W6

*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: Tue, 16 Nov 2010 14:16:44 +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/16/t1289916891m11pkt57cgeaemd.htm/, Retrieved Tue, 16 Nov 2010 15:14:51 +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/16/t1289916891m11pkt57cgeaemd.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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68 70 90 95 75 69 39 80 100 80 81 55 100 75 70 100 61 83 90 60 44 90 100 82 80 88 100 83 75 55 75 80 70 100 60 95 95 90 90 80 76 65 78 70 60 65 100 65 90 90 90 80 91 100 90 80 100 88 61 90 58 90 88 90 80 85 60 95 100 61 80 90 75 85 95 78 90 80 100 30 70 67 35 100 96 74 70 80 100 100 74 59 35 80 91 75 82 100 90 50 90 60 100 80 65 100 72 98 93 45 88 82 90 100 75 100 100 80 71 71 60 100 80 85 100 61 73 80 60 100 83 70 91 45 70 95 80 78 100 100 100 82 90 87 75 100

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 80.445205479452 1.33025655631288 60.4734516042718 Geometric Mean 78.534300089989 Harmonic Mean 76.1760297217087 Quadratic Mean 82.0245118726421 Winsorized Mean ( 1 / 48 ) 80.4794520547945 1.32171354897135 60.890237614216 Winsorized Mean ( 2 / 48 ) 80.4794520547945 1.32171354897135 60.890237614216 Winsorized Mean ( 3 / 48 ) 80.5616438356164 1.30291532428329 61.8318338376534 Winsorized Mean ( 4 / 48 ) 80.6986301369863 1.27422653794607 63.3314624470661 Winsorized Mean ( 5 / 48 ) 80.7328767123288 1.26749601943030 63.6947773205756 Winsorized Mean ( 6 / 48 ) 80.7328767123288 1.26749601943030 63.6947773205756 Winsorized Mean ( 7 / 48 ) 80.972602739726 1.2232183482863 66.1963604888421 Winsorized Mean ( 8 / 48 ) 81.2465753424657 1.17819753145660 68.958364937347 Winsorized Mean ( 9 / 48 ) 81.2465753424657 1.17819753145660 68.958364937347 Winsorized Mean ( 10 / 48 ) 81.4520547945205 1.14792051588796 70.9561800378784 Winsorized Mean ( 11 / 48 ) 81.527397260274 1.13746667635521 71.6745368941382 Winsorized Mean ( 12 / 48 ) 81.6095890410959 1.12641548122403 72.450699055036 Winsorized Mean ( 13 / 48 ) 81.6095890410959 1.12641548122403 72.450699055036 Winsorized Mean ( 14 / 48 ) 81.6095890410959 1.12641548122403 72.450699055036 Winsorized Mean ( 15 / 48 ) 81.6095890410959 1.12641548122403 72.450699055036 Winsorized Mean ( 16 / 48 ) 81.6095890410959 1.12641548122403 72.450699055036 Winsorized Mean ( 17 / 48 ) 81.6095890410959 1.12641548122403 72.450699055036 Winsorized Mean ( 18 / 48 ) 81.6095890410959 1.12641548122403 72.450699055036 Winsorized Mean ( 19 / 48 ) 81.7397260273973 1.10941582650519 73.6781683427831 Winsorized Mean ( 20 / 48 ) 81.7397260273973 1.10941582650519 73.6781683427831 Winsorized Mean ( 21 / 48 ) 81.7397260273973 1.10941582650519 73.6781683427831 Winsorized Mean ( 22 / 48 ) 81.7397260273973 1.10941582650519 73.6781683427831 Winsorized Mean ( 23 / 48 ) 82.3698630136986 1.03207939565944 79.8096186786767 Winsorized Mean ( 24 / 48 ) 82.3698630136986 1.03207939565944 79.8096186786767 Winsorized Mean ( 25 / 48 ) 82.3698630136986 1.03207939565944 79.8096186786767 Winsorized Mean ( 26 / 48 ) 82.3698630136986 1.03207939565944 79.8096186786767 Winsorized Mean ( 27 / 48 ) 82.3698630136986 