*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: Thu, 25 Nov 2010 20:43:28 +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/Nov/25/t1290717755z8nerlxoftpgjbu.htm/, Retrieved Thu, 25 Nov 2010 21:42:35 +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/2010/Nov/25/t1290717755z8nerlxoftpgjbu.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:

Dataseries X:

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1,00 1,10 0,20 0,20 -0,10 -0,20 -0,10 -0,40 0,00 -0,30 -0,20 0,30 1,80 2,40 2,90 3,60 3,90 4,90 5,20 5,80 6,00 7,60 7,70 8,70 8,70 8,90 9,20 9,70 10,20 10,50 10,10 11,40 11,60 11,60 12,40 12,40 11,40 11,60 11,90 11,00 10,70 10,30 11,00 10,20 10,10 9,90 9,30 8,50 8,40 8,10 7,80 8,40 8,80 8,90 8,40 7,80 7,50 7,30 7,60 7,90 8,30 8,20 8,00 7,60 7,30 6,80 6,40 6,60 6,80 6,60 6,00 5,80 5,90 5,50 5,30 5,30 4,90 5,40 6,20 6,20 6,40 7,10 7,40 7,90 7,60 8,40 8,80 8,60 8,70 8,90 8,20 8,10 7,30 6,90 7,00 6,90 7,10 7,00 7,00 7,20 7,70 7,40 7,40 7,40 7,80 8,00 7,80 7,40 6,90 5,90 5,60 5,40 4,40 3,90 3,80 3,90 3,90 4,10 3,90 4,20 4,20 4,70 4,40 4,60 5,50 5,90 6,00 5,80 4,90

