Central Tendency - Celebrity

*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, 14 Dec 2010 09:52:46 +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/Dec/14/t1292320251n6g9kawbloi23y8.htm/, Retrieved Tue, 14 Dec 2010 10:50:53 +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/Dec/14/t1292320251n6g9kawbloi23y8.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:

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Dataseries X:

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6 4 5 4 4 6 6 4 4 6 4 6 5 4 6 3 5 6 4 6 2 7 5 2 4 4 6 6 5 6 6 4 6 6 6 2 4 5 3 7 5 3 8 8 5 6 3 5 4 5 5 6 5 6 6 4 8 6 4 6 5 5 6 6 6 6 6 6 7 4 4 3 6 5 5 3 5 4 3 7 4 4 5 6 2 2 6 4 5 6 7 8 6 6 3 7 3 6 4 4 6 6 6 4 7 5 7 4 6 6 6 5 5 6 7 4 4 8 6 3 4 5 5 6 8 2 4 7 5 6 6 4 5 6 6 6 6 5 5 6 4 6 3 6 8 4

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 3 seconds R Server 'George Udny Yule' @ 72.249.76.132 Central Tendency - Ungrouped Data Measure Value S.E. Value/S.E. Arithmetic Mean 5.14383561643836 0.115411291802909 44.5696043782495 Geometric Mean 4.92785597675172 Harmonic Mean 4.67395861122756 Quadratic Mean 5.32826528608553 Winsorized Mean ( 1 / 48 ) 5.14383561643836 0.115411291802909 44.5696043782495 Winsorized Mean ( 2 / 48 ) 5.14383561643836 0.115411291802909 44.5696043782495 Winsorized Mean ( 3 / 48 ) 5.14383561643836 0.115411291802909 44.5696043782495 Winsorized Mean ( 4 / 48 ) 5.14383561643836 0.115411291802909 44.5696043782495 Winsorized Mean ( 5 / 48 ) 5.14383561643836 0.115411291802909 44.5696043782495 Winsorized Mean ( 6 / 48 ) 5.18493150684932 0.108671465665704 47.7119865374708 Winsorized Mean ( 7 / 48 ) 5.13698630136986 0.101304732105339 50.7082561160945 Winsorized Mean ( 8 / 48 ) 5.13698630136986 0.101304732105339 50.7082561160945 Winsorized Mean ( 9 / 48 ) 5.13698630136986 0.101304732105339 50.7082561160945 Winsorized Mean ( 10 / 48 ) 5.13698630136986 0.101304732105339 50.7082561160945 Winsorized Mean ( 11 / 48 ) 5.13698630136986 0.101304732105339 50.7082561160945 Winsorized Mean ( 12 / 48 ) 5.13698630136986 0.101304732105339 50.7082561160945 Winsorized Mean ( 13 / 48 ) 5.13698630136986 0.101304732105339 50.7082561160945 Winsorized Mean ( 14 / 48 ) 5.13698630136986 0.101304732105339 50.7082561160945 Winsorized Mean ( 15 / 48 ) 5.13698630136986 0.101304732105339 50.7082561160945 Winsorized Mean ( 16 / 48 ) 5.13698630136986 0.101304732105339 50.7082561160945 Winsorized Mean ( 17 / 48 ) 5.13698630136986 0.0737869220876361 69.6191974950346 Winsorized Mean ( 18 / 48 ) 5.13698630136986 0.0737869220876361 69.6191974950346 Winsorized Mean ( 19 / 48 ) 5.13698630136986 0.0737869220876361 69.6191974950346 Winsorized Mean ( 20 / 48 ) 5.13698630136986 0.0737869220876361 69.6191974950346 Winsorized Mean ( 21 / 48 ) 5.13698630136986 0.0737869220876361 69.6191974950346 Winsorized Mean ( 22 / 48 ) 5.13698630136986 0.0737869220876361 69.6191974950346 Winsorized Mean ( 23 / 48 ) 5.13698630136986 0.0737869220876361 69.6191974950346 Winsorized Mean ( 24 / 48 ) 5.13698630136986 0.0737869220876361 69.6191974950346 Winsorized Mean ( 25 / 48 ) 5.13698630136986 0.0737869220876361 69.6191974950346 Winsorized Mean ( 26 / 48 ) 5.13698630136986 0.0737869220876361 69.6191974950346 Winsorized Mean ( 27 / 48 ) 5.13698630136986 0.0737869220876361 69.6191974950346 Winsorized Mean ( 28 / 48 ) 5.13698630136986 0.0737869220876361 69.6191974950346 Winsorized Mean ( 29 / 48 ) 5.13698630136986 0.0737869220876361 69.6191974950346 Winsorized Mean ( 30 / 48 ) 5.13698630136986 0.0737869220876361 69.6191974950346 Winsorized Mean ( 31 / 48 ) 5.13698630136986 0.0737869220876361 69.6191974950346 Winsorized Mean ( 32 / 48 ) 5.13698630136986 0.0737869220876361 69.6191974950346 Winsorized Mean ( 33 / 48 ) 5.13698630136986 0.0737869220876361 69.6191974950346 Winsorized Mean ( 34 / 48 ) 5.13698630136986 0.0737869220876361 69.6191974950346 Winsorized Mean ( 35 / 48 ) 5.13698630136986 0.0737869220876361 69.6191974950346 Winsorized Mean ( 36 / 48 ) 5.13698630136986 0.0737869220876361 69.6191974950346 Winsorized Mean ( 37 / 48 ) 5.13698630136986 0.0737869220876361 69.6191974950346 Winsorized Mean ( 38 / 48 ) 5.13698630136986 0.0737869220876361 69.6191974950346 Winsorized Mean ( 39 / 48 ) 5.13698630136986 0.0737869220876361 69.6191974950346 Winsorized Mean ( 40 / 48 ) 5.13698630136986 0.0737869220876361 69.6191974950346 Winsorized Mean ( 41 / 48 ) 5.13698630136986 0.0737869220876361 69.6191974950346 Winsorized Mean ( 42 / 48 ) 5.13698630136986 0.0737869220876361 69.6191974950346 Winsorized Mean ( 43 / 48 ) 5.13698630136986 0.0737869220876361 69.6191974950346 Winsorized Mean ( 44 / 48 ) 5.13698630136986 0.0737869220876361 69.6191974950346 Winsorized Mean ( 45 / 48 ) 5.13698630136986 0.0737869220876361 69.6191974950346 Winsorized Mean ( 46 / 48 ) 5.13698630136986 0.0737869220876361 69.6191974950346 Winsorized Mean ( 47 / 48 ) 5.13698630136986 0.0737869220876361 69.6191974950346 Winsorized Mean ( 48 / 48 ) 5.13698630136986 0.0737869220876361 69.6191974950346 Trimmed Mean ( 1 / 48 ) 5.14583333333333 0.113214299720608 45.4521500025377 Trimmed Mean ( 2 / 48 ) 5.14788732394366 0.11082061622271 46.4524336662976 Trimmed Mean ( 3 / 48 ) 5.15 0.108206437394109 47.5942108808435 Trimmed Mean ( 4 / 48 ) 5.15217391304348 0.105343420355078 48.9083598736135 Trimmed Mean ( 5 / 48 ) 5.15441176470588 0.102197359403887 50.4358605229269 Trimmed Mean ( 6 / 48 ) 5.15671641791045 0.0987263053040465 52.2324460743199 Trimmed Mean ( 7 / 48 ) 5.15151515151515 0.096482700315628 53.3931485609625 Trimmed Mean ( 8 / 48 ) 5.15384615384615 0.0954926581433206 53.9711246294032 Trimmed Mean ( 9 / 48 ) 5.15625 0.0944038876109612 54.6190430340001 Trimmed Mean ( 10 / 48 ) 5.15873015873016 0.0932058301962108 55.3477196423264 Trimmed Mean ( 11 / 48 ) 5.16129032258065 0.091886354378262 56.1703678147195 Trimmed Mean ( 12 / 48 ) 5.16393442622951 0.0904314244785578 57.1033184095638 Trimmed Mean ( 13 / 48 ) 5.16666666666667 0.0888246733498353 58.1670212995638 Trimmed Mean ( 14 / 48 ) 5.16949152542373 0.0870468417026572 59.3874679920285 Trimmed Mean ( 15 / 48 ) 5.17241379310345 0.0850750282405464 60.7982612533333 Trimmed Mean ( 16 / 48 ) 5.17543859649123 0.0828816643749685 62.4437097821395 Trimmed Mean ( 17 / 48 ) 5.17857142857143 0.0804330758069427 64.3836055828718 Trimmed Mean ( 18 / 48 ) 5.18181818181818 0.0808439823871256 64.0965230659318 Trimmed Mean ( 19 / 48 ) 5.18518518518519 0.0812546009008576 63.814050253128 Trimmed Mean ( 