0.947014486809335 86.9784614290514 Winsorized Mean ( 28 / 48 ) 82.1780821917808 0.88308970050131 93.0574574079284 Winsorized Mean ( 29 / 48 ) 82.1780821917808 0.840163565260817 97.8120042211897 Winsorized Mean ( 30 / 48 ) 82.3835616438356 0.818322319972051 100.673731649711 Winsorized Mean ( 31 / 48 ) 82.3835616438356 0.818322319972051 100.673731649711 Winsorized Mean ( 32 / 48 ) 82.3835616438356 0.818322319972051 100.673731649711 Winsorized Mean ( 33 / 48 ) 82.3835616438356 0.818322319972051 100.673731649711 Winsorized Mean ( 34 / 48 ) 82.3835616438356 0.818322319972051 100.673731649711 Winsorized Mean ( 35 / 48 ) 81.9041095890411 0.768924600834731 106.517738540459 Winsorized Mean ( 36 / 48 ) 81.4109589041096 0.721730405852391 112.799680107644 Winsorized Mean ( 37 / 48 ) 81.4109589041096 0.721730405852391 112.799680107644 Winsorized Mean ( 38 / 48 ) 81.6712328767123 0.693727180488566 117.728172073630 Winsorized Mean ( 39 / 48 ) 81.4041095890411 0.669504344126517 121.588620452115 Winsorized Mean ( 40 / 48 ) 81.6780821917808 0.64053996260542 127.514420582835 Winsorized Mean ( 41 / 48 ) 81.958904109589 0.611716550882357 133.981831930768 Winsorized Mean ( 42 / 48 ) 82.2465753424657 0.583148786918094 141.038748922267 Winsorized Mean ( 43 / 48 ) 82.2465753424657 0.583148786918094 141.038748922267 Winsorized Mean ( 44 / 48 ) 82.5479452054795 0.554287807229553 148.926142932985 Winsorized Mean ( 45 / 48 ) 82.5479452054795 0.554287807229553 148.926142932985 Winsorized Mean ( 46 / 48 ) 82.5479452054795 0.554287807229553 148.926142932985 Winsorized Mean ( 47 / 48 ) 82.5479452054795 0.554287807229553 148.926142932985 Winsorized Mean ( 48 / 48 ) 82.5479452054795 0.554287807229553 148.926142932985 Trimmed Mean ( 1 / 48 ) 80.6597222222222 1.29490676384207 62.2899844795773 Trimmed Mean ( 2 / 48 ) 80.8450704225352 1.2654911942427 63.884340555143 Trimmed Mean ( 3 / 48 ) 81.0357142857143 1.23312497165243 65.715735346048 Trimmed Mean ( 4 / 48 ) 81.2028985507246 1.20518290002841 67.3780706221526 Trimmed Mean ( 5 / 48 ) 81.3382352941177 1.18359430926079 68.7213808462102 Trimmed Mean ( 6 / 48 ) 81.4701492537313 1.16164580398222 70.133382287824 Trimmed Mean ( 7 / 48 ) 81.6060606060606 1.13748190793571 71.7427328177542 Trimmed Mean ( 8 / 48 ) 81.7076923076923 1.11996284512473 72.955716935942 Trimmed Mean ( 9 / 48 ) 81.7734375 1.10881926963120 73.7482110382141 Trimmed Mean ( 10 / 48 ) 81.8412698412698 1.09651179675978 74.6378379905378 Trimmed Mean ( 11 / 48 ) 81.8870967741936 1.08751646592280 75.2973397094356 Trimmed Mean ( 12 / 48 ) 81.9262295081967 1.07899404901455 75.9283423138618 Trimmed Mean ( 13 / 48 ) 81.9583333333333 1.07096881670252 76.5272826389849 Trimmed Mean ( 14 / 48 ) 81.9915254237288 1.06199922457277 77.2048825710893 Trimmed Mean ( 15 / 48 ) 82.0258620689655 1.05198186681636 77.9726957815373 Trimmed Mean ( 16 / 48 ) 82.061403508772 1.04079832493788 78.8446729232292 Trimmed Mean ( 17 / 48 ) 82.0982142857143 1.02831219417952 79.8378301360318 Trimmed Mean ( 18 / 48 ) 82.1363636363636 1.01436531533204 80.9731586785154 Trimmed Mean ( 19 / 48 ) 82.175925925926 0.998772932138707 82.2768852475405 Trimmed Mean ( 20 / 48 ) 82.2075471698113 0.983303285617521 83.6034500974787 Trimmed Mean ( 21 / 48 ) 82.2403846153846 0.96595280581387 85.1391332168577 Trimmed Mean ( 22 / 48 ) 82.2745098039216 0.946455942578166 86.9290435007509 Trimmed Mean ( 23 / 48 ) 82.31 0.92449221661724 89.0326587076915 Trimmed Mean ( 24 / 48 ) 82.3061224489796 0.908663698326207 90.5793007914705 Trimmed Mean ( 25 / 48 ) 82.3020833333333 0.890756601285625 92.3957040728602 Trimmed Mean ( 26 / 48 ) 82.2978723404255 0.870449541243662 94.5464021071707 Trimmed Mean ( 27 / 48 ) 82.2934782608696 0.847347403059192 97.1189360630175 Trimmed Mean ( 28 / 48 ) 82.2888888888889 0.83093203756222 99.0320329088613 Trimmed Mean ( 29 / 48 ) 82.2954545454545 0.819236954612518 100.453787005224 Trimmed Mean ( 30 / 48 ) 82.3023255813954 0.810341801427899 101.564951279042 Trimmed Mean ( 31 / 48 ) 82.297619047619 0.802280842456981 102.579564028455 Trimmed Mean ( 32 / 48 ) 82.2926829268293 0.792825364174422 103.796733360721 Trimmed Mean ( 33 / 48 ) 82.2875 0.781752686377366 105.260271482174 Trimmed Mean ( 34 / 48 ) 82.2820512820513 0.768792193765834 107.027688300271 Trimmed Mean ( 35 / 48 ) 82.2763157894737 0.753610882936868 109.176124777867 Trimmed Mean ( 36 / 48 ) 82.2972972972973 0.741664709906984 110.962940797896 Trimmed Mean ( 37 / 48 ) 82.3472222222222 0.732692774609437 112.389837972836 Trimmed Mean ( 38 / 48 ) 82.4 0.721856360057086 114.150133682390 Trimmed Mean ( 39 / 48 ) 82.4411764705882 0.712481952374103 115.709845275212 Trimmed Mean ( 40 / 48 ) 82.5 0.703719720642704 117.234173748397 Trimmed Mean ( 41 / 48 ) 82.546875 0.696835850206443 118.459569747373 Trimmed Mean ( 42 / 48 ) 82.5806451612903 0.69200632866248 119.335101054500 Trimmed Mean ( 43 / 48 ) 82.6 0.689386856045382 119.816615700840 Trimmed Mean ( 44 / 48 ) 82.6206896551724 0.685529097045402 120.521054483703 Trimmed Mean ( 45 / 48 ) 82.625 0.684030501712261 120.791397157252 Trimmed Mean ( 46 / 48 ) 82.6296296296296 0.681335626842981 121.275956186968 Trimmed Mean ( 47 / 48 ) 82.6346153846154 0.67715849293235 122.031424322505 Trimmed Mean ( 48 / 48 ) 82.64 0.671130632984825 123.135490973586 Median 80.5 Midrange 65 Midmean - Weighted Average at Xnp 81.375 Midmean - Weighted Average at X(n+1)p 81.375 Midmean - Empirical Distribution Function 81.375 Midmean - Empirical Distribution Function - Averaging 81.375 Midmean - Empirical Distribution Function - Interpolation 81.375 Midmean - Closest Observation 81.375 Midmean - True Basic - Statistics Graphics Toolkit 81.375 Midmean - MS Excel (old versions) 81.375 Number of observations 146

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Nov/16/t1289916891m11pkt57cgeaemd/1cibn1289917000.png (open in new window) http://www.freestatistics.org/blog/date/2010/Nov/16/t1289916891m11pkt57cgeaemd/1cibn1289917000.ps (open in new window) http://www.freestatistics.org/blog/date/2010/Nov/16/t1289916891m11pkt57cgeaemd/2cibn1289917000.png (open in new window) http://www.freestatistics.org/blog/date/2010/Nov/16/t1289916891m11pkt57cgeaemd/2cibn1289917000.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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