central tendency bruin brood

*Unverified author*

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

Title produced by software: Central Tendency

Date of computation: Wed, 16 Dec 2009 08:21:25 -0700

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2009/Dec/16/t1260976942pxpmwncmfsa7xjh.htm/, Retrieved Wed, 16 Dec 2009 16:22:24 +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/2009/Dec/16/t1260976942pxpmwncmfsa7xjh.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:

KDGP1W52

Dataseries X:

» Textbox « » Textfile « » CSV «

1,38 1,38 1,38 1,38 1,38 1,38 1,38 1,38 1,38 1,38 1,38 1,38 1,38 1,38 1,38 1,38 1,38 1,38 1,38 1,38 1,38 1,38 1,38 1,43 1,43 1,43 1,43 1,43 1,43 1,43 1,43 1,43 1,43 1,43 1,43 1,43 1,43 1,43 1,43 1,43 1,43 1,43 1,44 1,48 1,48 1,48 1,48 1,48 1,48 1,48 1,48 1,48 1,48 1,48 1,48 1,48 1,48 1,48 1,48 1,48 1,48 1,48 1,48 1,48 1,48 1,48 1,48 1,48 1,48 1,48 1,48 1,48 1,48 1,57 1,58 1,58 1,58 1,58 1,59 1,6 1,6 1,61 1,61 1,61 1,62 1,63 1,63 1,64 1,64 1,64 1,64 1,64 1,65 1,65 1,65 1,65 1,65 1,66 1,66 1,67 1,68 1,68 1,68 1,68 1,69 1,7 1,7 1,71 1,72 1,73 1,74 1,74 1,75 1,75 1,75 1,76 1,79 1,83 1,84 1,85 1,87 1,87 1,87 1,88 1,88 1,88 1,88 1,89 1,89 1,89 1,9 1,89

