.3181479718606 40.063164257525 Trimmed Mean ( 37 / 40 ) 253.108695652174 6.26363079878187 40.4092616220926 Trimmed Mean ( 38 / 40 ) 253.045454545455 6.20679183211452 40.7691221793800 Trimmed Mean ( 39 / 40 ) 253.023809523810 6.1705802405854 41.0048649654712 Trimmed Mean ( 40 / 40 ) 253 6.1229915597709 41.3196715249868 Median 250.5 Midrange 209.5 Midmean - Weighted Average at Xnp 252.936507936508 Midmean - Weighted Average at X(n+1)p 254.435483870968 Midmean - Empirical Distribution Function 252.936507936508 Midmean - Empirical Distribution Function - Averaging 254.435483870968 Midmean - Empirical Distribution Function - Interpolation 254.435483870968 Midmean - Closest Observation 252.936507936508 Midmean - True Basic - Statistics Graphics Toolkit 254.435483870968 Midmean - MS Excel (old versions) 252.936507936508 Number of observations 120

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Aug/15/t1281877859zzu6k1hc7abbms9/1wh4s1281877817.png (open in new window) http://www.freestatistics.org/blog/date/2010/Aug/15/t1281877859zzu6k1hc7abbms9/1wh4s1281877817.ps (open in new window) http://www.freestatistics.org/blog/date/2010/Aug/15/t1281877859zzu6k1hc7abbms9/2793d1281877817.png (open in new window) http://www.freestatistics.org/blog/date/2010/Aug/15/t1281877859zzu6k1hc7abbms9/2793d1281877817.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