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 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 Central Tendency - Ungrouped Data Measure Value S.E. Value/S.E. Arithmetic Mean 6.63488372093023 0.264793988874517 25.0567762098045 Geometric Mean NaN Harmonic Mean 0 Quadratic Mean 7.27987030295918 Winsorized Mean ( 1 / 43 ) 6.63565891472868 0.26463417791757 25.0748371466803 Winsorized Mean ( 2 / 43 ) 6.62945736434108 0.263051752866269 25.2021029782356 Winsorized Mean ( 3 / 43 ) 6.62248062015504 0.261987873239231 25.2778135807370 Winsorized Mean ( 4 / 43 ) 6.62558139534884 0.261360759387639 25.3503296013999 Winsorized Mean ( 5 / 43 ) 6.62558139534884 0.261360759387639 25.3503296013999 Winsorized Mean ( 6 / 43 ) 6.62093023255814 0.259066868712298 25.5568389175649 Winsorized Mean ( 7 / 43 ) 6.63178294573643 0.256922058997228 25.8124310992229 Winsorized Mean ( 8 / 43 ) 6.60697674418605 0.253443307725328 26.0688546226931 Winsorized Mean ( 9 / 43 ) 6.6139534883721 0.252071707206867 26.2383809815841 Winsorized Mean ( 10 / 43 ) 6.64496124031008 0.238614178766718 27.8481407712429 Winsorized Mean ( 11 / 43 ) 6.63643410852713 0.234812254874742 28.2627246694057 Winsorized Mean ( 12 / 43 ) 6.68294573643411 0.22079161893298 30.2681132949285 Winsorized Mean ( 13 / 43 ) 6.73333333333333 0.209374337131119 32.1593057945618 Winsorized Mean ( 14 / 43 ) 6.7875968992248 0.200879268018609 33.7894346498515 Winsorized Mean ( 15 / 43 ) 6.85736434108527 0.187628428864258 36.5475764125612 Winsorized Mean ( 16 / 43 ) 6.88217054263566 0.184325351719021 37.3370807566752 Winsorized Mean ( 17 / 43 ) 6.86899224806201 0.179070186918533 38.3592175016103 Winsorized Mean ( 18 / 43 ) 6.84108527131783 0.17544797453183 38.9921017302865 Winsorized Mean ( 19 / 43 ) 6.78217054263566 0.168247527872412 40.3106698113199 Winsorized Mean ( 20 / 43 ) 6.76666666666667 0.166455777429903 40.6514377040246 Winsorized Mean ( 21 / 43 ) 6.71782945736434 0.161079245313718 41.7051212543284 Winsorized Mean ( 22 / 43 ) 6.75193798449612 0.156489548060323 43.1462552495416 Winsorized Mean ( 23 / 43 ) 6.76976744186047 0.154148089643215 43.9172970455197 Winsorized Mean ( 24 / 43 ) 6.75116279069768 0.152165076838736 44.3673603099648 Winsorized Mean ( 25 / 43 ) 6.78992248062016 0.147166572954937 46.1376679791223 Winsorized Mean ( 26 / 43 ) 6.76976744186046 0.145043283482167 46.6741187825688 Winsorized Mean ( 27 / 43 ) 6.81162790697674 0.139782967446330 48.7300279241253 Winsorized Mean ( 28 / 43 ) 6.83333333333333 0.137122161156041 49.8339092362845 Winsorized Mean ( 29 / 43 ) 6.85581395348837 0.129352081428532 53.0011877487743 Winsorized Mean ( 30 / 43 ) 6.83255813953488 0.126933509300367 53.8278518981681 Winsorized Mean ( 31 / 43 ) 6.80852713178295 0.124500119702356 54.6869123343829 Winsorized Mean ( 32 / 43 ) 6.88294573643411 0.115811114254396 59.4325145798593 Winsorized Mean ( 33 / 43 ) 6.90852713178295 0.112935371000211 61.1723950662899 Winsorized Mean ( 34 / 43 ) 6.90852713178294 0.112935371000211 61.1723950662899 Winsorized Mean ( 35 / 43 ) 6.90852713178295 0.107156874242271 64.4711520435304 Winsorized Mean ( 36 / 43 ) 6.88062015503876 0.104362669392914 65.9298980666541 Winsorized Mean ( 37 / 43 ) 6.9093023255814 0.101212620268089 68.2652252977963 Winsorized Mean ( 38 / 43 ) 6.87984496124031 0.0983166199477343 69.9764186858506 Winsorized Mean ( 39 / 43 ) 6.91007751937985 0.0950306264461233 72.7142162247815 Winsorized Mean ( 40 / 43 ) 6.94108527131783 0.0854310519397879 81.2478029207686 Winsorized Mean ( 41 / 43 ) 6.94108527131783 0.0854310519397879 81.2478029207686 Winsorized Mean ( 42 / 43 ) 6.90852713178295 0.082322093588069 83.9206928622646 Winsorized Mean ( 43 / 43 ) 6.94186046511628 0.078847513104073 88.041590556617 Trimmed Mean ( 1 / 43 ) 6.64488188976378 0.259191026712405 25.6370059336076 Trimmed Mean ( 2 / 43 ) 6.6544 0.253192529064729 26.2819761095668 Trimmed Mean ( 3 / 43 ) 6.66747967479675 0.247489045378268 26.9405042336562 Trimmed Mean ( 4 / 43 ) 6.68347107438017 0.241609465370878 27.6622899029259 Trimmed Mean ( 5 / 43 ) 6.69915966386555 0.235290811216519 28.4718286669549 Trimmed Mean ( 6 / 43 ) 6.71538461538462 0.228256037000291 29.4204030861013 Trimmed Mean ( 7 / 43 ) 6.73304347826087 0.220953214548394 30.4727111213229 Trimmed Mean ( 8 / 43 ) 6.7495575221239 0.213250696372802 31.6508111669863 Trimmed Mean ( 9 / 43 ) 6.77027027027027 0.205280793271436 32.9805344298245 Trimmed Mean ( 10 / 43 ) 6.7908256880734 0.196540506556896 34.5517868404778 Trimmed Mean ( 11 / 43 ) 6.80841121495327 0.189171324401691 35.9907149589762 Trimmed Mean ( 12 / 43 ) 6.82761904761905 0.181474905873272 37.6229375337818 Trimmed Mean ( 13 / 43 ) 6.84271844660194 0.175142931713277 39.0693382808278 Trimmed Mean ( 14 / 43 ) 6.85346534653465 0.169813901379872 40.3586825980962 Trimmed Mean ( 15 / 43 ) 6.85959595959596 0.165087879072870 41.5511786699261 Trimmed Mean ( 16 / 43 ) 6.85979381443299 0.161638011111865 42.4392367070486 Trimmed Mean ( 17 / 43 ) 6.8578947368421 0.158178170392539 43.3555067669792 Trimmed Mean ( 18 / 43 ) 6.85698924731183 0.154951000786828 44.2526296215747 Trimmed Mean ( 19 / 43 ) 6.85824175824176 0.151750598151154 45.1941662293184 Trimmed Mean ( 20 / 43 ) 6.86404494382022 0.149002875723866 46.0665266389944 Trimmed Mean ( 21 / 43 ) 6.87126436781609 0.146069487680214 47.0410657074335 Trimmed Mean ( 22 / 43 ) 6.88235294117647 0.143331474848757 48.0170384658268 Trimmed Mean ( 23 / 43 ) 6.89156626506024 0.140767436261370 48.9571057631846 Trimmed Mean ( 24 / 43 ) 6.9 0.138097746738754 49.9646095823204 Trimmed Mean ( 25 / 43 ) 6.91012658227848 0.135221876845551 51.102134828162 Trimmed Mean ( 26 / 43 ) 6.91818181818182 0.132535700096848 52.1986288458619 Trimmed Mean ( 27 / 43 ) 6.928 0.129636498030538 53.4417398283006 Trimmed Mean ( 28 / 43 ) 6.93561643835616 0.126950083417288 54.6326260815333 Trimmed Mean ( 29 / 43 ) 6.94225352112676 0.124141510280698 55.9220965286273 Trimmed Mean ( 30 / 43 ) 6.94782608695652 0.121857055295133 57.0161987759278 Trimmed Mean ( 31 / 43 ) 6.95522388059702 0.119422770861819 58.2403492265701 Trimmed Mean ( 32 / 43 ) 6.96461538461538 0.116796806817825 59.6301865981536 Trimmed Mean ( 33 / 43 ) 6.96984126984127 0.114906291450133 60.6567419579983 Trimmed Mean ( 34 / 43 ) 6.97377049180328 0.113004222546578 61.7124770618975 Trimmed Mean ( 35 / 43 ) 6.97796610169492 0.110655762695442 63.0601238626893 Trimmed Mean ( 36 / 43 ) 6.98245614035088 0.108623271362833 64.281401699158 Trimmed Mean ( 37 / 43 ) 6.98909090909091 0.106479404033447 65.6379604350107 Trimmed Mean ( 38 / 43 ) 6.99433962264151 0.104312494340870 67.0517915120076 Trimmed Mean ( 39 / 43 ) 7.00196078431373 0.101999238600712 68.6471867865968 Trimmed Mean ( 40 / 43 ) 7.00816326530612 0.0996523179795103 70.3261440114929 Trimmed Mean ( 41 / 43 ) 7.01276595744681 0.0983497986679478 71.3043244869628 Trimmed Mean ( 42 / 43 ) 7.01777777777778 0.0965719959036628 72.6688696045849 Trimmed Mean ( 43 / 43 ) 7.02558139534884 0.0947160484059897 74.1751953716911 Median 7.1 Midrange 6 Midmean - Weighted Average at Xnp 6.98636363636364 Midmean - Weighted Average at X(n+1)p 6.98636363636364 Midmean - Empirical Distribution Function 6.98636363636364 Midmean - Empirical Distribution Function - Averaging 6.98636363636364 Midmean - Empirical Distribution Function - Interpolation 6.98636363636364 Midmean - Closest Observation 6.89565217391304 Midmean - True Basic - Statistics Graphics Toolkit 6.98636363636364 Midmean - MS Excel (old versions) 6.98636363636364 Number of observations 129

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Nov/25/t1290717755z8nerlxoftpgjbu/1u5261290717805.png (open in new window) http://www.freestatistics.org/blog/date/2010/Nov/25/t1290717755z8nerlxoftpgjbu/1u5261290717805.ps (open in new window) http://www.freestatistics.org/blog/date/2010/Nov/25/t1290717755z8nerlxoftpgjbu/25ejr1290717805.png (open in new window) http://www.freestatistics.org/blog/date/2010/Nov/25/t1290717755z8nerlxoftpgjbu/25ejr1290717805.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')

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