computation15

*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, 16 Nov 2010 11:42:55 +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/16/t1289907680t6ue9ilq28z1tph.htm/, Retrieved Tue, 16 Nov 2010 12:41:22 +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/16/t1289907680t6ue9ilq28z1tph.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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3 2 1 5 3 1 4 2 8 0 3 4 4 4 1 1 3 5 2 2 2 4 5 4 2 3 3 6 2 4 3 4 5 2 3 6 4 5 3 6 3 2 2 2 2 5 10 0 0 3 3 3 1 2 0 6 2 4 4 0 0 6 1 1 5 4 7 2 5 4 6 5 6 5 4 4 4 3 4 2 1 8 5 3 6 4 3 2 3 5 3 4 4 5 4 0 1 3 3 4 5 5 1 2 3 5 4 4 1 1 2 2 0 1 5 5 0 3 5 4 4 3 6 5 6 0 5 0 3 0 9 4 1 6 2 1 3 2 3 6 2 2 0 7 3 1 2 6 5 0 4 5 0 3 7 3

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 1 seconds R Server 'George Udny Yule' @ 72.249.76.132 Central Tendency - Ungrouped Data Measure Value S.E. Value/S.E. Arithmetic Mean 3.29487179487179 0.161470176069647 20.4054511803506 Geometric Mean 0 Harmonic Mean 0 Quadratic Mean 3.85971966565396 Winsorized Mean ( 1 / 52 ) 3.28846153846154 0.159872161342303 20.5693193289643 Winsorized Mean ( 2 / 52 ) 3.27564102564103 0.157149367591426 20.8441247702465 Winsorized Mean ( 3 / 52 ) 3.27564102564103 0.157149367591426 20.8441247702465 Winsorized Mean ( 4 / 52 ) 3.25 0.152623866629739 21.2941794213902 Winsorized Mean ( 5 / 52 ) 3.25 0.152623866629739 21.2941794213902 Winsorized Mean ( 6 / 52 ) 3.25 0.152623866629739 21.2941794213902 Winsorized Mean ( 7 / 52 ) 3.20512820512821 0.146285112210440 21.9101462664050 Winsorized Mean ( 8 / 52 ) 3.20512820512821 0.146285112210440 21.9101462664050 Winsorized Mean ( 9 / 52 ) 3.20512820512821 0.146285112210440 21.9101462664050 Winsorized Mean ( 10 / 52 ) 3.20512820512821 0.146285112210440 21.9101462664050 Winsorized Mean ( 11 / 52 ) 3.20512820512821 0.146285112210440 21.9101462664050 Winsorized Mean ( 12 / 52 ) 3.20512820512821 0.146285112210440 21.9101462664050 Winsorized Mean ( 13 / 52 ) 3.20512820512821 0.146285112210440 21.9101462664050 Winsorized Mean ( 14 / 52 ) 3.20512820512821 0.146285112210440 21.9101462664050 Winsorized Mean ( 15 / 52 ) 3.30128205128205 0.134102374321200 24.6176256609362 Winsorized Mean ( 16 / 52 ) 3.30128205128205 0.134102374321200 24.6176256609362 Winsorized Mean ( 17 / 52 ) 3.30128205128205 0.134102374321200 24.6176256609362 Winsorized Mean ( 18 / 52 ) 3.30128205128205 0.134102374321200 24.6176256609362 Winsorized Mean ( 19 / 52 ) 3.30128205128205 0.134102374321200 24.6176256609362 Winsorized Mean ( 20 / 52 ) 3.17307692307692 0.119332116269697 26.590301272338 Winsorized Mean ( 21 / 52 ) 3.17307692307692 0.119332116269697 26.590301272338 Winsorized Mean ( 22 / 52 ) 3.17307692307692 0.119332116269697 26.590301272338 Winsorized Mean ( 23 / 52 ) 3.17307692307692 0.119332116269697 26.590301272338 Winsorized Mean ( 24 / 52 ) 3.17307692307692 0.119332116269697 26.590301272338 Winsorized Mean ( 25 / 52 ) 3.17307692307692 0.119332116269697 26.590301272338 Winsorized Mean ( 26 / 52 ) 3.17307692307692 0.119332116269697 26.590301272338 Winsorized Mean ( 27 / 52 ) 3.17307692307692 0.119332116269697 26.590301272338 Winsorized Mean ( 28 / 52 ) 3.17307692307692 0.119332116269697 26.590301272338 Winsorized Mean ( 29 / 52 ) 3.17307692307692 0.119332116269697 26.590301272338 Winsorized Mean ( 30 / 52 ) 3.17307692307692 0.119332116269697 26.590301272338 Winsorized Mean ( 31 / 52 ) 3.37179487179487 