ct ruwe olie

*Unverified author*

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

Title produced by software: Central Tendency

Date of computation: Mon, 28 Dec 2009 06:51:26 -0700

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2009/Dec/28/t1262008337rc89tjaf619rx3l.htm/, Retrieved Mon, 28 Dec 2009 14:52:19 +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/Dec/28/t1262008337rc89tjaf619rx3l.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:

Dataseries X:

» Textbox « » Textfile « » CSV «

32,68 31,54 32,43 26,54 25,85 27,6 25,71 25,38 28,57 27,64 25,36 25,9 26,29 21,74 19,2 19,32 19,82 20,36 24,31 25,97 25,61 24,67 25,59 26,09 28,37 27,34 24,46 27,46 30,23 32,33 29,87 24,87 25,48 27,28 28,24 29,58 26,95 29,08 28,76 29,59 30,7 30,52 32,67 33,19 37,13 35,54 37,75 41,84 42,94 49,14 44,61 40,22 44,23 45,85 53,38 53,26 51,8 55,3 57,81 63,96 63,77 59,15 56,12 57,42 63,52 61,71 63,01 68,18 72,03 69,75 74,41 74,33 64,24 60,03 59,44 62,5 55,04 58,34 61,92 67,65 67,68 70,3 75,26 71,44 76,36 81,71 92,6 90,6 92,23 94,09 102,79 109,65 124,05 132,69 135,81 116,07 101,42 75,73 55,48 43,80 45,29 44,01 47,48 51,07 57,84 69,04 65,61 72,87 68,41 73,25 77,43

