*Unverified author*

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

Title produced by software: Central Tendency

Date of computation: Wed, 13 Jan 2010 06:25:36 -0700

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2010/Jan/13/t1263389184qaaw8te8jakadbt.htm/, Retrieved Wed, 13 Jan 2010 14:26:26 +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/Jan/13/t1263389184qaaw8te8jakadbt.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:

KDGP1W51

Dataseries X:

» Textbox « » Textfile « » CSV «

2,46 2,46 2,45 2,45 2,46 2,43 2,44 2,44 2,43 2,43 2,42 2,43 2,43 2,42 2,41 2,42 2,39 2,4 2,39 2,4 2,41 2,41 2,41 2,41 2,42 2,43 2,43 2,43 2,44 2,42 2,44 2,42 2,42 2,42 2,43 2,44 2,43 2,44 2,44 2,45 2,45 2,43 2,44 2,45 2,46 2,44 2,43 2,42 2,41 2,43 2,41 2,43 2,43 2,44 2,43 2,44 2,43 2,44 2,44 2,43 2,43 2,43 2,43 2,44 2,47 2,48 2,49 2,5 2,51 2,49 2,49 2,48 2,48 2,48 2,5 2,5 2,5 2,5 2,5 2,48 2,49 2,48 2,5 2,5 2,49 2,48 2,47 2,46 2,43 2,42 2,43 2,45 2,45 2,46 2,44 2,45 2,45 2,42 2,41 2,39 2,39 2,38 2,37 2,37 2,38 2,39 2,41 2,42 2,48 2,53 2,56 2,56 2,53 2,57 2,56 2,57 2,58 2,57 2,6 2,63 2,72 2,83 2,9 2,92 2,94 2,95 2,98 3,02 3,16 3,2 3,18 3,17 3,19

