*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: Fri, 12 Nov 2010 15:30:06 +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/12/t1289575751r6f9mc0qbqc3k3m.htm/, Retrieved Fri, 12 Nov 2010 16:29:13 +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/Nov/12/t1289575751r6f9mc0qbqc3k3m.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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90 80 100 96 100 91 81 80 100 94 100 80 100 90 100 100 100 90 97 90 86 100 100 82 90 94 100 95 100 88 80 81 100 100 100 100 95 100 90 90 100 85 98 91 90 70 100 83 100 100 100 100 100 100 86 100 100 100 100 100 76 100 100 100 100 80 100 100 100 89 100 90 90 95 95 99 90 90 100 100 90 100 81 100 100 98 96 90 90 100 100 88 73 85 100 100 99 90 100 100 100 91 96 80 100 85 90 100 94 95 96 80 100 82 90 100 90 100 100 94 90 79 95 100 91 100 100 76 87 95 71 100 100 100 92 93 80 100 80 90 100 100 100 99 85 100 100 85 100 100

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 'Gwilym Jenkins' @ 72.249.127.135 Central Tendency - Ungrouped Data Measure Value S.E. Value/S.E. Arithmetic Mean 93.72 0.627563735098467 149.339413287313 Geometric Mean 93.3858916840362 Harmonic Mean 93.0295248327893 Quadratic Mean 94.0325475566838 Winsorized Mean ( 1 / 50 ) 93.7266666666667 0.625905816378857 149.745639382163 Winsorized Mean ( 2 / 50 ) 93.7533333333333 0.619658321573993 151.298433457959 Winsorized Mean ( 3 / 50 ) 93.8133333333333 0.60699772170381 154.553023807082 Winsorized Mean ( 4 / 50 ) 93.8133333333333 0.60699772170381 154.553023807082 Winsorized Mean ( 5 / 50 ) 93.9133333333333 0.58862724056661 159.546359497282 Winsorized Mean ( 6 / 50 ) 93.9533333333333 0.582007377634664 161.429797875018 Winsorized Mean ( 7 / 50 ) 93.9533333333333 0.582007377634664 161.429797875018 Winsorized Mean ( 8 / 50 ) 93.9533333333333 0.582007377634664 161.429797875018 Winsorized Mean ( 9 / 50 ) 93.9533333333333 0.582007377634664 161.429797875018 Winsorized Mean ( 10 / 50 ) 93.9533333333333 0.582007377634664 161.429797875018 Winsorized Mean ( 11 / 50 ) 93.9533333333333 0.582007377634664 161.429797875018 Winsorized Mean ( 12 / 50 ) 93.9533333333333 0.582007377634664 161.429797875018 Winsorized Mean ( 13 / 50 ) 93.9533333333333 0.582007377634664 161.429797875018 Winsorized Mean ( 14 / 50 ) 93.9533333333333 0.582007377634664 161.429797875018 Winsorized Mean ( 15 / 50 ) 94.0533333333333 0.566221959993711 166.106827319763 Winsorized Mean ( 16 / 50 ) 94.0533333333333 0.566221959993711 166.106827319763 Winsorized Mean ( 17 / 50 ) 94.0533333333333 0.566221959993711 166.106827319763 Winsorized Mean ( 18 / 50 ) 94.1733333333333 0.547987709219495 171.853002811806 Winsorized Mean ( 19 / 50 ) 94.1733333333333 0.547987709219495 171.853002811806 Winsorized Mean ( 20 / 50 ) 94.3066666666667 0.528468867364298 178.452644026156 Winsorized Mean ( 21 / 50 ) 94.5866666666667 0.489914996659905 193.067506223591 Winsorized Mean ( 22 / 50 ) 94.5866666666667 0.489914996659905 193.067506223591 Winsorized Mean ( 23 / 50 ) 94.5866666666667 0.489914996659905 193.067506223591 Winsorized Mean ( 24 / 50 ) 94.5866666666667 0.489914996659905 193.067506223591 Winsorized Mean ( 25 / 50 ) 94.5866666666667 0.489914996659905 193.067506223591 Winsorized Mean ( 26 / 50 ) 94.76 0.467625732293846 202.640687746531 Winsorized Mean ( 27 / 50 ) 94.76 0.467625732293846 202.640687746531 Winsorized Mean ( 28 / 50 ) 94.9466666666667 0.444683902680887 213.514962188326 Winsorized Mean ( 29 / 50 ) 95.14 0.422099789933841 225.396937569934 Winsorized Mean ( 30 / 50 ) 95.14 0.422099789933841 225.396937569934 Winsorized Mean ( 31 / 50 ) 95.3466666666667 0.399326801140211 238.768513394092 Winsorized Mean ( 32 / 50 ) 95.56 0.377378215684713 253.220763754517 Winsorized Mean ( 33 / 50 ) 95.56 0.377378215684713 253.220763754517 Winsorized Mean ( 34 / 50 ) 95.56 0.377378215684713 253.220763754517 Winsorized Mean ( 35 / 50 ) 95.56 0.377378215684713 253.220763754517 Winsorized