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 1.56015151515152 0.0139087542550767 112.170470952282 Geometric Mean 1.55234071959777 Harmonic Mean 1.54485360334809 Quadratic Mean 1.56825226016580 Winsorized Mean ( 1 / 44 ) 1.56007575757576 0.0138948232788348 112.277481063911 Winsorized Mean ( 2 / 44 ) 1.56007575757576 0.0138948232788348 112.277481063911 Winsorized Mean ( 3 / 44 ) 1.56007575757576 0.0138948232788348 112.277481063911 Winsorized Mean ( 4 / 44 ) 1.56007575757576 0.0138948232788348 112.277481063911 Winsorized Mean ( 5 / 44 ) 1.55969696969697 0.0138270016615046 112.800808727700 Winsorized Mean ( 6 / 44 ) 1.55969696969697 0.0138270016615046 112.800808727700 Winsorized Mean ( 7 / 44 ) 1.55969696969697 0.0138270016615046 112.800808727700 Winsorized Mean ( 8 / 44 ) 1.55969696969697 0.0138270016615046 112.800808727700 Winsorized Mean ( 9 / 44 ) 1.55901515151515 0.013707672995978 113.733027624206 Winsorized Mean ( 10 / 44 ) 1.55901515151515 0.013707672995978 113.733027624206 Winsorized Mean ( 11 / 44 ) 1.55901515151515 0.013707672995978 113.733027624206 Winsorized Mean ( 12 / 44 ) 1.55719696969697 0.0133985139375135 116.221618080875 Winsorized Mean ( 13 / 44 ) 1.55621212121212 0.013235762432128 117.576311088406 Winsorized Mean ( 14 / 44 ) 1.55515151515152 0.0130637880788572 119.042922754421 Winsorized Mean ( 15 / 44 ) 1.55060606060606 0.0123620107742835 125.433158805504 Winsorized Mean ( 16 / 44 ) 1.54696969696970 0.0118431706725530 130.621244913311 Winsorized Mean ( 17 / 44 ) 1.54568181818182 0.0116686623892746 132.464353378032 Winsorized Mean ( 18 / 44 ) 1.54568181818182 0.0116686623892746 132.464353378032 Winsorized Mean ( 19 / 44 ) 1.54568181818182 0.0116686623892746 132.464353378032 Winsorized Mean ( 20 / 44 ) 1.54416666666667 0.0114686316831649 134.642624275169 Winsorized Mean ( 21 / 44 ) 1.54416666666667 0.0114686316831649 134.642624275169 Winsorized Mean ( 22 / 44 ) 1.5425 0.0112539992120621 137.062387417510 Winsorized Mean ( 23 / 44 ) 1.54946969696970 0.010155689720681 152.571586921799 Winsorized Mean ( 24 / 44 ) 1.54765151515152 0.00992561965888402 155.924926436837 Winsorized Mean ( 25 / 44 ) 1.54575757575758 0.00969230601476712 159.482952086167 Winsorized Mean ( 26 / 44 ) 1.54575757575758 0.00969230601476712 159.482952086167 Winsorized Mean ( 27 / 44 ) 1.54371212121212 0.0094471301779189 163.405403772279 Winsorized Mean ( 28 / 44 ) 1.54159090909091 0.0091999089455401 167.565887686121 Winsorized Mean ( 29 / 44 ) 1.54159090909091 0.0091999089455401 167.565887686121 Winsorized Mean ( 30 / 44 ) 1.54159090909091 0.0091999089455401 167.565887686121 Winsorized Mean ( 31 / 44 ) 1.54159090909091 0.0091999089455401 167.565887686121 Winsorized Mean ( 32 / 44 ) 1.53916666666667 0.0089250105806004 172.455444480058 Winsorized Mean ( 33 / 44 ) 1.53666666666667 0.0086490060098243 177.669742039858 Winsorized Mean ( 34 / 44 ) 1.53666666666667 0.0086490060098243 177.669742039858 Winsorized Mean ( 35 / 44 ) 1.53401515151515 0.00836429122322711 183.400495101759 Winsorized Mean ( 36 / 44 ) 1.53401515151515 0.00836429122322711 183.400495101759 Winsorized Mean ( 37 / 44 ) 1.53401515151515 0.00836429122322711 183.400495101759 Winsorized Mean ( 38 / 44 ) 1.53401515151515 0.00836429122322711 183.400495101759 Winsorized Mean ( 39 / 44 ) 1.53401515151515 0.00836429122322711 183.400495101759 Winsorized Mean ( 40 / 44 ) 1.53098484848485 0.00804715159058018 190.251771853905 Winsorized Mean ( 41 / 44 ) 1.53098484848485 0.00804715159058018 190.251771853905 Winsorized Mean ( 42 / 44 ) 1.53416666666667 0.00774704294407624 198.032549676230 Winsorized Mean ( 43 / 44 ) 1.54719696969697 0.00663069847882814 233.33845968674 Winsorized Mean ( 44 / 44 ) 1.54719696969697 0.00663069847882814 233.33845968674 Trimmed Mean ( 1 / 44 ) 1.55892307692308 0.0138072799555731 112.905878778379 Trimmed Mean ( 2 / 44 ) 1.557734375 0.013709323712008 113.625909470325 Trimmed Mean ( 3 / 44 ) 1.55650793650794 0.0135998680947466 114.450223021588 Trimmed Mean ( 4 / 44 ) 1.55524193548387 0.0134776790487948 115.393899042502 Trimmed Mean ( 5 / 44 ) 1.55393442622951 0.0133413479273149 