Mini tutorial mean Y

*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: Mon, 15 Nov 2010 17:29:21 +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/Nov/15/t1289842101qcwgq9vlyv6l2ma.htm/, Retrieved Mon, 15 Nov 2010 18:28:22 +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/Nov/15/t1289842101qcwgq9vlyv6l2ma.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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10 20 40 67 38 61 29 0 30 39 70 65 5 30 50 90 45 75 76 15 10 60 67 60 80 70 70 87 27 65 56 82 30 38 56 70 80 71 50 31 40 71 71 10 20 40 55 80 80 72 60 29 70 60 63 70 38 40 80 24 40 47 70 75 60 65 91 68 90 20 61 13 80 40 70 39 93 10 25 56 18 60 74 35 71 100 64 50 40 35 60 70 55 65 30 25 80 26 78 10 70 65 80 60 74 49 70 66 65 40 40 20 90 48 25 35 40 77 70 82 80 52 71 70 50 80 72 80 91 18 70 76 65 35 62 76 50 68 80 90 79 30 60 100

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 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 Central Tendency - Ungrouped Data Measure Value S.E. Value/S.E. Arithmetic Mean 55.6805555555556 1.93231558237395 28.8154564727720 Geometric Mean 0 Harmonic Mean 0 Quadratic Mean 60.2848562152129 Winsorized Mean ( 1 / 48 ) 55.7152777777778 1.92561918503365 28.9336947880503 Winsorized Mean ( 2 / 48 ) 55.6875 1.89887272692547 29.3266100515149 Winsorized Mean ( 3 / 48 ) 55.6458333333333 1.89328929693486 29.3910885269467 Winsorized Mean ( 4 / 48 ) 55.6458333333333 1.89328929693486 29.3910885269467 Winsorized Mean ( 5 / 48 ) 55.6111111111111 1.88881175856053 29.4423787119435 Winsorized Mean ( 6 / 48 ) 55.6111111111111 1.88881175856053 29.4423787119435 Winsorized Mean ( 7 / 48 ) 55.7569444444444 1.86480318572801 29.8996402790234 Winsorized Mean ( 8 / 48 ) 55.8680555555556 1.84729917217668 30.2431010618199 Winsorized Mean ( 9 / 48 ) 55.8680555555556 1.79546736052579 31.116163280849 Winsorized Mean ( 10 / 48 ) 55.5208333333333 1.75607970310566 31.6163516013217 Winsorized Mean ( 11 / 48 ) 55.6736111111111 1.73367145990154 32.1131266210455 Winsorized Mean ( 12 / 48 ) 55.5069444444444 1.71650418267682 32.3372031391636 Winsorized Mean ( 13 / 48 ) 55.5069444444444 1.71650418267682 32.3372031391636 Winsorized Mean ( 14 / 48 ) 55.5069444444444 1.71650418267682 32.3372031391636 Winsorized Mean ( 15 / 48 ) 55.9236111111111 1.65828544931838 33.7237543355989 Winsorized Mean ( 16 / 48 ) 56.0347222222222 1.64346948785257 34.095383356 Winsorized Mean ( 17 / 48 ) 56.0347222222222 1.64346948785257 34.095383356 Winsorized Mean ( 18 / 48 ) 56.0347222222222 1.64346948785257 34.095383356 Winsorized Mean ( 19 / 48 ) 56.1666666666667 1.62619867928926 34.5386251889065 Winsorized Mean ( 20 / 48 ) 56.3055555555556 1.60834066382914 35.0084760162087 Winsorized Mean ( 21 / 48 ) 56.5972222222222 1.57184580883142 36.0068537920389 Winsorized Mean ( 22 / 48 ) 56.5972222222222 1.57184580883142 36.0068537920389 Winsorized Mean ( 23 / 48 ) 56.7569444444444 1.55241391999666 36.5604454542424 Winsorized Mean ( 24 / 48 ) 56.5902777777778 1.53518097086012 36.8622845462133 Winsorized Mean ( 25 / 48 ) 56.4166666666667 1.51768581757564 37.1728232637681 Winsorized Mean ( 26 / 48 ) 56.2361111111111 