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 51.356036036036 2.49994745327014 20.5428461981703 Geometric Mean 45.4064366310611 Harmonic Mean 40.4019357109850 Quadratic Mean 57.6620632386402 Winsorized Mean ( 1 / 37 ) 51.329009009009 2.49133222357806 20.6030366095815 Winsorized Mean ( 2 / 37 ) 51.1823423423424 2.44607370948194 20.9242845560784 Winsorized Mean ( 3 / 37 ) 50.9812612612613 2.38842275946317 21.3451580375662 Winsorized Mean ( 4 / 37 ) 50.7996396396396 2.32742652933099 21.8265277118078 Winsorized Mean ( 5 / 37 ) 50.6063963963964 2.24649573247959 22.5268161718425 Winsorized Mean ( 6 / 37 ) 50.5404504504505 2.23013415192534 22.6625157983512 Winsorized Mean ( 7 / 37 ) 50.0914414414414 2.13742654455389 23.4353978475065 Winsorized Mean ( 8 / 37 ) 49.9984684684685 2.11599265529241 23.6288478333869 Winsorized Mean ( 9 / 37 ) 50.0081981981982 2.1062556768397 23.7427007310111 Winsorized Mean ( 10 / 37 ) 49.8631531531532 2.07960592082867 23.9772125351923 Winsorized Mean ( 11 / 37 ) 48.9920720720721 1.93187394486683 25.3598699864702 Winsorized Mean ( 12 / 37 ) 48.5412612612613 1.86224926357636 26.0659312427597 Winsorized Mean ( 13 / 37 ) 48.4182882882883 1.84452025006206 26.2498003405814 Winsorized Mean ( 14 / 37 ) 48.3514414414414 1.83223431959833 26.3893329167861 Winsorized Mean ( 15 / 37 ) 48.3068468468468 1.82152552809455 26.5199944232346 Winsorized Mean ( 16 / 37 ) 48.1915315315315 1.80438316179383 26.7080366032800 Winsorized Mean ( 17 / 37 ) 48.19 1.80156280777789 26.7489980321248 Winsorized Mean ( 18 / 37 ) 48.0343243243243 1.77652762295230 27.0383211067099 Winsorized Mean ( 19 / 37 ) 48.0035135135135 1.76432669187244 27.2078372642929 Winsorized Mean ( 20 / 37 ) 47.8972072072072 1.74005518364097 27.5262575908569 Winsorized Mean ( 21 / 37 ) 47.8631531531531 1.71743171957914 27.8690282748953 Winsorized Mean ( 22 / 37 ) 47.7026126126126 1.68230476296869 28.3555118327275 Winsorized Mean ( 23 / 37 ) 47.6010810810811 1.66709099111821 28.5533791104901 Winsorized Mean ( 24 / 37 ) 47.4735135135135 1.64580815478881 28.8451077213221 Winsorized Mean ( 25 / 37 ) 47.3631531531531 1.62551974165167 29.1372365032172 Winsorized Mean ( 26 / 37 ) 47.3186486486487 1.61815631776986 29.2423223448913 Winsorized Mean ( 27 / 37 ) 47.342972972973 1.58789927411771 29.8148464103796 Winsorized Mean ( 28 / 37 ) 47.3681981981982 1.58343648716884 29.9148078132845 Winsorized Mean ( 29 / 37 ) 46.8874774774775 1.51676013320987 30.9129152664707 Winsorized Mean ( 30 / 37 ) 46.5685585585586 1.47009900576881 31.6771580524979 Winsorized Mean ( 31 / 37 ) 46.5797297297297 1.45175304494699 32.0851606902816 Winsorized Mean ( 32 / 37 ) 46.6690990990991 1.43006701646227 32.6342042448823 Winsorized Mean ( 33 / 37 ) 46.5977477477478 1.42168263623660 32.7764766622590 Winsorized Mean ( 34 / 37 ) 46.5272972972973 1.39552617305728 33.340325818015 Winsorized Mean ( 35 / 37 ) 46.48 1.36602294022417 34.0257828996434 Winsorized Mean ( 36 / 37 ) 46.3859459459459 1.33588869203854 34.7229123372262 Winsorized Mean ( 37 / 37 ) 46.3759459459459 1.32202518421111 35.0794723881298 Trimmed Mean ( 1 / 37 ) 50.8762385321101 2.40549752900068 21.1499857799670 Trimmed Mean ( 2 / 37 ) 50.4065420560748 2.30776184148854 21.8421767575296 Trimmed Mean ( 3 / 37 ) 49.9964761904762 2.22432999741047 22.4770947875006 Trimmed Mean ( 4 / 37 ) 49.6427184466019 2.15458530341703 23.0404980335993 Trimmed Mean ( 5 / 37 ) 49.3248514851485 2.09624157124768 23.5301370613456 Trimmed Mean ( 6 / 37 ) 49.0374747474747 2.05292951931745 23.8865846518581 Trimmed Mean ( 7 / 37 ) 49.0374747474747 2.00764533496944 24.4253673162950 Trimmed Mean ( 8 / 37 ) 48.5270526315789 1.97671307974490 24.549365878553 Trimmed Mean ( 9 / 37 ) 48.3075268817204 1.94556805459754 24.8295230627198 Trimmed Mean ( 10 / 37 ) 48.077032967033 1.91153122810156 25.1510580942906 Trimmed Mean ( 11 / 37 ) 47.8542696629213 1.87716811581344 25.4927991050948 Trimmed Mean ( 12 / 37 ) 47.7222988505747 1.86233491381803 25.6249821106226 Trimmed Mean ( 13 / 37 ) 47.6331764705882 1.85529352598354 25.6741996904973 Trimmed Mean ( 14 / 37 ) 47.6331764705882 1.84890236429602 25.7629485420258 Trimmed Mean ( 15 / 37 ) 47.4741975308642 1.84233226504366 25.7685317853015 Trimmed Mean ( 16 / 37 ) 47.3962025316456 1.8352370715671 25.8256566772456 Trimmed Mean ( 17 / 37 ) 47.3245454545455 1.82832832620468 25.8840519923376 Trimmed Mean ( 18 / 37 ) 47.2492 1.81962463964115 25.9664542734034 Trimmed Mean ( 19 / 37 ) 47.1828767123288 1.81173261169957 26.0429582200140 Trimmed Mean ( 20 / 37 ) 47.1153521126761 1.80294298681954 26.1324692223293 Trimmed Mean ( 21 / 37 ) 47.0524637681159 1.79460813170123 26.2187955893813 Trimmed Mean ( 22 / 37 ) 46.9885074626866 1.78642591788644 26.30308203224 Trimmed Mean ( 23 / 37 ) 46.9330769230769 1.77996026753242 26.3674857125552 Trimmed Mean ( 24 / 37 ) 46.8819047619048 1.77275925153671 26.4457256230733 Trimmed Mean ( 25 / 37 ) 46.8370491803279 1.76540647410508 26.530461889277 Trimmed Mean ( 26 / 37 ) 46.7974576271186 1.75762735563799 26.6253580299631 Trimmed Mean ( 27 / 37 ) 46.7584210526316 1.74745776298761 26.7579692299339 Trimmed Mean ( 28 / 37 ) 46.7584210526316 1.73752110380412 26.9109946062002 Trimmed Mean ( 29 / 37 ) 46.6658490566038 1.72401168410625 27.0681744716806 Trimmed Mean ( 30 / 37 ) 46.6492156862745 1.71556580372562 27.1917379006789 Trimmed Mean ( 31 / 37 ) 46.6492156862745 1.7097673366314 27.2839553586181 Trimmed Mean ( 32 / 37 ) 46.6610638297872 1.70259453298773 27.4058578984779 Trimmed Mean ( 33 / 37 ) 46.6604444444444 1.69413545651037 27.542333917358 Trimmed Mean ( 34 / 37 ) 46.6653488372093 1.68162867808129 27.7500909953877 Trimmed Mean ( 35 / 37 ) 46.6763414634146 1.66709656165009 27.9985830078219 Trimmed Mean ( 36 / 37 ) 46.6923076923077 1.65046627614219 28.290373676369 Trimmed Mean ( 37 / 37 ) 46.7178378378378 1.63105545956674 28.6427034493651 Median 45.85 Midrange 77.505 Midmean - Weighted Average at Xnp 46.3848214285714 Midmean - Weighted Average at X(n+1)p 46.7584210526316 Midmean - Empirical Distribution Function 46.7584210526316 Midmean - Empirical Distribution Function - Averaging 46.7584210526316 Midmean - Empirical Distribution Function - Interpolation 46.7147272727273 Midmean - Closest Observation 46.3848214285714 Midmean - True Basic - Statistics Graphics Toolkit 46.7584210526316 Midmean - MS Excel (old versions) 46.7584210526316 Number of observations 111

Charts produced by software:

http://www.freestatistics.org/blog/date/2009/Dec/28/t1262008337rc89tjaf619rx3l/1bmv61262008283.png (open in new window) http://www.freestatistics.org/blog/date/2009/Dec/28/t1262008337rc89tjaf619rx3l/1bmv61262008283.ps (open in new window) http://www.freestatistics.org/blog/date/2009/Dec/28/t1262008337rc89tjaf619rx3l/2716o1262008283.png (open in new window) http://www.freestatistics.org/blog/date/2009/Dec/28/t1262008337rc89tjaf619rx3l/2716o1262008283.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

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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.

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