Opgave 5 OEFENING 2 - Centrummaten - Quincy Cabral MAR201a

*Unverified author*

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

Title produced by software: Central Tendency

Date of computation: Thu, 23 Apr 2009 04:38:07 -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/Apr/23/t12404831394kd0vu70xzhra5x.htm/, Retrieved Thu, 23 Apr 2009 12:39:01 +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/Apr/23/t12404831394kd0vu70xzhra5x.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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3,27 3,27 3,27 3,27 3,27 3,28 3,32 3,34 3,34 3,35 3,35 3,35 3,35 3,35 3,4 3,42 3,42 3,42 3,42 3,42 3,42 3,42 3,42 3,42 3,42 3,42 3,43 3,47 3,51 3,52 3,52 3,52 3,52 3,52 3,52 3,52 3,52 3,52 3,58 3,6 3,61 3,61 3,61 3,63 3,68 3,69 3,69 3,69 3,69 3,69 3,69 3,69 3,69 3,78 3,79 3,79 3,8 3,8 3,8 3,8 3,81 3,95 3,99 4 4,06 4,16 4,19 4,2 4,2 4,2 4,2 4,2 4,23 4,38 4,43 4,44 4,44 4,44 4,44 4,44 4,45 4,45 4,45 4,45 4,45 4,45 4,45 4,45 4,46 4,46 4,46 4,48 4,58 4,67 4,68 4,68 4,69 4,69 4,69 4,69 4,69 4,69 4,69 4,73 4,78 4,79 4,79 4,8 4,8 4,81 5,16 5,26 5,29 5,29 5,29 5,3 5,3 5,3 5,3 5,3 5,3 5,3 5,3 5,35 5,44 5,47 5,47 5,48 5,48 5,48 5,48

