Univariate analysis of X

*The author of this computation has been verified*

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

Title produced by software: Central Tendency

Date of computation: Sat, 11 Dec 2010 10:52:21 +0000

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2010/Dec/11/t1292064673vhtn3yv6q0mt9s3.htm/, Retrieved Sat, 11 Dec 2010 11:51:13 +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/Dec/11/t1292064673vhtn3yv6q0mt9s3.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:

Dataseries X:

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15 15 14 10 10 12 18 12 14 18 9 11 11 17 8 16 21 24 21 14 7 18 18 13 11 13 13 18 14 12 9 12 8 5 10 11 11 12 12 15 12 16 14 17 13 10 17 12 13 13 11 13 12 12 12 9 7 17 12 12 9 9 13 10 11 12 10 13 6 7 13 11 18 9 9 11 11 15 8 11 14 14 12 12 8 11 10 17 16 13 15 11 12 16 20 16 11 15 15 12 9 24 15 18 17 12 15 11 11 15 12 14 11 20 11 12 17 12 11 10 11 12 9 8 6 12 15 13 17 14 16 15 16 11 11 16 15 14 9 13 11 14 11 12 8 7 11 13 9 12 10 12

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 'RServer@AstonUniversity' @ vre.aston.ac.uk Central Tendency - Ungrouped Data Measure Value S.E. Value/S.E. Arithmetic Mean 12.7105263157895 0.274803326317298 46.2531749019422 Geometric Mean 12.2665415653407 Harmonic Mean 11.8131067207993 Quadratic Mean 13.1514457880413 Winsorized Mean ( 1 / 50 ) 12.7171052631579 0.27365720886588 46.4709309718589 Winsorized Mean ( 2 / 50 ) 12.6776315789474 0.264127158016024 47.9982129599041 Winsorized Mean ( 3 / 50 ) 12.6973684210526 0.261047216997108 48.6401217646127 Winsorized Mean ( 4 / 50 ) 12.6710526315789 0.255776130048259 49.5396213446041 Winsorized Mean ( 5 / 50 ) 12.6710526315789 0.255776130048259 49.5396213446041 Winsorized Mean ( 6 / 50 ) 12.5921052631579 0.242409204247189 51.945656528444 Winsorized Mean ( 7 / 50 ) 12.6381578947368 0.235885888728703 53.5774223835502 Winsorized Mean ( 8 / 50 ) 12.6381578947368 0.235885888728703 53.5774223835502 Winsorized Mean ( 9 / 50 ) 12.6381578947368 0.235885888728703 53.5774223835502 Winsorized Mean ( 10 / 50 ) 12.6381578947368 0.235885888728703 53.5774223835502 Winsorized Mean ( 11 / 50 ) 12.6381578947368 0.235885888728703 53.5774223835502 Winsorized Mean ( 12 / 50 ) 12.6381578947368 0.235885888728703 53.5774223835502 Winsorized Mean ( 13 / 50 ) 12.6381578947368 0.213182932102152 59.2831601015832 Winsorized Mean ( 14 / 50 ) 12.6381578947368 0.213182932102152 59.2831601015832 Winsorized Mean ( 15 / 50 ) 12.6381578947368 0.213182932102152 59.2831601015832 Winsorized Mean ( 16 / 50 ) 12.6381578947368 0.213182932102152 59.2831601015832 Winsorized Mean ( 17 / 50 ) 12.6381578947368 0.213182932102152 59.2831601015832 Winsorized Mean ( 18 / 50 ) 12.6381578947368 0.213182932102152 59.2831601015832 Winsorized Mean ( 19 / 50 ) 12.6381578947368 0.213182932102152 59.2831601015832 Winsorized Mean ( 20 / 50 ) 12.6381578947368 0.213182932102152 59.2831601015832 Winsorized Mean ( 21 / 50 ) 12.5 0.19558565118678 63.9106188217394 Winsorized Mean ( 22 / 50 ) 12.5 0.19558565118678 63.9106188217394 Winsorized Mean ( 23 / 50 ) 12.5 0.19558565118678 63.9106188217394 Winsorized Mean ( 24 / 50 ) 12.6578947368421 0.178366699823569 70.9655712045054 Winsorized Mean ( 25 / 50 ) 12.6578947368421 0.178366699823569 70.9655712045054 Winsorized Mean ( 26 / 50 ) 12.6578947368421 