GuyVanHasseltBloemkoolCentrummaten

*Unverified author*

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

Title produced by software: Central Tendency

Date of computation: Mon, 17 Aug 2009 08:25:38 -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/Aug/17/t12505192183il411jehw5bhej.htm/, Retrieved Mon, 17 Aug 2009 16:26:58 +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/Aug/17/t12505192183il411jehw5bhej.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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0,8800 1,0300 0,6900 0,7100 1,1100 1,0500 1,0300 0,6500 0,5900 0,7700 0,9000 1,2600 0,9600 0,8300 0,8700 0,7900 1,1200 0,8800 0,6400 0,6400 0,5800 0,5000 0,9900 1,0700 0,8900 0,8900 0,8300 0,8600 0,9000 1,1200 0,8800 0,8800 0,8900 0,8200 0,8800 0,8100 0,8800 0,7600 1,1300 0,8500 1,4500 1,5500 0,7100 0,8100 0,8300 0,7300 0,9000 0,9400 1,7800 0,8800 1,0400 0,8300 1,4100 0,9600 1,3000 0,8300 1,4000 0,9100 0,8700 0,9700 1,1900 1,2300 1,3300 1,1700 1,0900 0,6300 0,8900 0,6300 1,5100 0,9700 0,8400 0,9200 0,9500 0,7300 1,0200 0,7900 1,2700 0,9500 0,7500 0,5200 0,9500 0,8200 0,7600 1,2400 0,9400 1,0400 1,8100 0,9500 1,3900 0,8600 1,1500 1,5100 0,6000 0,7200 1,1000 1,6200 1,8400 1,7300 1,3600 1,0700 1,0000 1,4900 0,9000 1,4300 1,5400 0,8100 1,6100 1,3000 1,4000 1,0300 0,7900 1,1100 1,1500 1,0300 1,5900 1,1100 1,3300 0,9300 1,0700 1,1400 1,1200 0,8600 0,8200 1,0200 1,0700 1,3100 0,9800 0,8900 etc...