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 2.50706766917293 0.0155677039324670 161.042866696889 Geometric Mean 2.50138653037549 Harmonic Mean 2.49632349692810 Quadratic Mean 2.51343966455700 Winsorized Mean ( 1 / 44 ) 2.50699248120301 0.0155425114561667 161.299059567901 Winsorized Mean ( 2 / 44 ) 2.50699248120301 0.0154830274645147 161.918751804112 Winsorized Mean ( 3 / 44 ) 2.50676691729323 0.0154091125034877 162.680810898477 Winsorized Mean ( 4 / 44 ) 2.50676691729323 0.0152933452111922 163.912269204431 Winsorized Mean ( 5 / 44 ) 2.50150375939850 0.0136808895091046 182.846572785619 Winsorized Mean ( 6 / 44 ) 2.4996992481203 0.0131724198056540 189.767657347767 Winsorized Mean ( 7 / 44 ) 2.49812030075188 0.0127421410944637 196.051847349051 Winsorized Mean ( 8 / 44 ) 2.49751879699248 0.0125812040035545 198.511906832356 Winsorized Mean ( 9 / 44 ) 2.49684210526316 0.0121804651921530 204.987417629312 Winsorized Mean ( 10 / 44 ) 2.49533834586466 0.0117869892435253 211.702776197524 Winsorized Mean ( 11 / 44 ) 2.49037593984962 0.0102561219985344 242.818478583376 Winsorized Mean ( 12 / 44 ) 2.48045112781955 0.00785119108361697 315.933098736508 Winsorized Mean ( 13 / 44 ) 2.47165413533835 0.00592654632720525 417.04797345335 Winsorized Mean ( 14 / 44 ) 2.46849624060150 0.0053094020224476 464.92923876643 Winsorized Mean ( 15 / 44 ) 2.46624060150376 0.00489884170769008 503.433413174448 Winsorized Mean ( 16 / 44 ) 2.46503759398496 0.00469097928234266 525.484647366409 Winsorized Mean ( 17 / 44 ) 2.46503759398496 0.00469097928234266 525.484647366408 Winsorized Mean ( 18 / 44 ) 2.46503759398496 0.00469097928234266 525.484647366409 Winsorized Mean ( 19 / 44 ) 2.46360902255639 0.00445265510181709 553.289883501422 Winsorized Mean ( 20 / 44 ) 2.46511278195489 0.00432452160849337 570.031324878433 Winsorized Mean ( 21 / 44 ) 2.46511278195489 0.00432452160849337 570.031324878433 Winsorized Mean ( 22 / 44 ) 2.46015037593985 0.00353671779726154 695.602679366934 Winsorized Mean ( 23 / 44 ) 2.46015037593985 0.00353671779726154 695.602679366934 Winsorized Mean ( 24 / 44 ) 2.45654135338346 0.0030227456868888 812.685421747103 Winsorized Mean ( 25 / 44 ) 2.45466165413534 0.00278030716076204 882.874269712902 Winsorized Mean ( 26 / 44 ) 2.45466165413534 0.00278030716076204 882.874269712902 Winsorized Mean ( 27 / 44 ) 2.45466165413534 0.00278030716076204 882.874269712902 Winsorized Mean ( 28 / 44 ) 2.45466165413534 0.00278030716076204 882.874269712902 Winsorized Mean ( 29 / 44 ) 2.45466165413534 0.00278030716076204 882.874269712902 Winsorized Mean ( 30 / 44 ) 2.45466165413534 0.00278030716076204 882.874269712902 Winsorized Mean ( 31 / 44 ) 2.45466165413534 0.00278030716076204 882.874269712902 Winsorized Mean ( 32 / 44 ) 2.45706766917293 0.00257000849506345 956.054298611286 Winsorized Mean ( 33 / 44 ) 2.45458646616541 0.00226545294272908 1083.48596427189 Winsorized Mean ( 34 / 44 ) 2.45458646616541 0.00226545294272908 1083.48596427189 Winsorized Mean ( 35 / 44 ) 2.45458646616541 0.00226545294272908 1083.48596427189 Winsorized Mean ( 36 / 44 ) 2.45458646616541 0.00226545294272908 1083.48596427189 Winsorized Mean ( 37 / 44 ) 2.45458646616541 0.00226545294272908 1083.48596427189 Winsorized Mean ( 38 / 44 ) 2.45172932330827 0.00193748056001386 1265.42137965541 Winsorized Mean ( 39 / 44 ) 2.45172932330827 0.00193748056001386 1265.42137965541 Winsorized Mean ( 40 / 44 ) 2.45172932330827 0.00193748056001386 1265.42137965541 Winsorized Mean ( 41 / 44 ) 2.45172932330827 0.00193748056001386 1265.42137965541 Winsorized Mean ( 42 / 44 ) 2.45172932330827 0.00193748056001386 1265.42137965541 Winsorized Mean ( 43 / 44 ) 2.45172932330827 0.00193748056001386 1265.42137965541 Winsorized Mean ( 44 / 44 ) 2.45172932330827 0.00193748056001386 1265.42137965541 Trimmed Mean ( 1 / 44 ) 2.50282442748092 0.0148459598111655 168.586232167930 Trimmed Mean ( 2 / 44 ) 2.49852713178295 0.0140536851249418 177.784482117696 Trimmed Mean ( 3 / 44 ) 2.49409448818898 0.0131812446674237 189.215400450984 Trimmed Mean ( 4 / 44 ) 2.4896 0.0122022737172614 204.027549101624 Trimmed Mean ( 5 / 44 ) 2.48495934959350 0.0110909474859790 224.052936210811 