*Unverified author*

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

Title produced by software: Central Tendency

Date of computation: Wed, 28 Oct 2009 12:00:10 -0600

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2009/Oct/28/t1256752871ct4lsj5864fxzap.htm/, Retrieved Wed, 28 Oct 2009 19:01:13 +0100

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/2009/Oct/28/t1256752871ct4lsj5864fxzap.htm/}, year = {2009}, } @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 = {2009}, 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:

KDGP1W52

Dataseries X:

» Textbox « » Textfile « » CSV «

1,61 1,58 1,69 1,78 1,76 1,83 1,8 1,57 1,45 1,4 1,55 1,58 1,58 1,59 1,8 1,99 2,06 2,06 2,08 2 1,85 1,77 1,7 1,66 1,67 1,73 1,91 2,02 2,07 2,15 2,1 1,68 1,68 1,65 1,72 1,73 1,76 1,84 1,99 2,05 2,12 2,13 2,08 1,88 1,81 1,81 1,88 1,87 1,87 1,9 2,01 2,05 2,16 2,18 2,15 2,12 2,04 2,04 2,06 1,93 1,86 1,94 2,35 2,46 2,59 2,66 2,41 2,18 2,13 2,11 2,12 2,16 2,07 2,2 2,29 2,32 2,37 2,38 2,38 2,28 2,22 2,25 2,3 2,3 2,23 2,27 2,3 2,32 2,41 2,43 2,45 2,47 2,46 2,5 2,46 2,43 2,37 2,45 2,53 2,56 2,62 2,67 2,62 2,6 2,53 2,49 2,48 2,44