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 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 Central Tendency - Ungrouped Data Measure Value S.E. Value/S.E. Arithmetic Mean 1.01462121212121 0.0246005340310508 41.2438693745655 Geometric Mean 0.978545921720826 Harmonic Mean 0.944941351528161 Quadratic Mean 1.05296514949955 Winsorized Mean ( 1 / 44 ) 1.01454545454545 0.0245195243471796 41.3770446840726 Winsorized Mean ( 2 / 44 ) 1.015 0.0242763648886008 41.8102135413447 Winsorized Mean ( 3 / 44 ) 1.01409090909091 0.0239792672384263 42.29032100972 Winsorized Mean ( 4 / 44 ) 1.01106060606061 0.0232241731908737 43.5348375053421 Winsorized Mean ( 5 / 44 ) 1.01181818181818 0.0229998687959071 43.9923458171309 Winsorized Mean ( 6 / 44 ) 1.01090909090909 0.0228215716608776 44.2962082511637 Winsorized Mean ( 7 / 44 ) 1.00931818181818 0.0223529696704047 45.1536505753202 Winsorized Mean ( 8 / 44 ) 1.00871212121212 0.0222417596971964 45.35217244251 Winsorized Mean ( 9 / 44 ) 1.00734848484848 0.0217892827137728 46.2313742990608 Winsorized Mean ( 10 / 44 ) 1.01037878787879 0.0214265162087265 47.1555328003945 Winsorized Mean ( 11 / 44 ) 1.01037878787879 0.0209461061475905 48.2370699718341 Winsorized Mean ( 12 / 44 ) 1.00674242424242 0.020325393746546 49.5312630493816 Winsorized Mean ( 13 / 44 ) 1.00575757575758 0.0198921802295060 50.5604495914298 Winsorized Mean ( 14 / 44 ) 1.00469696969697 0.0194352485181807 51.694577960098 Winsorized Mean ( 15 / 44 ) 1.00356060606061 0.0192554964877330 52.1181371095748 Winsorized Mean ( 16 / 44 ) 1.00598484848485 0.0189993303291181 52.9484371848143 Winsorized Mean ( 17 / 44 ) 1.00598484848485 0.0186652270050412 53.8962021845834 Winsorized Mean ( 18 / 44 ) 1.00189393939394 0.0180337324244220 55.5566599201135 Winsorized Mean ( 19 / 44 ) 0.999015151515152 0.0172431616380664 57.9368895614655 Winsorized Mean ( 20 / 44 ) 1.00053030303030 0.0170917278712005 58.5388622244679 Winsorized Mean ( 21 / 44 ) 0.998939393939394 0.0164728228561283 60.6416643136404 Winsorized Mean ( 22 / 44 ) 0.997272727272727 0.0162340656262667 61.430867056441 Winsorized Mean ( 23 / 44 ) 0.997272727272727 0.0162340656262667 61.430867056441 Winsorized Mean ( 24 / 44 ) 0.993636363636364 0.0152927605632557 64.9742967939874 Winsorized Mean ( 25 / 44 ) 0.991742424242424 0.0150331179670043 65.9705076763959 Winsorized Mean ( 26 / 44 ) 0.989772727272727 0.0143114241862200 69.1596248139821 Winsorized Mean ( 27 / 44 ) 0.987727272727273 0.0140401883889222 70.3500013936136 Winsorized Mean ( 28 / 44 ) 0.979242424242424 0.0129531537346645 75.5987649264005 Winsorized Mean ( 29 / 44 ) 0.977045454545455 0.0121971708438694 80.1042690187902 Winsorized Mean ( 30 / 44 ) 0.9725 0.0116583402758501 83.416676558541 Winsorized Mean ( 31 / 44 ) 0.9725 0.0116583402758501 83.416676558541 Winsorized Mean ( 32 / 44 ) 0.9725 0.0111388181992842 87.3072872364943 Winsorized Mean ( 33 / 44 ) 0.97 0.0108546428258467 89.362682454209 Winsorized Mean ( 34 / 44 ) 0.967424242424243 0.0105677491191286 91.5449668154131 Winsorized Mean ( 35 / 44 ) 0.967424242424242 0.0105677491191286 91.5449668154131 Winsorized Mean ( 36 / 44 ) 0.967424242424242 0.0105677491191286 91.5449668154131 Winsorized Mean ( 37 / 44 ) 0.967424242424242 0.00998473343804614 96.8903424840506 Winsorized Mean ( 38 / 44 ) 0.97030303030303 0.00970829419124988 99.9457794735524 Winsorized Mean ( 39 / 44 ) 0.973257575757576 0.00943309605000447 103.174776404096 Winsorized Mean ( 40 / 44 ) 0.970227272727273 0.00910045329436815 106.613070947543 Winsorized Mean ( 41 / 44 ) 0.967121212121212 0.00876514604202271 110.337147548318 Winsorized Mean ( 42 / 44 ) 0.963939393939394 0.00779891091864589 123.599231225321 Winsorized Mean ( 43 / 44 ) 0.963939393939394 0.00779891091864589 123.599231225321 Winsorized Mean ( 44 / 44 ) 0.967272727272727 0.00749746731011773 129.013263714722 Trimmed Mean ( 1 / 44 ) 1.01223076923077 0.0238236077461396 42.4885592483275 Trimmed Mean ( 2 / 44 ) 1.00984375 0.0230523263187941 43.8065875016133 Trimmed Mean ( 3 / 44 ) 1.00714285714286 0.0223390489183395 45.0844107474975 Trimmed Mean ( 4 / 44 ) 1.00467741935484 0.0216704798488037 