Opgave 5, oefening 2, stap 1, Sara Vandenberghe

*Unverified author*

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

Title produced by software: Central Tendency

Date of computation: Thu, 02 Jul 2009 14:26:22 -0600

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2009/Jul/02/t1246566448rly43omt0m41m0v.htm/, Retrieved Thu, 02 Jul 2009 22:27:30 +0200

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/Jul/02/t1246566448rly43omt0m41m0v.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:

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9,26 9,29 9,28 9,31 9,27 9,27 9,28 9,25 9,32 9,33 9,31 9,3 9,29 9,33 9,35 9,35 9,37 9,37 9,35 9,33 9,34 9,37 9,33 9,31 9,26 9,27 9,29 9,27 9,29 9,31 9,33 9,35 9,34 9,35 9,38 9,43 9,47 9,5 9,55 9,58 9,61 9,57 9,61 9,65 9,62 9,63 9,62 9,63 9,65 9,72 9,75 9,77 9,78 9,82 9,84 9,9 9,94 9,96 10,03 10,03 10,12 10,12 10,05 10,14 10,17 10,2 10,2 10,35 10,43 10,52 10,57 10,57 10,57 10,65 10,57 10,61 10,63 10,71 10,72 10,77 10,79 10,82 10,9 10,83 10,92 10,91 10,88 10,87 11 10,99 11,03 11,04 10,99 10,9 11 10,99 10,92 10,98 11,15 11,19 11,33 11,38 11,4 11,45 11,56 11,61 11,82 11,77 11,85 11,82 11,92 11,86 11,87 11,94 11,86 11,92 11,83 11,91 11,93 11,99 11,96 12,12 11,85 12,01 12,1 12,21 12,31 12,31 12,39 12,35 12,41 12,51