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 'George Udny Yule' @ 72.249.76.132 Central Tendency - Ungrouped Data Measure Value S.E. Value/S.E. Arithmetic Mean 2.08333333333333 0.0304076947322049 68.5133599136953 Geometric Mean 2.05899008517345 Harmonic Mean 2.03415321495609 Quadratic Mean 2.10694398666955 Winsorized Mean ( 1 / 36 ) 2.08370370370370 0.0302972445711069 68.7753534422348 Winsorized Mean ( 2 / 36 ) 2.08481481481481 0.0298329494285681 69.8829601078059 Winsorized Mean ( 3 / 36 ) 2.08537037037037 0.0297414222375189 70.1166996559993 Winsorized Mean ( 4 / 36 ) 2.085 0.0295593283766901 70.5361087176862 Winsorized Mean ( 5 / 36 ) 2.08453703703704 0.0294845484814749 70.6993033434699 Winsorized Mean ( 6 / 36 ) 2.08287037037037 0.0292238501670547 71.2729622710178 Winsorized Mean ( 7 / 36 ) 2.08157407407407 0.0288303670876335 72.2007481814875 Winsorized Mean ( 8 / 36 ) 2.08305555555556 0.0285978000874127 72.8397131663429 Winsorized Mean ( 9 / 36 ) 2.08388888888889 0.027738341684391 75.126657267386 Winsorized Mean ( 10 / 36 ) 2.08388888888889 0.0274750377071926 75.8466252566182 Winsorized Mean ( 11 / 36 ) 2.08388888888889 0.0271894604391262 76.6432601174435 Winsorized Mean ( 12 / 36 ) 2.08388888888889 0.0268821876599376 77.5193193072787 Winsorized Mean ( 13 / 36 ) 2.08268518518519 0.0267219722706475 77.9390519566136 Winsorized Mean ( 14 / 36 ) 2.08398148148148 0.0265407658173208 78.5200207042048 Winsorized Mean ( 15 / 36 ) 2.08537037037037 0.0263494981492233 79.1426978442032 Winsorized Mean ( 16 / 36 ) 2.08685185185185 0.0257536617378322 81.0312674405543 Winsorized Mean ( 17 / 36 ) 2.08842592592593 0.0255456757857487 81.7526200301581 Winsorized Mean ( 18 / 36 ) 2.08675925925926 0.02532681117322 82.3932884794337 Winsorized Mean ( 19 / 36 ) 2.09027777777778 0.0244165061478970 85.6092089964238 Winsorized Mean ( 20 / 36 ) 2.09027777777778 0.0244165061478970 85.6092089964238 Winsorized Mean ( 21 / 36 ) 2.08833333333333 0.0236715218865425 88.2213380002649 Winsorized Mean ( 22 / 36 ) 2.09037037037037 0.0234173409569204 89.2659151274225 Winsorized Mean ( 23 / 36 ) 2.08824074074074 0.0220915793901960 94.5265480505877 Winsorized Mean ( 24 / 36 ) 2.08824074074074 0.0220915793901960 94.5265480505877 Winsorized Mean ( 25 / 36 ) 2.08824074074074 0.0215261554155187 97.0094613009845 Winsorized Mean ( 26 / 36 ) 2.08824074074074 0.0215261554155187 97.0094613009845 Winsorized Mean ( 27 / 36 ) 2.08824074074074 0.0203201396957166 102.767046487428 Winsorized Mean ( 28 / 36 ) 2.08305555555556 0.0190921769508424 109.105188000242 Winsorized Mean ( 29 / 36 ) 2.08574074074074 0.0187748698355923 111.092154513195 Winsorized Mean ( 30 / 36 ) 2.08296296296296 0.0178088671851933 116.962125737834 Winsorized Mean ( 31 / 36 ) 2.08583333333333 0.0174752581860000 119.359228409247 Winsorized Mean ( 32 / 36 ) 2.08583333333333 0.0174752581860000 119.359228409247 Winsorized Mean ( 33 / 36 ) 2.08583333333333 0.0167748952225207 124.342555089885 Winsorized Mean ( 34 / 36 ) 2.08268518518519 0.0164190360111520 126.845765108902 Winsorized Mean ( 35 / 36 ) 2.08592592592593 0.0153131820703621 136.217666344027 Winsorized Mean ( 36 / 36 ) 2.08259259259259 0.0141924482100659 146.739488618710 Trimmed Mean ( 1 / 36 ) 2.08424528301887 0.0297847769848906 69.9768638212795 Trimmed Mean ( 2 / 36 ) 2.08480769230769 0.029210414820806 71.3720672950774 Trimmed Mean ( 3 / 36 ) 2.08480392156863 0.0288381536651925 72.2932523965629 Trimmed Mean ( 4 / 36 ) 2.0846 0.0284553238348372 73.2586988677272 Trimmed Mean ( 5 / 36 ) 2.08448979591837 0.0280808855629439 74.2316260377879 Trimmed Mean ( 6 / 36 ) 2.08447916666667 0.0276764157119262 75.3160809681158 Trimmed Mean ( 7 / 36 ) 2.08478723404255 0.027278665131253 76.4255590957793 Trimmed Mean ( 8 / 36 ) 2.08532608695652 0.0269089398461635 77.4956612515462 Trimmed Mean ( 9 / 36 ) 2.08566666666667 0.0265315161329805 78.6109114990996 Trimmed Mean ( 10 / 36 ) 2.08590909090909 0.026253644004242 79.4521739752415 Trimmed Mean ( 11 / 36 ) 2.08616279069767 0.0259754533209693 80.3128540210527 Trimmed Mean ( 12 / 36 ) 2.08642857142857 0.0256971878517203 81.1928754020801 Trimmed Mean ( 13 / 36 ) 2.08670731707317 0.0254191332658021 82.0919932734507 Trimmed Mean ( 14 / 36 ) 2.087125 0.0251163077728244 83.0984004049452 Trimmed Mean ( 15 / 36 ) 2.08743589743590 0.0247870960337177 84.214620970378 Trimmed Mean ( 16 / 36 ) 2.08763157894737 0.0244273849926838 85.462753363597 Trimmed Mean ( 17 / 36 ) 2.08770270270270 0.0240891434198758 86.6657093742967 Trimmed Mean ( 18 / 36 ) 2.08763888888889 0.0237170767234944 88.0226055355654 Trimmed Mean ( 19 / 36 ) 2.08771428571429 0.0233056666161081 89.5796854946567 Trimmed Mean ( 20 / 36 ) 2.0875 0.0229462621836363 90.9734223070399 Trimmed Mean ( 21 / 36 ) 2.08727272727273 0.0225129286394033 92.7144024975709 Trimmed Mean ( 22 / 36 ) 2.0871875 0.0221012604121474 94.437487323249 Trimmed Mean ( 23 / 36 ) 2.08693548387097 0.0216390620482679 96.4429733236988 Trimmed Mean ( 24 / 36 ) 2.08683333333333 0.0212776794360794 98.076171304414 Trimmed Mean ( 25 / 36 ) 2.08672413793103 0.0208302968352657 100.177359661923 Trimmed Mean ( 26 / 36 ) 2.08660714285714 0.0203672081519173 102.449345403323 Trimmed Mean ( 27 / 36 ) 2.08648148148148 0.0197895238847231 105.433637192868 Trimmed Mean ( 28 / 36 ) 2.08634615384615 0.0192781279604287 108.22348301291 Trimmed Mean ( 29 / 36 ) 2.0866 0.0188476382973505 110.708830840271 Trimmed Mean ( 30 / 36 ) 2.08666666666667 0.0183526655003917 113.698289037205 Trimmed Mean ( 31 / 36 ) 2.08695652173913 0.0178962915901035 116.613909157202 Trimmed Mean ( 32 / 36 ) 2.08704545454545 0.0173649410642951 120.187304225105 Trimmed Mean ( 33 / 36 ) 2.08714285714286 0.0166618542911281 125.264740687007 Trimmed Mean ( 34 / 36 ) 2.08725 0.0158922150753128 131.337890288331 Trimmed Mean ( 35 / 36 ) 2.08763157894737 0.0149414895377084 139.720445788134 Trimmed Mean ( 36 / 36 ) 2.08777777777778 0.0139563441289690 149.593457891612 Median 2.08 Midrange 2.035 Midmean - Weighted Average at Xnp 2.07660714285714 Midmean - Weighted Average at X(n+1)p 2.08648148148148 Midmean - Empirical Distribution Function 2.07660714285714 Midmean - Empirical Distribution Function - Averaging 2.08648148148148 Midmean - Empirical Distribution Function - Interpolation 2.08648148148148 Midmean - Closest Observation 2.07660714285714 Midmean - True Basic - Statistics Graphics Toolkit 2.08648148148148 Midmean - MS Excel (old versions) 2.08672413793103 Number of observations 108

Charts produced by software:

http://www.freestatistics.org/blog/date/2009/Oct/28/t1256752871ct4lsj5864fxzap/1j4sz1256752807.png (open in new window) http://www.freestatistics.org/blog/date/2009/Oct/28/t1256752871ct4lsj5864fxzap/1j4sz1256752807.ps (open in new window) http://www.freestatistics.org/blog/date/2009/Oct/28/t1256752871ct4lsj5864fxzap/28umo1256752807.png (open in new window) http://www.freestatistics.org/blog/date/2009/Oct/28/t1256752871ct4lsj5864fxzap/28umo1256752807.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