Home » date » 2007 » Dec » 21 » attachments

robustness of central tendency paper

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

Title produced by software: Central Tendency

Date of computation: Fri, 21 Dec 2007 05:09:07 -0700

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2007/Dec/21/t1198237868az3kgi8x2h7il6z.htm/, Retrieved Fri, 21 Dec 2007 12:51:10 +0100

User-defined keywords:

Dataseries X:

» Textbox « » Textfile « » CSV «

0.00200147839087365 -0.0216058444005542 -0.0222145391353238 -0.0463985224381376 -0.0353895324141767 -0.00932747082545202 0.0323671470576175 0.0524787528909093 -0.0345828840913102 0.0218191134390016 -0.0197276173643167 -0.0167535721706866 -0.0612768206067064 -0.0161420992820751 -0.0197857153606179 0.0544297619502803 -0.00217303079785906 -0.0228193177289160 0.0144316044983902 0.0274435630572674 0.0142137759982791 0.159834240154226 -0.0214959343099046 0.00675270350609719 0.0985968705390431 -0.0145013124776513 0.0170492335281872 -0.0531272284338411 -0.00444892352079798 0.0131112572585838 0.0561877511329985 -0.0239301906202676 -0.00494997317367667 0.0347398710767976 -0.00436421755315953 0.0100763865618025 0.0313879952146342 -0.00476915900880408 -0.00452389727569396 -0.0303248377253466 -0.00947344518451138 0.0124410167441955 0.0089866232118211 0.0120244946854947 0.00722018999236059 -0.0294831633822169 -0.00306040964075164 0.00649679218741509 -0.0123572816765002 0.00439863636840774 -0.00623602489273799 -0.106126447542172 -0.00238282008985389 0.00251495964172511 0.109705993487879 0.010080866523411 0.0074489176906658 -0.0244593383436526 -0.0082576514941279 -0.0049345890875587 0.000421793444245806 -0.00441571103437802 -0.00534514728290785 0.0213902267384058 0.00608139143442771 -0.0197927389349290 -0.00652549674086137 -0.000316549923858597 -0.0110717984282002 0.00830966692376999 -0.0106978412552433 -0.00205385008959703 0.0167323581047296 -0.00374319446726109 -0.0193040237051260 0.0313676465741677 0.00203221930894221 -0.0032515955901252 -0.0799819891658529 0.00784734309454633 -0.00759310363931603 -0.00680303446603329 -0.0106429612240380 -0.0284949069867679 0.0444628650674193 -0.0171287395161674 -0.0343181733968545 0.0208233058747531 -0.032083747726223 -0.0325805438051414 0.0687576767971405 0.00826018419130082 -0.0442807032733388

Text written by user:

Output produced by software:

Summary of compuational transaction Raw Input view raw input (R code) Raw Output view raw output of R engine Computing time 6 seconds R Server 'Herman Ole Andreas Wold' @ 193.190.124.10:1001 Central Tendency - Ungrouped Data Measure Value S.E. Value/S.E. Arithmetic Mean -0.000183903100638346 0.0036655068751339 -0.0501712605931555 Geometric Mean NaN Harmonic Mean -0.0294134830363143 Quadratic Mean 0.0351587878104832 Winsorized Mean ( 1 / 31 ) -0.000441793297305312 0.00335950950585457 -0.131505297584485 Winsorized Mean ( 2 / 31 ) -0.000278437477728740 0.00318261214927171 -0.0874870906882123 Winsorized Mean ( 3 / 31 ) -0.00097810204447188 0.00283577132429948 -0.344915697570748 Winsorized Mean ( 4 / 31 ) -0.00122933729902837 0.0026435285216758 -0.465036518028209 Winsorized Mean ( 5 / 31 ) -0.00120999160106705 0.00260055517958791 -0.465282033069105 Winsorized Mean ( 6 / 31 ) -0.00076223922688698 0.00247577656501061 -0.307878844019882 Winsorized Mean ( 7 / 31 ) -0.00130487015704144 0.00233138264194525 -0.559697980745316 Winsorized Mean ( 8 / 31 ) -0.00211848592445357 0.00216054896152157 -0.980531319670542 Winsorized Mean ( 9 / 31 ) -0.00217994667549876 0.00209172977563997 -1.04217413782896 Winsorized Mean ( 10 / 31 ) -0.00223181288668853 0.00206454303215936 -1.08102027999592 Winsorized Mean ( 11 / 31 ) -0.00202617659674758 0.00203201540582746 -0.997126592119756 Winsorized Mean ( 12 / 31 ) -0.00242390681271798 0.001927581897705 -1.25748577303196 Winsorized Mean ( 13 / 31 ) -0.00307197683311172 0.00178011553852611 -1.72571766642475 Winsorized Mean ( 14 / 31 ) -0.00252903546542062 0.00167984195379572 -1.50551988519282 Winsorized Mean ( 15 / 31 ) -0.00253512790739928 0.00165368910603687 -1.53301361068697 Winsorized Mean ( 16 / 31 ) -0.00299331275990926 0.00153060375816139 -1.95564184652528 Winsorized Mean ( 17 / 31 ) -0.00294068529870187 0.00150690372661372 -1.95147523147355 Winsorized Mean ( 18 / 31 ) -0.00326818056416699 0.00142888045989649 -2.28723161656486 Winsorized Mean ( 19 / 31 ) -0.00329022841126127 0.00141977152804030 -2.31743512690576 Winsorized Mean ( 20 / 31 ) -0.00316105064023325 0.00133791095972198 -2.36267639282223 Winsorized Mean ( 21 / 31 ) -0.00331080930412165 0.00131785951672909 -2.51226269727067 Winsorized Mean ( 22 / 31 ) -0.00339559779200113 0.00130325270618529 -2.60547917981332 Winsorized Mean ( 23 / 31 ) -0.00377152030346929 0.00122851156574153 -3.06999169453712 Winsorized Mean ( 24 / 31 ) -0.00321131276092733 0.00115291051152325 -2.78539637624126 Winsorized Mean ( 25 / 31 ) -0.0034034084610619 0.00110342574322423 -3.08440190195045 Winsorized Mean ( 26 / 31 ) -0.003421715648002 0.00105805691815178 -3.23396179288642 Winsorized Mean ( 27 / 31 ) -0.00295972414324098 0.000995126604027047 -2.97421868862079 Winsorized Mean ( 28 / 31 ) -0.00243850573761619 0.000900358719375443 -2.70837132482898 Winsorized Mean ( 29 / 31 ) -0.00216189630225959 0.000837698597139712 -2.58075674191325 Winsorized Mean ( 30 / 31 ) -0.00211504808463001 0.000814621251502886 -2.59635760880038 Winsorized Mean ( 31 / 31 ) -0.00225258356964937 0.000793200982476415 -2.83986482545280 Trimmed Mean ( 1 / 31 ) -0.000778140450235386 0.00308796841160277 -0.25199106548875 Trimmed Mean ( 2 / 31 ) -0.00112960432913985 0.00275870703927931 -0.409468752229286 Trimmed Mean ( 3 / 31 ) -0.00158453833592854 0.00248018328316298 -0.63887953228512 Trimmed Mean ( 4 / 31 ) -0.00180570921869509 0.00231954491762307 -0.778475641914049 Trimmed Mean ( 5 / 31 ) -0.00196716279860173 0.00220401340853816 -0.892536674677707 Trimmed Mean ( 6 / 31 ) -0.00214103174025784 0.00208195655518610 -1.02837484044736 Trimmed Mean ( 7 / 31 ) -0.00241155432199516 0.00197325817865743 -1.22211799149158 Trimmed Mean ( 8 / 31 ) -0.00260250353784060 0.00188340329238225 -1.38180895635411 Trimmed Mean ( 9 / 31 ) -0.00267752626791559 0.00181869680127043 -1.47222245403700 Trimmed Mean ( 10 / 31 ) -0.00274795990885131 0.00175750296744496 -1.56355918581819 Trimmed Mean ( 11 / 31 ) -0.00281556789907827 0.00169082290779134 -1.66520567358301 Trimmed Mean ( 12 / 31 ) -0.00291229173454171 0.00161796358123636 -1.79997360157903 Trimmed Mean ( 13 / 31 ) -0.00291229173454171 0.00155227350327940 -1.87614600673726 Trimmed Mean ( 14 / 31 ) -0.00295742670477942 0.00150232290455674 -1.96856927083330 Trimmed Mean ( 15 / 31 ) -0.00300259720960977 0.00146067615804101 -2.05562142784388 Trimmed Mean ( 16 / 31 ) -0.00305011048294919 0.00141498303566998 -2.15558095472502 Trimmed Mean ( 17 / 31 ) -0.0030557060213419 0.00138172517249697 -2.21151505535636 Trimmed Mean ( 18 / 31 ) -0.00306674516190487 0.00134501370071265 -2.28008470120413 Trimmed Mean ( 19 / 31 ) -0.00304782244229843 0.00131356754644744 -2.32026320271180 Trimmed Mean ( 20 / 31 ) -0.00302543539650544 0.00127586351013445 -2.37128452414681 Trimmed Mean ( 21 / 31 ) -0.00301307047722438 0.00124376878506440 -2.42253263902933 Trimmed Mean ( 22 / 31 ) -0.00298616113718410 0.00120665743031750 -2.47473811717909 Trimmed Mean ( 23 / 31 ) -0.00294933559666380 0.00116193565256679 -2.53829511999957 Trimmed Mean ( 24 / 31 ) -0.00287545813025519 0.00111947783395728 -2.56857084886677 Trimmed Mean ( 25 / 31 ) -0.00284519216063067 0.00108100762247115 -2.63198158966415 Trimmed Mean ( 26 / 31 ) -0.00284519216063067 0.00104090452732372 -2.73338436517897 Trimmed Mean ( 27 / 31 ) -0.00273702260487047 0.000997744113190567 -2.74321097833198 Trimmed Mean ( 28 / 31 ) -0.00271629062982697 0.000955452236662809 -2.84293711982337 Trimmed Mean ( 29 / 31 ) -0.00274265184918983 0.000921911026233323 -2.97496371249138 Trimmed Mean ( 30 / 31 ) -0.00279908890860938 0.00089085040175388 -3.14204147306733 Trimmed Mean ( 31 / 31 ) -0.00286749299100732 0.000852028292129645 -3.3654903452091 Median -0.00436421755315953 Midrange 0.026853896306027 Midmean - Weighted Average at Xnp -0.00323260086014369 Midmean - Weighted Average at X(n+1)p -0.00294933559666380 Midmean - Empirical Distribution Function -0.00294933559666380 Midmean - Empirical Distribution Function - Averaging -0.00294933559666380 Midmean - Empirical Distribution Function - Interpolation -0.00294933559666380 Midmean - Closest Observation -0.00329888313348991 Midmean - True Basic - Statistics Graphics Toolkit -0.00294933559666380 Midmean - MS Excel (old versions) -0.00294933559666380 Number of observations 93

Charts produced by software:

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2007/Dec/21/t1198237868az3kgi8x2h7il6z/1dq5k1198238931.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2007/Dec/21/t1198237868az3kgi8x2h7il6z/1dq5k1198238931.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2007/Dec/21/t1198237868az3kgi8x2h7il6z/233ok1198238931.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2007/Dec/21/t1198237868az3kgi8x2h7il6z/233ok1198238931.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