paper 2

*The author of this computation has been verified*

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

Title produced by software: Central Tendency

Date of computation: Tue, 22 Dec 2009 07:26:53 -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/22/t1261492103853i7ceercnftdm.htm/, Retrieved Tue, 22 Dec 2009 15:28:26 +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/22/t1261492103853i7ceercnftdm.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 «

33 39 45 46 45 45 49 50 54 59 58 56 48 50 52 53 55 43 42 38 41 41 39 34 27 15 14 31 41 43 46 42 45 45 40 35 36 38 39 32 24 21 12 29 36 31 28 30 38 27 40 40 44 47 45 42 38 46 37 41 40 33 34 36 36 38 42 35 25 24 22 27 17 30 30 34 37 36 33 33 33 37 40 35 37 43 42 33 39 40 37 44 42 43 40 30 30 31 18 24 22 26 28 23 17 12 9 19 21 18 18 15 24 18 19 30 33 35 36 47 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 2 seconds R Server 'Gwilym Jenkins' @ 72.249.127.135 Central Tendency - Ungrouped Data Measure Value S.E. Value/S.E. Arithmetic Mean 35.1735537190083 0.970052800666708 36.2594218529484 Geometric Mean 33.2365122151167 Harmonic Mean 30.8446332604069 Quadratic Mean 36.7436956980884 Winsorized Mean ( 1 / 40 ) 35.1900826446281 0.963115500282926 36.537759629339 Winsorized Mean ( 2 / 40 ) 35.1570247933884 0.956852066229556 36.7423826881866 Winsorized Mean ( 3 / 40 ) 35.1818181818182 0.94278469186056 37.316917092054 Winsorized Mean ( 4 / 40 ) 35.1818181818182 0.931023312121398 37.7883321757584 Winsorized Mean ( 5 / 40 ) 35.1404958677686 0.924215532529095 38.0219706669584 Winsorized Mean ( 6 / 40 ) 35.1900826446281 0.89898274693229 39.1443359338225 Winsorized Mean ( 7 / 40 ) 35.0743801652893 0.88179985057924 39.7758971520005 Winsorized Mean ( 8 / 40 ) 35.1404958677686 0.87072891356964 40.3575617165469 Winsorized Mean ( 9 / 40 ) 35.0661157024793 0.860419490328687 40.7546738499424 Winsorized Mean ( 10 / 40 ) 34.9834710743802 0.84956507030829 41.1780948829327 Winsorized Mean ( 11 / 40 ) 34.8925619834711 0.838288435085696 41.62357551778 Winsorized Mean ( 12 / 40 ) 34.9917355371901 0.821918727739822 42.5732306081079 Winsorized Mean ( 13 / 40 ) 34.8842975206612 0.809226246992505 43.1082131237202 Winsorized Mean ( 14 / 40 ) 35.1157024793388 0.772655084207793 45.4480960483721 Winsorized Mean ( 15 / 40 ) 35.1157024793388 0.772655084207793 45.4480960483721 Winsorized Mean ( 16 / 40 ) 35.2479338842975 0.752889840421096 46.8168541955396 Winsorized Mean ( 17 / 40 ) 35.1074380165289 0.736663019283371 47.657391639778 Winsorized Mean ( 18 / 40 ) 35.2561983471074 0.715003412272949 49.3091329942472 Winsorized Mean ( 19 / 40 ) 35.4132231404959 0.693006129895452 51.100880082891 Winsorized Mean ( 20 / 40 ) 35.4132231404959 0.693006129895452 51.100880082891 Winsorized Mean ( 21 / 40 ) 35.4132231404959 0.693006129895452 51.100880082891 Winsorized Mean ( 22 / 40 ) 35.4132231404959 0.693006129895452 51.100880082891 Winsorized Mean ( 23 / 40 ) 35.4132231404959 0.645675316649144 54.8467971863623 Winsorized Mean ( 24 / 40 ) 35.6115702479339 0.619514150349273 57.4830618927051 Winsorized Mean ( 25 / 40 ) 35.6115702479339 0.570313806232499 62.4420623501725 Winsorized Mean ( 26 / 40 ) 35.6115702479339 0.570313806232499 62.4420623501725 Winsorized Mean ( 27 / 40 ) 35.6115702479339 0.570313806232499 62.4420623501725 Winsorized Mean ( 28 / 40 ) 35.8429752066116 0.541781606511939 66.1576081133012 Winsorized Mean ( 29 / 40 ) 35.603305785124 0.516194933341099 68.9725983063795 Winsorized Mean ( 30 / 40 ) 35.8512396694215 0.486407695119211 73.7061523268765 Winsorized Mean ( 31 / 40 ) 36.1074380165289 0.457084070501109 78.9951791077378 Winsorized Mean ( 32 / 40 ) 36.1074380165289 0.457084070501109 78.9951791077378 Winsorized Mean ( 33 / 40 ) 36.1074380165289 0.457084070501109 78.9951791077378 Winsorized Mean ( 34 / 40 ) 36.1074380165289 0.457084070501109 78.9951791077378 Winsorized Mean ( 35 / 40 ) 35.8181818181818 0.426885704795414 83.9057888699921 Winsorized Mean ( 36 / 40 ) 35.8181818181818 0.426885704795414 83.9057888699921 Winsorized Mean ( 37 / 40 ) 36.1239669421488 0.392872140777579 91.9484055821613 Winsorized Mean ( 38 / 40 ) 36.1239669421488 0.392872140777579 91.9484055821613 Winsorized Mean ( 39 / 40 ) 35.801652892562 0.360520712088023 99.3053982535706 Winsorized Mean ( 40 / 40 ) 36.1322314049587 