0.0984654586343951 34.2434282900609 Winsorized Mean ( 32 / 52 ) 3.37179487179487 0.0984654586343951 34.2434282900609 Winsorized Mean ( 33 / 52 ) 3.37179487179487 0.0984654586343951 34.2434282900609 Winsorized Mean ( 34 / 52 ) 3.37179487179487 0.0984654586343951 34.2434282900609 Winsorized Mean ( 35 / 52 ) 3.37179487179487 0.0984654586343951 34.2434282900609 Winsorized Mean ( 36 / 52 ) 3.37179487179487 0.0984654586343951 34.2434282900609 Winsorized Mean ( 37 / 52 ) 3.37179487179487 0.0984654586343951 34.2434282900609 Winsorized Mean ( 38 / 52 ) 3.37179487179487 0.0984654586343951 34.2434282900609 Winsorized Mean ( 39 / 52 ) 3.37179487179487 0.0984654586343951 34.2434282900609 Winsorized Mean ( 40 / 52 ) 3.37179487179487 0.0984654586343951 34.2434282900609 Winsorized Mean ( 41 / 52 ) 3.37179487179487 0.0984654586343951 34.2434282900609 Winsorized Mean ( 42 / 52 ) 3.37179487179487 0.0984654586343951 34.2434282900609 Winsorized Mean ( 43 / 52 ) 3.09615384615385 0.0720598766247673 42.966405039468 Winsorized Mean ( 44 / 52 ) 3.09615384615385 0.0720598766247673 42.966405039468 Winsorized Mean ( 45 / 52 ) 3.09615384615385 0.0720598766247673 42.966405039468 Winsorized Mean ( 46 / 52 ) 3.09615384615385 0.0720598766247673 42.966405039468 Winsorized Mean ( 47 / 52 ) 3.09615384615385 0.0720598766247673 42.966405039468 Winsorized Mean ( 48 / 52 ) 3.09615384615385 0.0720598766247673 42.966405039468 Winsorized Mean ( 49 / 52 ) 3.09615384615385 0.0720598766247673 42.966405039468 Winsorized Mean ( 50 / 52 ) 3.09615384615385 0.0720598766247673 42.966405039468 Winsorized Mean ( 51 / 52 ) 3.09615384615385 0.0720598766247673 42.966405039468 Winsorized Mean ( 52 / 52 ) 3.09615384615385 0.0720598766247673 42.966405039468 Trimmed Mean ( 1 / 52 ) 3.27272727272727 0.156155081285072 20.9581862197150 Trimmed Mean ( 2 / 52 ) 3.25657894736842 0.152101782105785 21.4105245992681 Trimmed Mean ( 3 / 52 ) 3.24666666666667 0.149252175134073 21.7528934754230 Trimmed Mean ( 4 / 52 ) 3.23648648648649 0.146152936571260 22.1445190388526 Trimmed Mean ( 5 / 52 ) 3.23287671232877 0.144180480469968 22.4224298725524 Trimmed Mean ( 6 / 52 ) 3.22916666666667 0.14203768432516 22.7345769681396 Trimmed Mean ( 7 / 52 ) 3.22535211267606 0.139706717290818 23.0865929371317 Trimmed Mean ( 8 / 52 ) 3.22857142857143 0.13838848499542 23.3297692989289 Trimmed Mean ( 9 / 52 ) 3.23188405797101 0.136948447582655 23.5992748732724 Trimmed Mean ( 10 / 52 ) 3.23529411764706 0.135374609001359 23.8988252044707 Trimmed Mean ( 11 / 52 ) 3.23880597014925 0.133653337061383 24.232885174141 Trimmed Mean ( 12 / 52 ) 3.24242424242424 0.131769050218783 24.6068726839928 Trimmed Mean ( 13 / 52 ) 3.24615384615385 0.129703822264506 25.0274339605347 Trimmed Mean ( 14 / 52 ) 3.25 0.127436876453854 25.5028221848865 Trimmed Mean ( 15 / 52 ) 3.25396825396825 0.124943927962885 26.04342849646 Trimmed Mean ( 16 / 52 ) 3.25 0.123665178275293 26.2806397510310 Trimmed Mean ( 17 / 52 ) 3.24590163934426 0.122251091116637 26.5511056768191 Trimmed Mean ( 18 / 52 ) 3.24166666666667 0.120686547567540 26.8602154258536 Trimmed Mean ( 19 / 52 ) 3.23728813559322 0.118954086793353 27.2146020608525 Trimmed Mean ( 20 / 52 ) 3.23275862068966 0.117033394317224 27.6225314966695 Trimmed Mean ( 21 / 52 ) 3.23684210526316 0.116422526004378 27.8025414526862 Trimmed Mean ( 22 / 52 ) 3.24107142857143 0.115724409482938 28.0068089615034 Trimmed Mean ( 23 / 52 ) 3.24545454545455 0.114929258900944 28.2387146362073 Trimmed Mean ( 24 / 52 ) 3.25 0.114025890800869 28.5022987075425 Trimmed Mean ( 25 / 52 ) 3.25471698113208 0.113001459614739 28.8024331033292 Trimmed Mean ( 26 / 52 ) 3.25961538461538 0.111841127039556 29.1450512964031 Trimmed Mean ( 27 / 52 ) 3.26470588235294 0.110527643801489 29.537460223222 Trimmed Mean ( 28 / 52 ) 3.27 0.109040813413598 29.9887711548585 Trimmed Mean ( 29 / 52 ) 3.27551020408163 0.107356794015621 30.5105068954 Trimmed Mean ( 30 / 52 ) 3.28125 0.10544717331275 31.1174770922309 Trimmed Mean ( 31 / 52 ) 3.28125 0.103277717772156 31.7711319612897 Trimmed Mean ( 32 / 52 ) 3.28260869565217 0.102903485455090 31.8998786205817 Trimmed Mean ( 33 / 52 ) 3.27777777777778 0.102439382858810 31.9972425282518 Trimmed Mean ( 34 / 52 ) 3.27272727272727 0.101872839486771 32.1256115880845 Trimmed Mean ( 35 / 52 ) 3.26744186046512 0.101189124990388 32.2904448553684 Trimmed Mean ( 36 / 52 ) 3.26190476190476 0.100370866534256 32.4985214787548 Trimmed Mean ( 37 / 52 ) 3.25609756097561 0.099397425122457 32.7583693135322 Trimmed Mean ( 38 / 52 ) 3.25 0.0982440773491065 33.0808745696827 Trimmed Mean ( 39 / 52 ) 3.24358974358974 0.0968809229521843 33.4801697253712 Trimmed Mean ( 40 / 52 ) 3.23684210526316 0.0952713963676173 33.9749623567327 Trimmed Mean ( 41 / 52 ) 3.22972972972973 0.093370189756534 34.590587618504 Trimmed Mean ( 42 / 52 ) 3.22222222222222 0.0911202713056208 35.3622983783133 Trimmed Mean ( 43 / 52 ) 3.21428571428571 0.0884484553381272 36.3407783889262 Trimmed Mean ( 44 / 52 ) 3.22058823529412 0.0885092323554849 36.3870316077206 Trimmed Mean ( 45 / 52 ) 3.22058823529412 0.0884875626240188 36.3959424329305 Trimmed Mean ( 46 / 52 ) 3.234375 0.0883664232159712 36.6018548934028 Trimmed Mean ( 47 / 52 ) 3.24193548387097 0.0881248449514041 36.7879851097464 Trimmed Mean ( 48 / 52 ) 3.25 0.0877367660276714 37.0426236017746 Trimmed Mean ( 49 / 52 ) 3.25862068965517 0.0871694597736675 37.3825959013176 Trimmed Mean ( 50 / 52 ) 3.26785714285714 0.0863813330174845 37.8305940497086 Trimmed Mean ( 51 / 52 ) 3.27777777777778 0.0853187662269377 38.4180166067953 Trimmed Mean ( 52 / 52 ) 3.28846153846154 0.0839114417793667 39.1896679252405 Median 3 Midrange 5 Midmean - Weighted Average at Xnp 3.46666666666667 Midmean - Weighted Average at X(n+1)p 3.46666666666667 Midmean - Empirical Distribution Function 3.46666666666667 Midmean - Empirical Distribution Function - Averaging 3.46666666666667 Midmean - Empirical Distribution Function - Interpolation 3.46666666666667 Midmean - Closest Observation 3.46666666666667 Midmean - True Basic - Statistics Graphics Toolkit 3.46666666666667 Midmean - MS Excel (old versions) 3.46666666666667 Number of observations 156

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Nov/16/t1289907680t6ue9ilq28z1tph/1dduu1289907773.png (open in new window) http://www.freestatistics.org/blog/date/2010/Nov/16/t1289907680t6ue9ilq28z1tph/1dduu1289907773.ps (open in new window) http://www.freestatistics.org/blog/date/2010/Nov/16/t1289907680t6ue9ilq28z1tph/264tx1289907773.png (open in new window) http://www.freestatistics.org/blog/date/2010/Nov/16/t1289907680t6ue9ilq28z1tph/264tx1289907773.ps (open in new window)

Parameters (Session):

par1 = 12 ;

Parameters (R input):

par1 = 12 ;

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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