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 'Gwilym Jenkins' @ 72.249.127.135 Central Tendency - Ungrouped Data Measure Value S.E. Value/S.E. Arithmetic Mean 10.4392424242424 0.0894799934354902 116.665659254529 Geometric Mean 10.3900835857682 Harmonic Mean 10.3421788299117 Quadratic Mean 10.4893591825529 Winsorized Mean ( 1 / 44 ) 10.4385606060606 0.0893416129783534 116.838730106538 Winsorized Mean ( 2 / 44 ) 10.4382575757576 0.0892908095626787 116.901813600764 Winsorized Mean ( 3 / 44 ) 10.4375757575758 0.089117691861295 117.121253250377 Winsorized Mean ( 4 / 44 ) 10.4363636363636 0.0889209267472694 117.366788877784 Winsorized Mean ( 5 / 44 ) 10.4363636363636 0.0889209267472694 117.366788877784 Winsorized Mean ( 6 / 44 ) 10.4318181818182 0.0882055551827184 118.267133631307 Winsorized Mean ( 7 / 44 ) 10.4275757575758 0.0874324114367899 119.264419066315 Winsorized Mean ( 8 / 44 ) 10.4263636363636 0.0872541172134953 119.494230981126 Winsorized Mean ( 9 / 44 ) 10.4209090909091 0.0863052385441093 120.744803753519 Winsorized Mean ( 10 / 44 ) 10.4193939393939 0.0860932576452977 121.024505569549 Winsorized Mean ( 11 / 44 ) 10.4168939393939 0.0857474607491883 121.483410101943 Winsorized Mean ( 12 / 44 ) 10.4150757575758 0.0854988015340182 121.815459055667 Winsorized Mean ( 13 / 44 ) 10.4150757575758 0.0852663497944229 122.147550384020 Winsorized Mean ( 14 / 44 ) 10.4150757575758 0.0850172109918964 122.505497840531 Winsorized Mean ( 15 / 44 ) 10.4150757575758 0.0850172109918964 122.505497840531 Winsorized Mean ( 16 / 44 ) 10.4138636363636 0.0848537438784419 122.727214620985 Winsorized Mean ( 17 / 44 ) 10.4087121212121 0.0841656610083932 123.669344439345 Winsorized Mean ( 18 / 44 ) 10.4087121212121 0.0838496890855235 124.13536931062 Winsorized Mean ( 19 / 44 ) 10.4101515151515 0.0837074635263617 124.363480585851 Winsorized Mean ( 20 / 44 ) 10.4086363636364 0.0835074821132937 124.643158914971 Winsorized Mean ( 21 / 44 ) 10.4086363636364 0.0835074821132937 124.643158914971 Winsorized Mean ( 22 / 44 ) 10.4053030303030 0.0830696804984329 125.259938016727 Winsorized Mean ( 23 / 44 ) 10.4035606060606 0.0828419097431833 125.583302440908 Winsorized Mean ( 24 / 44 ) 10.4053787878788 0.0826625376709495 125.877804880597 Winsorized Mean ( 25 / 44 ) 10.3959090909091 0.0814340553635411 127.660461516982 Winsorized Mean ( 26 / 44 ) 10.3663636363636 0.0772695975744265 134.158374856019 Winsorized Mean ( 27 / 44 ) 10.3561363636364 0.0760231048105707 136.223538744453 Winsorized Mean ( 28 / 44 ) 10.3328030303030 0.0732536142511425 141.055197561694 Winsorized Mean ( 29 / 44 ) 10.3218181818182 0.0719861176587198 143.386232200395 Winsorized Mean ( 30 / 44 ) 10.3172727272727 0.0714682838855064 144.361556852284 Winsorized Mean ( 31 / 44 ) 10.3102272727273 0.0696609934781665 148.005745510344 Winsorized Mean ( 32 / 44 ) 10.2762878787879 0.0659676286372708 155.777736612195 Winsorized Mean ( 33 / 44 ) 10.2662878787879 0.0649193351058674 158.139140859131 Winsorized Mean ( 34 / 44 ) 10.2405303030303 0.0617732148772085 165.776223940849 Winsorized Mean ( 35 / 44 ) 10.2511363636364 0.0601148418764 170.525880858397 Winsorized Mean ( 36 / 44 ) 10.2538636363636 0.0581798132913444 176.244354463907 Winsorized Mean ( 37 / 44 ) 10.2622727272727 0.0573205182303051 179.033146316656 Winsorized Mean ( 38 / 44 ) 10.2737878787879 0.0555914230665473 184.808866405333 Winsorized Mean ( 39 / 44 ) 10.2796969696970 0.0550067751167365 186.880560583331 Winsorized Mean ( 40 / 44 ) 10.2827272727273 0.0547089845659763 187.953173583889 Winsorized Mean ( 41 / 44 ) 10.2889393939394 0.0534942839702062 192.33717381225 Winsorized Mean ( 42 / 44 ) 10.2698484848485 0.0516350725539859 198.892883787683 Winsorized Mean ( 43 / 44 ) 10.2731060606061 0.0513179451013565 200.185452482869 Winsorized Mean ( 44 / 44 ) 10.2697727272727 0.050997846165744 201.376597236985 Trimmed Mean ( 1 / 44 ) 10.4324615384615 0.0889691216652175 117.259351820038 Trimmed Mean ( 2 / 44 ) 10.426171875 0.0885457142802156 117.749028959266 Trimmed Mean ( 3 / 44 ) 10.4198412698413 0.088094825109857 118.279833768299 Trimmed Mean ( 4 / 44 ) 