0.178366699823569 70.9655712045054 Winsorized Mean ( 27 / 50 ) 12.6578947368421 0.178366699823569 70.9655712045054 Winsorized Mean ( 28 / 50 ) 12.6578947368421 0.178366699823569 70.9655712045054 Winsorized Mean ( 29 / 50 ) 12.4671052631579 0.156178036940353 79.8262387426428 Winsorized Mean ( 30 / 50 ) 12.4671052631579 0.156178036940353 79.8262387426428 Winsorized Mean ( 31 / 50 ) 12.4671052631579 0.156178036940353 79.8262387426428 Winsorized Mean ( 32 / 50 ) 12.4671052631579 0.156178036940353 79.8262387426428 Winsorized Mean ( 33 / 50 ) 12.6842105263158 0.135730936501963 93.4511383566 Winsorized Mean ( 34 / 50 ) 12.6842105263158 0.135730936501963 93.4511383566 Winsorized Mean ( 35 / 50 ) 12.6842105263158 0.135730936501963 93.4511383566 Winsorized Mean ( 36 / 50 ) 12.6842105263158 0.135730936501963 93.4511383566 Winsorized Mean ( 37 / 50 ) 12.6842105263158 0.135730936501963 93.4511383566 Winsorized Mean ( 38 / 50 ) 12.6842105263158 0.135730936501963 93.4511383566 Winsorized Mean ( 39 / 50 ) 12.6842105263158 0.135730936501963 93.4511383566 Winsorized Mean ( 40 / 50 ) 12.6842105263158 0.135730936501963 93.4511383566 Winsorized Mean ( 41 / 50 ) 12.6842105263158 0.135730936501963 93.4511383566 Winsorized Mean ( 42 / 50 ) 12.4078947368421 0.106168769066457 116.869535607739 Winsorized Mean ( 43 / 50 ) 12.4078947368421 0.106168769066457 116.869535607739 Winsorized Mean ( 44 / 50 ) 12.4078947368421 0.106168769066457 116.869535607739 Winsorized Mean ( 45 / 50 ) 12.4078947368421 0.106168769066457 116.869535607739 Winsorized Mean ( 46 / 50 ) 12.4078947368421 0.106168769066457 116.869535607739 Winsorized Mean ( 47 / 50 ) 12.4078947368421 0.106168769066457 116.869535607739 Winsorized Mean ( 48 / 50 ) 12.4078947368421 0.106168769066457 116.869535607739 Winsorized Mean ( 49 / 50 ) 12.4078947368421 0.106168769066457 116.869535607739 Winsorized Mean ( 50 / 50 ) 12.4078947368421 0.106168769066457 116.869535607739 Trimmed Mean ( 1 / 50 ) 12.6866666666667 0.263029445475547 48.232876147116 Trimmed Mean ( 2 / 50 ) 12.6554054054054 0.251254041345977 50.3689625751289 Trimmed Mean ( 3 / 50 ) 12.6438356164384 0.243913093474682 51.8374615988 Trimmed Mean ( 4 / 50 ) 12.625 0.237114509463868 53.2443165479245 Trimmed Mean ( 5 / 50 ) 12.612676056338 0.231356825220903 54.516118313325 Trimmed Mean ( 6 / 50 ) 12.6 0.225049954486528 55.98756964314 Trimmed Mean ( 7 / 50 ) 12.6014492753623 0.221202357408646 56.9679700659003 Trimmed Mean ( 8 / 50 ) 12.5955882352941 0.218276741772858 57.7046740435648 Trimmed Mean ( 9 / 50 ) 12.589552238806 0.215078725885926 58.5346234823952 Trimmed Mean ( 10 / 50 ) 12.5833333333333 0.211578359273179 59.4736313135239 Trimmed Mean ( 11 / 50 ) 12.5769230769231 0.207740889655814 60.5413941268883 Trimmed Mean ( 12 / 50 ) 12.5703125 0.203525640249397 61.7627955111529 Trimmed Mean ( 13 / 50 ) 12.5634920634921 0.1988845183776 63.169783983081 Trimmed Mean ( 14 / 50 ) 12.5564516129032 0.196781878496324 63.8089833721033 Trimmed Mean ( 15 / 50 ) 12.5491803278689 0.194457289874163 64.5343784025255 Trimmed Mean ( 16 / 50 ) 12.5416666666667 0.191885759566875 65.3600699446158 Trimmed Mean ( 17 / 50 ) 12.5338983050847 0.189038373862754 66.303460239161 Trimmed Mean ( 18 / 50 ) 12.5258620689655 0.185881427479837 67.3863023261119 Trimmed Mean ( 19 / 50 ) 12.5175438596491 0.182375285131142 68.6361852739424 