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 4.1681679389313 0.0612716870208285 68.0276346481921 Geometric Mean 4.11137339186683 Harmonic Mean 4.05688417191626 Quadratic Mean 4.22630719648773 Winsorized Mean ( 1 / 43 ) 4.1681679389313 0.0612716870208285 68.0276346481921 Winsorized Mean ( 2 / 43 ) 4.1681679389313 0.0612716870208285 68.0276346481921 Winsorized Mean ( 3 / 43 ) 4.1681679389313 0.0612716870208285 68.0276346481921 Winsorized Mean ( 4 / 43 ) 4.16786259541985 0.0612215644092908 68.078341931219 Winsorized Mean ( 5 / 43 ) 4.16824427480916 0.0611787213607832 68.1322554982506 Winsorized Mean ( 6 / 43 ) 4.16870229007634 0.060754929379287 68.6150462631854 Winsorized Mean ( 7 / 43 ) 4.16496183206107 0.0598876785853269 69.546222703004 Winsorized Mean ( 8 / 43 ) 4.16190839694656 0.0594303664937655 70.0299971628673 Winsorized Mean ( 9 / 43 ) 4.16259541984733 0.0593576486194754 70.1273638134238 Winsorized Mean ( 10 / 43 ) 4.16259541984733 0.0593576486194754 70.1273638134238 Winsorized Mean ( 11 / 43 ) 4.16259541984733 0.0593576486194754 70.1273638134238 Winsorized Mean ( 12 / 43 ) 4.16259541984733 0.0593576486194754 70.1273638134238 Winsorized Mean ( 13 / 43 ) 4.16259541984733 0.0593576486194754 70.1273638134239 Winsorized Mean ( 14 / 43 ) 4.16793893129771 0.0588078589102642 70.8738425192054 Winsorized Mean ( 15 / 43 ) 4.17022900763359 0.058580032997496 71.1885738919239 Winsorized Mean ( 16 / 43 ) 4.16900763358779 0.0583992630768015 71.3880178266133 Winsorized Mean ( 17 / 43 ) 4.16900763358779 0.0583992630768015 71.3880178266133 Winsorized Mean ( 18 / 43 ) 4.16900763358779 0.0583992630768015 71.3880178266133 Winsorized Mean ( 19 / 43 ) 4.16465648854962 0.057760647488039 72.1019702802332 Winsorized Mean ( 20 / 43 ) 4.1493893129771 0.0555784988361991 74.65817537113 Winsorized Mean ( 21 / 43 ) 4.09328244274809 0.0484093965473864 84.5555353853938 Winsorized Mean ( 22 / 43 ) 4.09160305343511 0.0482188708321988 84.8548085597826 Winsorized Mean ( 23 / 43 ) 4.09160305343511 0.0482188708321988 84.8548085597826 Winsorized Mean ( 24 / 43 ) 4.08977099236641 0.0480125822284875 85.18123380458 Winsorized Mean ( 25 / 43 ) 4.08977099236641 0.0480125822284875 85.18123380458 Winsorized Mean ( 26 / 43 ) 4.08977099236641 0.0475781602701283 85.9589981862782 Winsorized Mean ( 27 / 43 ) 4.08770992366412 0.0455745039112728 89.6929110105581 Winsorized Mean ( 28 / 43 ) 4.08770992366412 0.0437785980532752 93.3723350092137 Winsorized Mean ( 29 / 43 ) 4.08992366412214 0.043554825862802 93.9028817841088 Winsorized Mean ( 30 / 43 ) 4.08992366412214 0.043554825862802 93.9028817841088 Winsorized Mean ( 31 / 43 ) 4.08992366412214 0.043554825862802 93.9028817841088 Winsorized Mean ( 32 / 43 ) 4.08992366412214 0.043554825862802 93.9028817841088 Winsorized Mean ( 33 / 43 ) 4.08992366412214 0.043554825862802 93.9028817841088 Winsorized Mean ( 34 / 43 ) 4.08992366412214 0.043554825862802 93.9028817841088 Winsorized Mean ( 35 / 43 ) 4.08725190839695 0.0432724851092381 94.4538289880738 Winsorized Mean ( 36 / 43 ) 4.08725190839695 0.0432724851092381 94.4538289880738 Winsorized Mean ( 37 / 43 ) 4.08442748091603 0.0429756598969022 95.0404831645285 Winsorized Mean ( 38 / 43 ) 4.07572519083969 0.0385500613335939 105.725517673508 Winsorized Mean ( 39 / 43 ) 4.05190839694657 0.0350597367080331 115.571558072145 Winsorized Mean ( 40 / 43 ) 4.04885496183206 0.0341882875318640 118.428130044784 Winsorized Mean ( 41 / 43 ) 4.04885496183206 0.0341882875318640 118.428130044784 Winsorized Mean ( 42 / 43 ) 4.04885496183206 0.0341882875318640 118.428130044784 Winsorized Mean ( 43 / 43 ) 4.05213740458015 0.0332405258947081 121.903528765327 Trimmed Mean ( 1 / 43 ) 4.16496124031008 0.0609822620860793 68.2979131608965 Trimmed Mean ( 2 / 43 ) 4.16165354330709 0.0606559943743189 68.6107545715067 Trimmed Mean ( 3 / 43 ) 4.15824 0.0602892023714085 68.9715543818838 Trimmed Mean ( 4 / 43 ) 4.15471544715447 0.059877738200135 69.3866463904794 Trimmed Mean ( 5 / 43 ) 4.15115702479339 0.0594322530353921 69.8468729146337 