1.49996717495524 37.4915611821901 Winsorized Mean ( 27 / 48 ) 56.0486111111111 1.48206481277862 37.8179217452909 Winsorized Mean ( 28 / 48 ) 56.2430555555556 1.45834570516823 38.5663394874315 Winsorized Mean ( 29 / 48 ) 57.0486111111111 1.36395239950908 41.8259545799725 Winsorized Mean ( 30 / 48 ) 56.8402777777778 1.34398654906225 42.2922966137104 Winsorized Mean ( 31 / 48 ) 56.8402777777778 1.34398654906225 42.2922966137104 Winsorized Mean ( 32 / 48 ) 56.6180555555556 1.32327927469165 42.7861726835771 Winsorized Mean ( 33 / 48 ) 57.3055555555556 1.24672366965843 45.9649214579009 Winsorized Mean ( 34 / 48 ) 56.8333333333333 1.20378837388739 47.2120636535154 Winsorized Mean ( 35 / 48 ) 56.8333333333333 1.20378837388739 47.2120636535154 Winsorized Mean ( 36 / 48 ) 56.8333333333333 1.15486875172975 49.2119413987165 Winsorized Mean ( 37 / 48 ) 56.8333333333333 1.15486875172975 49.2119413987165 Winsorized Mean ( 38 / 48 ) 57.0972222222222 1.12661519397861 50.680323261561 Winsorized Mean ( 39 / 48 ) 57.0972222222222 1.12661519397861 50.680323261561 Winsorized Mean ( 40 / 48 ) 57.0972222222222 1.12661519397861 50.680323261561 Winsorized Mean ( 41 / 48 ) 56.8125 1.10241702869969 51.5344905974564 Winsorized Mean ( 42 / 48 ) 56.8125 1.10241702869969 51.5344905974564 Winsorized Mean ( 43 / 48 ) 56.8125 1.10241702869969 51.5344905974564 Winsorized Mean ( 44 / 48 ) 56.8125 1.10241702869969 51.5344905974564 Winsorized Mean ( 45 / 48 ) 56.8125 1.10241702869969 51.5344905974564 Winsorized Mean ( 46 / 48 ) 56.8125 1.10241702869969 51.5344905974564 Winsorized Mean ( 47 / 48 ) 56.8125 1.10241702869969 51.5344905974564 Winsorized Mean ( 48 / 48 ) 58.4791666666667 0.928586871066637 62.9765167791933 Trimmed Mean ( 1 / 48 ) 55.7605633802817 1.89397652993403 29.4410001913931 Trimmed Mean ( 2 / 48 ) 55.8071428571429 1.85950231571106 30.0118705879657 Trimmed Mean ( 3 / 48 ) 55.8695652173913 1.83708710711725 30.4120392554829 Trimmed Mean ( 4 / 48 ) 55.9485294117647 1.81476994745726 30.829543706163 Trimmed Mean ( 5 / 48 ) 56.0298507462687 1.79035121049140 31.2954522095640 Trimmed Mean ( 6 / 48 ) 56.1212121212121 1.76473114122609 31.8015650147255 Trimmed Mean ( 7 / 48 ) 56.2153846153846 1.73662310906653 32.3705151232276 Trimmed Mean ( 8 / 48 ) 56.2890625 1.71057791811587 32.9064592170113 Trimmed Mean ( 9 / 48 ) 56.3492063492063 1.68512888529047 33.4391077389272 Trimmed Mean ( 10 / 48 ) 56.4112903225806 1.66563089097940 33.8678218734348 Trimmed Mean ( 11 / 48 ) 56.516393442623 1.64985470272710 34.2553761547638 Trimmed Mean ( 12 / 48 ) 56.6083333333333 1.63553398167961 34.6115299146518 Trimmed Mean ( 13 / 48 ) 56.7203389830508 1.62172727719979 34.9752635850024 Trimmed Mean ( 14 / 48 ) 56.8362068965517 1.60625389308262 35.3843232015304 Trimmed Mean ( 15 / 48 ) 56.9561403508772 1.58892057202586 35.8458071181359 Trimmed Mean ( 16 / 48 ) 57.0446428571429 1.57667544808891 36.1803330712651 Trimmed Mean ( 17 / 48 ) 57.1272727272727 1.56457387958258 36.5129914750425 Trimmed Mean ( 18 / 48 ) 57.212962962963 1.55085986075664 36.8911236989844 Trimmed Mean ( 19 / 48 ) 57.3018867924528 1.53533814469848 37.3219977568564 Trimmed Mean ( 20 / 48 ) 