Trimmed Mean ( 6 / 44 ) 2.48132231404959 0.0103285838294666 240.238386502764 Trimmed Mean ( 7 / 44 ) 2.47789915966387 0.0095868758726934 258.467846310782 Trimmed Mean ( 8 / 44 ) 2.47461538461538 0.0088321433407096 280.182883039189 Trimmed Mean ( 9 / 44 ) 2.47130434782609 0.00797452249275761 309.899978346102 Trimmed Mean ( 10 / 44 ) 2.46796460176991 0.00703315168991493 350.904503497174 Trimmed Mean ( 11 / 44 ) 2.46468468468468 0.00595893649551435 413.611503754068 Trimmed Mean ( 12 / 44 ) 2.46183486238532 0.00501639367793434 490.757907062641 Trimmed Mean ( 13 / 44 ) 2.45990654205607 0.00446877393965801 550.465647909755 Trimmed Mean ( 14 / 44 ) 2.45876190476190 0.00422511078402394 581.9402213213 Trimmed Mean ( 15 / 44 ) 2.45786407766990 0.0040524133287598 606.518604661215 Trimmed Mean ( 16 / 44 ) 2.45712871287129 0.00392084208388954 626.683926641027 Trimmed Mean ( 17 / 44 ) 2.45646464646465 0.00380224719358868 646.056008827285 Trimmed Mean ( 18 / 44 ) 2.45577319587629 0.00366626164843613 669.830315281457 Trimmed Mean ( 19 / 44 ) 2.45505263157895 0.00350930193832060 699.584326093591 Trimmed Mean ( 20 / 44 ) 2.45440860215054 0.00336519033258945 729.352089949076 Trimmed Mean ( 21 / 44 ) 2.45362637362637 0.00321214303002456 763.859626016595 Trimmed Mean ( 22 / 44 ) 2.45280898876404 0.00303195765349517 808.985239598088 Trimmed Mean ( 23 / 44 ) 2.45229885057471 0.00294610389933098 832.387089651385 Trimmed Mean ( 24 / 44 ) 2.45176470588235 0.00284608173617171 861.452668320146 Trimmed Mean ( 25 / 44 ) 2.45144578313253 0.00280176957075479 874.9633833992 Trimmed Mean ( 26 / 44 ) 2.45123456790123 0.00277990316494342 881.769767671432 Trimmed Mean ( 27 / 44 ) 2.45101265822785 0.0027535049612912 890.1428153151 Trimmed Mean ( 28 / 44 ) 2.45077922077922 0.00272181532547091 900.420832319033 Trimmed Mean ( 29 / 44 ) 2.45053333333333 0.0026839082255851 913.046619840777 Trimmed Mean ( 30 / 44 ) 2.45027397260274 0.00263864128026635 928.612006083451 Trimmed Mean ( 31 / 44 ) 2.45 0.00258458516650107 947.927749394589 Trimmed Mean ( 32 / 44 ) 2.44971014492754 0.00251992075624699 972.137770147969 Trimmed Mean ( 33 / 44 ) 2.44925373134328 0.00246470731068723 993.730054973693 Trimmed Mean ( 34 / 44 ) 2.44892307692308 0.00244283761664622 1002.49114400212 Trimmed Mean ( 35 / 44 ) 2.44857142857143 0.00241451005904935 1014.10694869314 Trimmed Mean ( 36 / 44 ) 2.44819672131148 0.00237827366238337 1029.40076242447 Trimmed Mean ( 37 / 44 ) 2.44779661016949 0.00233224790301804 1049.54392155393 Trimmed Mean ( 38 / 44 ) 2.44736842105263 0.00227394410470451 1076.26586598559 Trimmed Mean ( 39 / 44 ) 2.44709090909091 0.00225738932183883 1084.03583086747 Trimmed Mean ( 40 / 44 ) 2.44679245283019 0.00223401570955564 1095.24406760634 Trimmed Mean ( 41 / 44 ) 2.44647058823529 0.00220202276727317 1111.01057836238 Trimmed Mean ( 42 / 44 ) 2.44612244897959 0.00215899334320521 1132.99212185069 Trimmed Mean ( 43 / 44 ) 2.44574468085106 0.00210159801872071 1163.75475189106 Trimmed Mean ( 44 / 44 ) 2.44533333333333 0.0020250950844368 1207.51531724418 Median 2.44 Midrange 2.785 Midmean - Weighted Average at Xnp 2.44897058823529 Midmean - Weighted Average at X(n+1)p 2.44897058823529 Midmean - Empirical Distribution Function 2.44897058823529 Midmean - Empirical Distribution Function - Averaging 2.44897058823529 Midmean - Empirical Distribution Function - Interpolation 2.44897058823529 Midmean - Closest Observation 2.44897058823529 Midmean - True Basic - Statistics Graphics Toolkit 2.44897058823529 Midmean - MS Excel (old versions) 2.44897058823529 Number of observations 133

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Jan/13/t1263389184qaaw8te8jakadbt/1se4p1263389134.png (open in new window) http://www.freestatistics.org/blog/date/2010/Jan/13/t1263389184qaaw8te8jakadbt/1se4p1263389134.ps (open in new window) http://www.freestatistics.org/blog/date/2010/Jan/13/t1263389184qaaw8te8jakadbt/2ehx71263389134.png (open in new window) http://www.freestatistics.org/blog/date/2010/Jan/13/t1263389184qaaw8te8jakadbt/2ehx71263389134.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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