46.3615677347496 Trimmed Mean ( 5 / 44 ) 1.00295081967213 0.0211761883119648 47.3621978090105 Trimmed Mean ( 6 / 44 ) 1.001 0.0206878900692702 48.3857946193792 Trimmed Mean ( 7 / 44 ) 0.999152542372881 0.0201880110775522 49.4923714146303 Trimmed Mean ( 8 / 44 ) 0.9975 0.0197320411583764 50.5522967438445 Trimmed Mean ( 9 / 44 ) 0.995877192982456 0.0192459188823735 51.7448503793984 Trimmed Mean ( 10 / 44 ) 0.994375 0.0187858542863426 52.9321150288553 Trimmed Mean ( 11 / 44 ) 0.992454545454545 0.0183298415697076 54.1441965922227 Trimmed Mean ( 12 / 44 ) 0.990462962962963 0.0178952106593465 55.3479353675925 Trimmed Mean ( 13 / 44 ) 0.98877358490566 0.0175050770867458 56.4849603349831 Trimmed Mean ( 14 / 44 ) 0.987115384615385 0.0171301050223134 57.6245961907171 Trimmed Mean ( 15 / 44 ) 0.985490196078431 0.0167725007735057 58.7563064915839 Trimmed Mean ( 16 / 44 ) 0.9839 0.0163940707438865 60.0156004796371 Trimmed Mean ( 17 / 44 ) 0.98204081632653 0.0159968958589898 61.3894611168988 Trimmed Mean ( 18 / 44 ) 0.980104166666667 0.0155896493380678 62.8689039382935 Trimmed Mean ( 19 / 44 ) 0.978404255319149 0.0152139498109885 64.3096807518374 Trimmed Mean ( 20 / 44 ) 0.976847826086957 0.0148900488064940 65.6040714695928 Trimmed Mean ( 21 / 44 ) 0.975111111111111 0.0145358864922634 67.0830163423541 Trimmed Mean ( 22 / 44 ) 0.97340909090909 0.0142092938771738 68.50509950201 Trimmed Mean ( 23 / 44 ) 0.971744186046512 0.0138648862751107 70.0867044103288 Trimmed Mean ( 24 / 44 ) 0.97 0.0134657083439684 72.034829154345 Trimmed Mean ( 25 / 44 ) 0.968414634146341 0.0131301931693602 73.7547895644197 Trimmed Mean ( 26 / 44 ) 0.966875 0.0127755623002906 75.6816003298738 Trimmed Mean ( 27 / 44 ) 0.965384615384615 0.0124579777270375 77.4912780016811 Trimmed Mean ( 28 / 44 ) 0.963947368421053 0.0121237463773973 79.509034453094 Trimmed Mean ( 29 / 44 ) 0.962972972972973 0.0118841902292822 81.0297508197274 Trimmed Mean ( 30 / 44 ) 0.962083333333333 0.0116983765910907 82.2407558725745 Trimmed Mean ( 31 / 44 ) 0.961428571428571 0.0115475176619314 83.2584629507088 Trimmed Mean ( 32 / 44 ) 0.960735294117647 0.0113649573396619 84.5348790500808 Trimmed Mean ( 33 / 44 ) 0.96 0.0112110501598934 85.6298015179988 Trimmed Mean ( 34 / 44 ) 0.959375 0.0110618638279996 86.728151323979 Trimmed Mean ( 35 / 44 ) 0.958870967741935 0.0109179547800420 87.8251455570004 Trimmed Mean ( 36 / 44 ) 0.958333333333333 0.0107387220216902 89.2409107338547 Trimmed Mean ( 37 / 44 ) 0.957758620689655 0.0105161504100292 91.075021119539 Trimmed Mean ( 38 / 44 ) 0.957142857142857 0.0103281052866736 92.6736153995118 Trimmed Mean ( 39 / 44 ) 0.956296296296296 0.0101294772823536 94.4072699548125 Trimmed Mean ( 40 / 44 ) 0.955192307692308 0.00991475881091853 96.3404482053977 Trimmed Mean ( 41 / 44 ) 0.9542 0.00970205111913802 98.3503372928812 Trimmed Mean ( 42 / 44 ) 0.953333333333333 0.00949212688564785 100.434111850609 Trimmed Mean ( 43 / 44 ) 0.952608695652174 0.00939439026057519 101.401865286555 Trimmed Mean ( 44 / 44 ) 0.951818181818182 0.00925486402754597 102.845182704490 Median 0.95 Midrange 1.17 Midmean - Weighted Average at Xnp 0.958059701492537 Midmean - Weighted Average at X(n+1)p 0.958059701492537 Midmean - Empirical Distribution Function 0.958059701492537 Midmean - Empirical Distribution Function - Averaging 0.958059701492537 Midmean - Empirical Distribution Function - Interpolation 0.958059701492537 Midmean - Closest Observation 0.958059701492537 Midmean - True Basic - Statistics Graphics Toolkit 0.958059701492537 Midmean - MS Excel (old versions) 0.960735294117647 Number of observations 132

Charts produced by software:

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Aug/17/t12505192183il411jehw5bhej/1bbmh1250519132.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Aug/17/t12505192183il411jehw5bhej/1bbmh1250519132.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Aug/17/t12505192183il411jehw5bhej/2o48m1250519132.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Aug/17/t12505192183il411jehw5bhej/2o48m1250519132.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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