0.324598108953416 111.313745854706 Trimmed Mean ( 1 / 40 ) 35.1932773109244 0.94011527860349 37.4350657966146 Trimmed Mean ( 2 / 40 ) 35.1965811965812 0.914583624414763 38.4837211786984 Trimmed Mean ( 3 / 40 ) 35.2173913043478 0.889877185253864 39.5755637833338 Trimmed Mean ( 4 / 40 ) 35.2300884955752 0.868213145480821 40.5776953262607 Trimmed Mean ( 5 / 40 ) 35.2432432432432 0.847911749635864 41.5647539480123 Trimmed Mean ( 6 / 40 ) 35.2660550458716 0.8271064195095 42.6378688570516 Trimmed Mean ( 7 / 40 ) 35.2803738317757 0.809896727343663 43.5615710505337 Trimmed Mean ( 8 / 40 ) 35.3142857142857 0.794246052716262 44.4626518363088 Trimmed Mean ( 9 / 40 ) 35.3398058252427 0.778855515706062 45.3740201007704 Trimmed Mean ( 10 / 40 ) 35.3762376237624 0.763375967886231 46.3418277650504 Trimmed Mean ( 11 / 40 ) 35.4242424242424 0.747715673173899 47.3766214821656 Trimmed Mean ( 12 / 40 ) 35.4845360824742 0.731753032411099 48.4925029494637 Trimmed Mean ( 13 / 40 ) 35.5368421052632 0.716281696247919 49.6129417956859 Trimmed Mean ( 14 / 40 ) 35.6021505376344 0.700487338697237 50.8248309010797 Trimmed Mean ( 15 / 40 ) 35.6483516483516 0.688005314595572 51.8140643569108 Trimmed Mean ( 16 / 40 ) 35.6966292134831 0.673708141144091 52.9853018443018 Trimmed Mean ( 17 / 40 ) 35.7356321839080 0.66017821585896 54.1302807718554 Trimmed Mean ( 18 / 40 ) 35.7882352941176 0.646709862612081 55.3389353760091 Trimmed Mean ( 19 / 40 ) 35.8313253012048 0.634223137608153 56.4964019388122 Trimmed Mean ( 20 / 40 ) 35.8641975308642 0.622805551571134 57.5849034106882 Trimmed Mean ( 21 / 40 ) 35.8987341772152 0.609508913349432 58.8978001649574 Trimmed Mean ( 22 / 40 ) 35.9350649350649 0.593982602699374 60.498514218694 Trimmed Mean ( 23 / 40 ) 35.9733333333333 0.575779403870894 62.4776313488969 Trimmed Mean ( 24 / 40 ) 36.013698630137 0.561137797795256 64.1797768242256 Trimmed Mean ( 25 / 40 ) 36.0422535211268 0.547699274106204 65.8066483289475 Trimmed Mean ( 26 / 40 ) 36.0724637681159 0.538508106382126 66.9859252638973 Trimmed Mean ( 27 / 40 ) 36.1044776119403 0.527461312051924 68.4495275520532 Trimmed Mean ( 28 / 40 ) 36.1384615384615 0.514163306086154 70.285959948309 Trimmed Mean ( 29 / 40 ) 36.1587301587302 0.502531405201403 71.9531750343814 Trimmed Mean ( 30 / 40 ) 36.1967213114754 0.491912556165418 73.5836498942779 Trimmed Mean ( 31 / 40 ) 36.1967213114754 0.483550450673035 74.8561422310631 Trimmed Mean ( 32 / 40 ) 36.2280701754386 0.477578441548465 75.8578424477776 Trimmed Mean ( 33 / 40 ) 36.2363636363636 0.469947798780041 77.1072100570132 Trimmed Mean ( 34 / 40 ) 36.2452830188679 0.460253022778028 78.7507766925593 Trimmed Mean ( 35 / 40 ) 36.2549019607843 0.447952323491565 80.934733585475 Trimmed Mean ( 36 / 40 ) 36.2857142857143 0.437408882639853 82.956052622257 Trimmed Mean ( 37 / 40 ) 36.3191489361702 0.423747414618277 85.7094289740682 Trimmed Mean ( 38 / 40 ) 36.3333333333333 0.413167122006423 87.938588038882 Trimmed Mean ( 39 / 40 ) 36.3488372093023 0.399173732608052 91.0601931941079 Trimmed Mean ( 40 / 40 ) 36.390243902439 0.387106289022272 94.0058194206845 Median 36 Midrange 34 Midmean - Weighted Average at Xnp 36.2903225806452 Midmean - Weighted Average at X(n+1)p 36.2903225806452 Midmean - Empirical Distribution Function 36.2903225806452 Midmean - Empirical Distribution Function - Averaging 36.2903225806452 Midmean - Empirical Distribution Function - Interpolation 36.2903225806452 Midmean - Closest Observation 36.03125 Midmean - True Basic - Statistics Graphics Toolkit 36.2903225806452 Midmean - MS Excel (old versions) 36.2903225806452 Number of observations 121

Charts produced by software:

http://www.freestatistics.org/blog/date/2009/Dec/22/t1261492103853i7ceercnftdm/1moak1261492010.png (open in new window) http://www.freestatistics.org/blog/date/2009/Dec/22/t1261492103853i7ceercnftdm/1moak1261492010.ps (open in new window) http://www.freestatistics.org/blog/date/2009/Dec/22/t1261492103853i7ceercnftdm/2kzj81261492010.png (open in new window) http://www.freestatistics.org/blog/date/2009/Dec/22/t1261492103853i7ceercnftdm/2kzj81261492010.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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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.

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