Trimmed Mean ( 20 / 50 ) 12.5089285714286 0.1784728653342 70.0886857394538 Trimmed Mean ( 21 / 50 ) 12.5 0.17411757744595 71.7905692426733 Trimmed Mean ( 22 / 50 ) 12.5 0.171275830684109 72.98169245522 Trimmed Mean ( 23 / 50 ) 12.5 0.168098076022968 74.3613508003034 Trimmed Mean ( 24 / 50 ) 12.5 0.164537053945261 75.9707293905878 Trimmed Mean ( 25 / 50 ) 12.4901960784314 0.162336546552452 76.9401366709232 Trimmed Mean ( 26 / 50 ) 12.48 0.15984841304034 78.0739687221699 Trimmed Mean ( 27 / 50 ) 12.469387755102 0.157031746521729 79.4067953219678 Trimmed Mean ( 28 / 50 ) 12.4583333333333 0.153837367607856 80.9837916954653 Trimmed Mean ( 29 / 50 ) 12.4468085106383 0.150205396837837 82.8652549953049 Trimmed Mean ( 30 / 50 ) 12.445652173913 0.148542955603851 83.784869658204 Trimmed Mean ( 31 / 50 ) 12.4444444444444 0.146631857557334 84.8686271302166 Trimmed Mean ( 32 / 50 ) 12.4431818181818 0.144435226400104 86.1506027879418 Trimmed Mean ( 33 / 50 ) 12.4418604651163 0.141908672932869 87.675123781913 Trimmed Mean ( 34 / 50 ) 12.4285714285714 0.140980211545937 88.1582691094326 Trimmed Mean ( 35 / 50 ) 12.4146341463415 0.13984895227578 88.77173510646 Trimmed Mean ( 36 / 50 ) 12.4 0.138481822597312 89.5424378985657 Trimmed Mean ( 37 / 50 ) 12.3846153846154 0.136838828110705 90.5051260348125 Trimmed Mean ( 38 / 50 ) 12.3684210526316 0.134871095394965 91.7054986200793 Trimmed Mean ( 39 / 50 ) 12.3513513513514 0.132518162792827 93.2049697267607 Trimmed Mean ( 40 / 50 ) 12.3333333333333 0.129704129422923 95.0882087425169 Trimmed Mean ( 41 / 50 ) 12.3142857142857 0.126332003919963 97.4755828466661 Trimmed Mean ( 42 / 50 ) 12.2941176470588 0.122275081595546 100.54475111883 Trimmed Mean ( 43 / 50 ) 12.2878787878788 0.121691940757357 100.975288185926 Trimmed Mean ( 44 / 50 ) 12.28125 0.120902586886605 101.57971236396 Trimmed Mean ( 45 / 50 ) 12.2741935483871 0.119865416418821 102.399790657715 Trimmed Mean ( 46 / 50 ) 12.2666666666667 0.118528326650028 103.491435451424 Trimmed Mean ( 47 / 50 ) 12.2586206896552 0.116825174910173 104.931327507798 Trimmed Mean ( 48 / 50 ) 12.25 0.114670618073466 106.827714071898 Trimmed Mean ( 49 / 50 ) 12.2407407407407 0.111952324587579 109.338870682984 Trimmed Mean ( 50 / 50 ) 12.2307692307692 0.10851869957016 112.706559138794 Median 12 Midrange 14.5 Midmean - Weighted Average at Xnp 12.5555555555556 Midmean - Weighted Average at X(n+1)p 12.5555555555556 Midmean - Empirical Distribution Function 12.5555555555556 Midmean - Empirical Distribution Function - Averaging 12.5555555555556 Midmean - Empirical Distribution Function - Interpolation 12.5555555555556 Midmean - Closest Observation 12.5555555555556 Midmean - True Basic - Statistics Graphics Toolkit 12.5555555555556 Midmean - MS Excel (old versions) 12.5555555555556 Number of observations 152

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Dec/11/t1292064673vhtn3yv6q0mt9s3/1w80h1292064737.png (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/11/t1292064673vhtn3yv6q0mt9s3/1w80h1292064737.ps (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/11/t1292064673vhtn3yv6q0mt9s3/2w80h1292064737.png (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/11/t1292064673vhtn3yv6q0mt9s3/2w80h1292064737.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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