116.475069437924 Trimmed Mean ( 6 / 44 ) 1.55266666666667 0.0132068934833616 117.564866304310 Trimmed Mean ( 7 / 44 ) 1.55135593220339 0.0130566219486212 118.817557734925 Trimmed Mean ( 8 / 44 ) 1.55 0.0128886361392211 120.260978993986 Trimmed Mean ( 9 / 44 ) 1.54859649122807 0.0127007263134693 121.929758425371 Trimmed Mean ( 10 / 44 ) 1.54723214285714 0.0125113910912072 123.665876286491 Trimmed Mean ( 11 / 44 ) 1.54581818181818 0.0122990142598028 125.686347634413 Trimmed Mean ( 12 / 44 ) 1.54435185185185 0.0120603888566077 128.051580277672 Trimmed Mean ( 13 / 44 ) 1.54301886792453 0.0118398794730218 130.323866171141 Trimmed Mean ( 14 / 44 ) 1.54173076923077 0.0116156090319536 132.729223667015 Trimmed Mean ( 15 / 44 ) 1.54049019607843 0.0113873381704096 135.280973746915 Trimmed Mean ( 16 / 44 ) 1.5396 0.0112266997768172 137.137362769709 Trimmed Mean ( 17 / 44 ) 1.53897959183673 0.0111116683296399 138.501217475289 Trimmed Mean ( 18 / 44 ) 1.5384375 0.0110017224777791 139.836057772524 Trimmed Mean ( 19 / 44 ) 1.53787234042553 0.0108755068520541 141.406957978704 Trimmed Mean ( 20 / 44 ) 1.53728260869565 0.0107307124952738 143.260068646209 Trimmed Mean ( 21 / 44 ) 1.53677777777778 0.0105891704717765 145.127305474378 Trimmed Mean ( 22 / 44 ) 1.53625 0.0104262756098714 147.344081192858 Trimmed Mean ( 23 / 44 ) 1.53581395348837 0.0102652443994020 149.612994462931 Trimmed Mean ( 24 / 44 ) 1.53488095238095 0.0101981150424657 150.506338278162 Trimmed Mean ( 25 / 44 ) 1.53402439024390 0.0101432969310606 151.235283820435 Trimmed Mean ( 26 / 44 ) 1.53325 0.0101019721724103 151.777293961222 Trimmed Mean ( 27 / 44 ) 1.53243589743590 0.0100484770665264 152.504293664636 Trimmed Mean ( 28 / 44 ) 1.53171052631579 0.0100094484449317 153.026466417476 Trimmed Mean ( 29 / 44 ) 1.53108108108108 0.0099862318539469 153.319200222249 Trimmed Mean ( 30 / 44 ) 1.53041666666667 0.00995183529915946 153.78235477791 Trimmed Mean ( 31 / 44 ) 1.52971428571429 0.0099042442928933 154.450379097769 Trimmed Mean ( 32 / 44 ) 1.52897058823529 0.0098410093780405 155.367252433178 Trimmed Mean ( 33 / 44 ) 1.52833333333333 0.00979411205391438 156.046135159594 Trimmed Mean ( 34 / 44 ) 1.5278125 0.00976527281110962 156.453642366433 Trimmed Mean ( 35 / 44 ) 1.52725806451613 0.00972158527429064 157.099693252196 Trimmed Mean ( 36 / 44 ) 1.52683333333333 0.00969737475881004 157.448110577165 Trimmed Mean ( 37 / 44 ) 1.52637931034483 0.00965746775067031 158.051711872285 Trimmed Mean ( 38 / 44 ) 1.52589285714286 0.0095983520829734 158.974461860974 Trimmed Mean ( 39 / 44 ) 1.52537037037037 0.00951556510369693 160.30265714621 Trimmed Mean ( 40 / 44 ) 1.52480769230769 0.00940335609922128 162.155689545137 Trimmed Mean ( 41 / 44 ) 1.5244 0.00930727167984523 163.785914114989 Trimmed Mean ( 42 / 44 ) 1.52395833333333 0.00917587987999538 166.083073586846 Trimmed Mean ( 43 / 44 ) 1.52326086956522 0.00904660156025234 168.379347694266 Trimmed Mean ( 44 / 44 ) 1.52159090909091 0.00901574369875655 168.770426481929 Median 1.48 Midrange 1.64 Midmean - Weighted Average at Xnp 1.51539473684210 Midmean - Weighted Average at X(n+1)p 1.51539473684210 Midmean - Empirical Distribution Function 1.51539473684210 Midmean - Empirical Distribution Function - Averaging 1.51539473684210 Midmean - Empirical Distribution Function - Interpolation 1.51539473684210 Midmean - Closest Observation 1.51539473684210 Midmean - True Basic - Statistics Graphics Toolkit 1.51539473684210 Midmean - MS Excel (old versions) 1.51740259740260 Number of observations 132

Charts produced by software:

http://www.freestatistics.org/blog/date/2009/Dec/16/t1260976942pxpmwncmfsa7xjh/1i0fn1260976882.png (open in new window) http://www.freestatistics.org/blog/date/2009/Dec/16/t1260976942pxpmwncmfsa7xjh/1i0fn1260976882.ps (open in new window) http://www.freestatistics.org/blog/date/2009/Dec/16/t1260976942pxpmwncmfsa7xjh/24x0h1260976882.png (open in new window) http://www.freestatistics.org/blog/date/2009/Dec/16/t1260976942pxpmwncmfsa7xjh/24x0h1260976882.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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