57.3846153846154 1.51974235343337 37.7594368249152 Trimmed Mean ( 21 / 48 ) 57.4607843137255 1.50406629122258 38.203624832931 Trimmed Mean ( 22 / 48 ) 57.52 1.49027012669014 38.5970294712615 Trimmed Mean ( 23 / 48 ) 57.5816326530612 1.47451336489083 39.0512788992756 Trimmed Mean ( 24 / 48 ) 57.6354166666667 1.45864932353520 39.512866963103 Trimmed Mean ( 25 / 48 ) 57.7021276595745 1.44223239057136 40.0088973433157 Trimmed Mean ( 26 / 48 ) 57.7826086956522 1.42513660898377 40.545312169656 Trimmed Mean ( 27 / 48 ) 57.8777777777778 1.40720704051531 41.1295396564982 Trimmed Mean ( 28 / 48 ) 57.9886363636364 1.38825254175608 41.7709563782128 Trimmed Mean ( 29 / 48 ) 58.093023255814 1.36905690196370 42.4328770940702 Trimmed Mean ( 30 / 48 ) 58.1547619047619 1.35744415433342 42.8413660474445 Trimmed Mean ( 31 / 48 ) 58.2317073170732 1.34561851359426 43.2750491530706 Trimmed Mean ( 32 / 48 ) 58.3125 1.33153021208540 43.7935988764931 Trimmed Mean ( 33 / 48 ) 58.4102564102564 1.31684391175418 44.3562489744496 Trimmed Mean ( 34 / 48 ) 58.4736842105263 1.30820268886805 44.6977251370138 Trimmed Mean ( 35 / 48 ) 58.5675675675676 1.30162104966648 44.995866948045 Trimmed Mean ( 36 / 48 ) 58.6666666666667 1.29311406107925 45.3685165388292 Trimmed Mean ( 37 / 48 ) 58.7714285714286 1.28764979688130 45.6424011511309 Trimmed Mean ( 38 / 48 ) 58.8823529411765 1.28021505062256 45.9941108429732 Trimmed Mean ( 39 / 48 ) 58.9848484848485 1.27399897615940 46.298976363909 Trimmed Mean ( 40 / 48 ) 59.09375 1.26552242137701 46.6951426555526 Trimmed Mean ( 41 / 48 ) 59.2096774193548 1.25431820950255 47.2046702111076 Trimmed Mean ( 42 / 48 ) 59.35 1.24233810003648 47.7728244817229 Trimmed Mean ( 43 / 48 ) 59.5 1.22665742783022 48.5058001118102 Trimmed Mean ( 44 / 48 ) 59.6607142857143 1.20638904843260 49.4539587898519 Trimmed Mean ( 45 / 48 ) 59.8333333333333 1.1803628526903 50.6906272058295 Trimmed Mean ( 46 / 48 ) 60.0192307692308 1.14699764965201 52.3272482619649 Trimmed Mean ( 47 / 48 ) 60.22 1.10408887545250 54.5427105905035 Trimmed Mean ( 48 / 48 ) 60.4375 1.04843105087541 57.645660102814 Median 60.5 Midrange 50 Midmean - Weighted Average at Xnp 57.84 Midmean - Weighted Average at X(n+1)p 58.6666666666667 Midmean - Empirical Distribution Function 57.84 Midmean - Empirical Distribution Function - Averaging 58.6666666666667 Midmean - Empirical Distribution Function - Interpolation 58.6666666666667 Midmean - Closest Observation 57.84 Midmean - True Basic - Statistics Graphics Toolkit 58.6666666666667 Midmean - MS Excel (old versions) 58.2077922077922 Number of observations 144

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Nov/15/t1289842101qcwgq9vlyv6l2ma/12bdf1289842157.png (open in new window) http://www.freestatistics.org/blog/date/2010/Nov/15/t1289842101qcwgq9vlyv6l2ma/12bdf1289842157.ps (open in new window) http://www.freestatistics.org/blog/date/2010/Nov/15/t1289842101qcwgq9vlyv6l2ma/22bdf1289842157.png (open in new window) http://www.freestatistics.org/blog/date/2010/Nov/15/t1289842101qcwgq9vlyv6l2ma/22bdf1289842157.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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