10.4135483870968 0.087651722532989 118.805975355219 Trimmed Mean ( 5 / 44 ) 10.4073770491803 0.0872084185628805 119.339132857641 Trimmed Mean ( 6 / 44 ) 10.401 0.0867039943315948 119.959871285998 Trimmed Mean ( 7 / 44 ) 10.3952542372881 0.0862885570538502 120.470831732657 Trimmed Mean ( 8 / 44 ) 10.39 0.0859612722674291 120.868383237469 Trimmed Mean ( 9 / 44 ) 10.3847368421053 0.085610605401893 121.301990487684 Trimmed Mean ( 10 / 44 ) 10.38 0.0853545109258587 121.610444338629 Trimmed Mean ( 11 / 44 ) 10.3752727272727 0.0850792408044507 121.948346378873 Trimmed Mean ( 12 / 44 ) 10.3706481481481 0.0847990797375552 122.296706287902 Trimmed Mean ( 13 / 44 ) 10.3660377358491 0.0844967852937768 122.679669999381 Trimmed Mean ( 14 / 44 ) 10.36125 0.0841644660584303 123.107179136701 Trimmed Mean ( 15 / 44 ) 10.3562745098039 0.0837986142910961 123.585271635026 Trimmed Mean ( 16 / 44 ) 10.3511 0.0833637393013475 124.167894659599 Trimmed Mean ( 17 / 44 ) 10.3458163265306 0.0828709707964407 124.842465668026 Trimmed Mean ( 18 / 44 ) 10.3407291666667 0.0823748711885246 125.532568579084 Trimmed Mean ( 19 / 44 ) 10.3354255319149 0.0818260852886642 126.309666354608 Trimmed Mean ( 20 / 44 ) 10.3297826086957 0.0811953779438672 127.221313211165 Trimmed Mean ( 21 / 44 ) 10.324 0.0804794931270229 128.281126021822 Trimmed Mean ( 22 / 44 ) 10.3179545454545 0.0796416607350192 129.554738691149 Trimmed Mean ( 23 / 44 ) 10.3118604651163 0.078716536177572 130.999926646345 Trimmed Mean ( 24 / 44 ) 10.3055952380952 0.0776640733915503 132.694498087149 Trimmed Mean ( 25 / 44 ) 10.2989024390244 0.0764536938410697 134.707715502060 Trimmed Mean ( 26 / 44 ) 10.2925 0.075196683033499 136.874388401080 Trimmed Mean ( 27 / 44 ) 10.2876923076923 0.0742492501740771 138.556177787289 Trimmed Mean ( 28 / 44 ) 10.2832894736842 0.0732830102035085 140.322967699161 Trimmed Mean ( 29 / 44 ) 10.2801351351351 0.0724796166224699 141.834844252586 Trimmed Mean ( 30 / 44 ) 10.2775 0.071670419707386 143.399467199448 Trimmed Mean ( 31 / 44 ) 10.275 0.070758022319503 145.213216299403 Trimmed Mean ( 32 / 44 ) 10.2727941176471 0.0698832104834417 146.999458762432 Trimmed Mean ( 33 / 44 ) 10.2725757575758 0.0692848283597642 148.265875816781 Trimmed Mean ( 34 / 44 ) 10.27296875 0.0686627078173914 149.61496679276 Trimmed Mean ( 35 / 44 ) 10.275 0.0682623140682035 150.522292428203 Trimmed Mean ( 36 / 44 ) 10.2765 0.0679376687571644 151.263653698984 Trimmed Mean ( 37 / 44 ) 10.2779310344828 0.067728131046626 151.752763226364 Trimmed Mean ( 38 / 44 ) 10.2789285714286 0.0675122300471324 152.252837215606 Trimmed Mean ( 39 / 44 ) 10.2792592592593 0.06739997732067 152.511316292489 Trimmed Mean ( 40 / 44 ) 10.2792307692308 0.0672481313717334 152.855262437098 Trimmed Mean ( 41 / 44 ) 10.279 0.067003045925281 153.410936145541 Trimmed Mean ( 42 / 44 ) 10.2783333333333 0.0667776115848976 153.918852282789 Trimmed Mean ( 43 / 44 ) 10.2789130434783 0.0666726289079308 154.169907679395 Trimmed Mean ( 44 / 44 ) 10.2793181818182 0.0664585882019811 154.672533075443 Median 10.2 Midrange 10.88 Midmean - Weighted Average at Xnp 10.2460294117647 Midmean - Weighted Average at X(n+1)p 10.2460294117647 Midmean - Empirical Distribution Function 10.2460294117647 Midmean - Empirical Distribution Function - Averaging 10.2460294117647 Midmean - Empirical Distribution Function - Interpolation 10.2460294117647 Midmean - Closest Observation 10.2460294117647 Midmean - True Basic - Statistics Graphics Toolkit 10.2460294117647 Midmean - MS Excel (old versions) 10.2597101449275 Number of observations 132

Charts produced by software:

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jul/02/t1246566448rly43omt0m41m0v/1dvqd1246566379.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jul/02/t1246566448rly43omt0m41m0v/1dvqd1246566379.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jul/02/t1246566448rly43omt0m41m0v/2kvsh1246566379.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jul/02/t1246566448rly43omt0m41m0v/2kvsh1246566379.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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