Trimmed Mean ( 6 / 43 ) 4.14739495798319 0.0589440217093263 70.3615877863824 Trimmed Mean ( 7 / 43 ) 4.1434188034188 0.0584895801090382 70.8402897694684 Trimmed Mean ( 8 / 43 ) 4.13991304347826 0.0581480652540288 71.1960582934688 Trimmed Mean ( 9 / 43 ) 4.13672566371681 0.057840325031189 71.5197513410615 Trimmed Mean ( 10 / 43 ) 4.13333333333333 0.0574985429909528 71.8858795080025 Trimmed Mean ( 11 / 43 ) 4.12981651376147 0.057107177531756 72.3169431979889 Trimmed Mean ( 12 / 43 ) 4.12616822429907 0.0566603701581729 72.8228250676878 Trimmed Mean ( 13 / 43 ) 4.12238095238095 0.0561513724369054 73.4154976712827 Trimmed Mean ( 14 / 43 ) 4.11844660194175 0.0555723652886234 74.1096151036937 Trimmed Mean ( 15 / 43 ) 4.11386138613861 0.0549808193912321 74.8235735969162 Trimmed Mean ( 16 / 43 ) 4.10888888888889 0.0543323808091322 75.6250476731965 Trimmed Mean ( 17 / 43 ) 4.10381443298969 0.0536153098044261 76.5418394104086 Trimmed Mean ( 18 / 43 ) 4.09852631578947 0.0527953152976739 77.6304922639613 Trimmed Mean ( 19 / 43 ) 4.09301075268817 0.0518567778387061 78.9291375838847 Trimmed Mean ( 20 / 43 ) 4.08758241758242 0.0508663264477028 80.3593006030224 Trimmed Mean ( 21 / 43 ) 4.08303370786517 0.0500166990741217 81.6334101099787 Trimmed Mean ( 22 / 43 ) 4.08229885057471 0.0498928820897772 81.8212674751686 Trimmed Mean ( 23 / 43 ) 4.08164705882353 0.0497489065118693 82.044960281684 Trimmed Mean ( 24 / 43 ) 4.08096385542169 0.0495606955814063 82.3427477670985 Trimmed Mean ( 25 / 43 ) 4.08037037037037 0.049343981722556 82.6923614173025 Trimmed Mean ( 26 / 43 ) 4.07974683544304 0.0490712094709982 83.1393169115635 Trimmed Mean ( 27 / 43 ) 4.07909090909091 0.0487811739603734 83.6201874191156 Trimmed Mean ( 28 / 43 ) 4.07853333333333 0.0486405063589891 83.8505525257467 Trimmed Mean ( 29 / 43 ) 4.07794520547945 0.0486374305847405 83.8437630535291 Trimmed Mean ( 30 / 43 ) 4.07718309859155 0.0486179964769452 83.8616025760124 Trimmed Mean ( 31 / 43 ) 4.0763768115942 0.0485545417186115 83.9545934800098 Trimmed Mean ( 32 / 43 ) 4.0755223880597 0.0484388966749348 84.137390977541 Trimmed Mean ( 33 / 43 ) 4.07461538461538 0.0482611470399271 84.4284820094391 Trimmed Mean ( 34 / 43 ) 4.07365079365079 0.0480091632250977 84.851526666918 Trimmed Mean ( 35 / 43 ) 4.07262295081967 0.0476679668358034 85.4373119132224 Trimmed Mean ( 36 / 43 ) 4.07169491525424 0.0472568077236977 86.1610233822971 Trimmed Mean ( 37 / 43 ) 4.07070175438596 0.0467206944114264 87.1284514425025 Trimmed Mean ( 38 / 43 ) 4.06981818181818 0.0460752501973333 88.3298118705328 Trimmed Mean ( 39 / 43 ) 4.06943396226415 0.0458941287294886 88.6700341616769 Trimmed Mean ( 40 / 43 ) 4.07058823529412 0.0460855230254139 88.3268316831164 Trimmed Mean ( 41 / 43 ) 4.07204081632653 0.0463460618422476 87.8616360153084 Trimmed Mean ( 42 / 43 ) 4.0736170212766 0.0465651101675224 87.4821729535563 Trimmed Mean ( 43 / 43 ) 4.07533333333333 0.0467289627489843 87.2121505291045 Median 4.16 Midrange 4.375 Midmean - Weighted Average at Xnp 4.08621621621621 Midmean - Weighted Average at X(n+1)p 4.08621621621621 Midmean - Empirical Distribution Function 4.08621621621621 Midmean - Empirical Distribution Function - Averaging 4.08621621621621 Midmean - Empirical Distribution Function - Interpolation 4.08621621621621 Midmean - Closest Observation 4.08621621621621 Midmean - True Basic - Statistics Graphics Toolkit 4.08621621621621 Midmean - MS Excel (old versions) 4.08621621621621 Number of observations 131

Charts produced by software:

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Apr/23/t12404831394kd0vu70xzhra5x/17gvk1240483085.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Apr/23/t12404831394kd0vu70xzhra5x/17gvk1240483085.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Apr/23/t12404831394kd0vu70xzhra5x/2hyqc1240483085.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Apr/23/t12404831394kd0vu70xzhra5x/2hyqc1240483085.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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