20 / 48 ) 5.18867924528302 0.0816641903805254 63.536774455311 Trimmed Mean ( 21 / 48 ) 5.19230769230769 0.08207189497118 63.2653564795964 Trimmed Mean ( 22 / 48 ) 5.19607843137255 0.08247672607979 63.0005418297731 Trimmed Mean ( 23 / 48 ) 5.2 0.0828775414010748 62.7431739901078 Trimmed Mean ( 24 / 48 ) 5.20408163265306 0.0832730201910927 62.4942102581469 Trimmed Mean ( 25 / 48 ) 5.20833333333333 0.0836616340137339 62.2547407151806 Trimmed Mean ( 26 / 48 ) 5.21276595744681 0.084041612000209 62.026011084055 Trimmed Mean ( 27 / 48 ) 5.21739130434783 0.0844108994255783 61.8094504365255 Trimmed Mean ( 28 / 48 ) 5.22222222222222 0.0847671081031683 61.6067049953664 Trimmed Mean ( 29 / 48 ) 5.22727272727273 0.085107456705349 61.4196796570963 Trimmed Mean ( 30 / 48 ) 5.23255813953488 0.0854286986072724 61.2505893785141 Trimmed Mean ( 31 / 48 ) 5.23809523809524 0.085727034176573 61.1020232813172 Trimmed Mean ( 32 / 48 ) 5.24390243902439 0.085998003537249 60.9770253184199 Trimmed Mean ( 33 / 48 ) 5.25 0.0862363546351508 60.8791967403043 Trimmed Mean ( 34 / 48 ) 5.25641025641026 0.0864358798029797 60.8128275941844 Trimmed Mean ( 35 / 48 ) 5.26315789473684 0.086589211784232 60.7830673854831 Trimmed Mean ( 36 / 48 ) 5.27027027027027 0.086687567058939 60.7961493103966 Trimmed Mean ( 37 / 48 ) 5.27777777777778 0.0867204199099118 60.8596889090311 Trimmed Mean ( 38 / 48 ) 5.28571428571429 0.0866750843408272 60.983087884052 Trimmed Mean ( 39 / 48 ) 5.29411764705882 0.0865361716973501 61.1780893841059 Trimmed Mean ( 40 / 48 ) 5.3030303030303 0.0862848780050879 61.4595561312331 Trimmed Mean ( 41 / 48 ) 5.3125 0.0858980338670346 61.8465843842649 Trimmed Mean ( 42 / 48 ) 5.32258064516129 0.0853468164859545 62.3641380465225 Trimmed Mean ( 43 / 48 ) 5.33333333333333 0.0845949694203154 63.045514052193 Trimmed Mean ( 44 / 48 ) 5.3448275862069 0.083596284973809 63.9361855360133 Trimmed Mean ( 45 / 48 ) 5.35714285714286 0.0822909449996929 65.1000284072913 Trimmed Mean ( 46 / 48 ) 5.37037037037037 0.0806000222661606 66.629886932737 Trimmed Mean ( 47 / 48 ) 5.38461538461539 0.0784168683653452 68.6665445440692 Trimmed Mean ( 48 / 48 ) 5.4 0.0755928946018454 71.435285398744 Median 5 Midrange 5 Midmean - Weighted Average at Xnp 5.17857142857143 Midmean - Weighted Average at X(n+1)p 5.17857142857143 Midmean - Empirical Distribution Function 5.17857142857143 Midmean - Empirical Distribution Function - Averaging 5.17857142857143 Midmean - Empirical Distribution Function - Interpolation 5.17857142857143 Midmean - Closest Observation 5.17857142857143 Midmean - True Basic - Statistics Graphics Toolkit 5.17857142857143 Midmean - MS Excel (old versions) 5.17857142857143 Number of observations 146

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Dec/14/t1292320251n6g9kawbloi23y8/1rna21292320363.png (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/14/t1292320251n6g9kawbloi23y8/1rna21292320363.ps (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/14/t1292320251n6g9kawbloi23y8/2rna21292320363.png (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/14/t1292320251n6g9kawbloi23y8/2rna21292320363.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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