Mean ( 36 / 50 ) 95.56 0.377378215684713 253.220763754517 Winsorized Mean ( 37 / 50 ) 95.56 0.377378215684713 253.220763754517 Winsorized Mean ( 38 / 50 ) 95.56 0.377378215684713 253.220763754517 Winsorized Mean ( 39 / 50 ) 95.56 0.377378215684713 253.220763754517 Winsorized Mean ( 40 / 50 ) 95.56 0.377378215684713 253.220763754517 Winsorized Mean ( 41 / 50 ) 95.56 0.377378215684713 253.220763754517 Winsorized Mean ( 42 / 50 ) 95.56 0.377378215684713 253.220763754517 Winsorized Mean ( 43 / 50 ) 95.56 0.377378215684713 253.220763754517 Winsorized Mean ( 44 / 50 ) 95.56 0.377378215684713 253.220763754517 Winsorized Mean ( 45 / 50 ) 95.56 0.377378215684713 253.220763754517 Winsorized Mean ( 46 / 50 ) 95.56 0.377378215684713 253.220763754517 Winsorized Mean ( 47 / 50 ) 95.56 0.377378215684713 253.220763754517 Winsorized Mean ( 48 / 50 ) 95.56 0.377378215684713 253.220763754517 Winsorized Mean ( 49 / 50 ) 95.56 0.377378215684713 253.220763754517 Winsorized Mean ( 50 / 50 ) 95.56 0.377378215684713 253.220763754517 Trimmed Mean ( 1 / 50 ) 93.8378378378378 0.613857117103193 152.865927955126 Trimmed Mean ( 2 / 50 ) 93.9520547945205 0.600608429645356 156.428132135936 Trimmed Mean ( 3 / 50 ) 94.0555555555556 0.589649272324601 159.511017769523 Trimmed Mean ( 4 / 50 ) 94.1408450704225 0.582654031683363 161.572459729554 Trimmed Mean ( 5 / 50 ) 94.2285714285714 0.574942944319969 163.892038957054 Trimmed Mean ( 6 / 50 ) 94.2971014492754 0.571124470612111 165.107794012417 Trimmed Mean ( 7 / 50 ) 94.360294117647 0.568286112898277 166.043638892400 Trimmed Mean ( 8 / 50 ) 94.4253731343284 0.565075757965348 167.102148346132 Trimmed Mean ( 9 / 50 ) 94.4924242424242 0.561455287034117 168.299108450078 Trimmed Mean ( 10 / 50 ) 94.5615384615385 0.557381629582717 169.653130714645 Trimmed Mean ( 11 / 50 ) 94.6328125 0.552805912316143 171.186324877583 Trimmed Mean ( 12 / 50 ) 94.7063492063492 0.54767241515894 172.925176775362 Trimmed Mean ( 13 / 50 ) 94.7822580645161 0.541917277521911 174.901709164798 Trimmed Mean ( 14 / 50 ) 94.860655737705 0.535466876927488 177.155039508729 Trimmed Mean ( 15 / 50 ) 94.9416666666667 0.528235771108525 179.733505111605 Trimmed Mean ( 16 / 50 ) 95.0169491525424 0.522142347318262 181.975182898978 Trimmed Mean ( 17 / 50 ) 95.0948275862069 0.515280516065047 184.549628059685 Trimmed Mean ( 18 / 50 ) 95.1754385964912 0.507549833431564 187.51939677136 Trimmed Mean ( 19 / 50 ) 95.25 0.50104459736204 190.102838153497 Trimmed Mean ( 20 / 50 ) 95.3272727272727 0.493681357646057 193.094738642364 Trimmed Mean ( 21 / 50 ) 95.3981481481482 0.487635242721155 195.634235983021 Trimmed Mean ( 22 / 50 ) 95.4528301886792 0.485019441903687 196.802070065542 Trimmed Mean ( 23 / 50 ) 95.5096153846154 0.48193566491901 198.179181033771 Trimmed Mean ( 24 / 50 ) 95.5686274509804 0.478322516108067 199.799558315981 Trimmed Mean ( 25 / 50 ) 95.63 0.474108413634253 201.704920752098 Trimmed Mean ( 26 / 50 ) 95.6938775510204 0.469209344152342 203.947084054555 Trimmed Mean ( 27 / 50 ) 95.75 0.465945558148047 205.496110705657 Trimmed Mean ( 28 / 50 ) 95.8085106382979 0.462077459940739 207.342965074698 Trimmed Mean ( 29 / 50 ) 95.858695652174 0.459954276415091 208.409184493950 Trimmed Mean ( 30 / 50 ) 95.9 0.459617710114272 208.651663958199 Trimmed Mean ( 31 / 50 ) 95.9431818181818 0.458963313946735 209.043247908299 Trimmed Mean ( 32 / 50 ) 95.9767441860465 0.460172079925061 208.567073868706 Trimmed Mean ( 33 / 50 ) 96 0.463219792343072 207.245030516528 Trimmed Mean ( 34 / 50 ) 96.0243902439024 0.466258567770396 205.946650381315 Trimmed Mean ( 35 / 50 ) 96.05 0.469277656603574 204.676269258519 Trimmed Mean ( 36 / 50 ) 96.076923076923 0.472264096538717 203.438973618962 Trimmed Mean ( 37 / 50 ) 96.1052631578947 0.475202245907188 202.240759562119 Trimmed Mean ( 38 / 50 ) 96.1351351351351 0.478073204659159 201.088733269781 Trimmed Mean ( 39 / 50 ) 96.1666666666667 0.4808540914633 199.991366141898 Trimmed Mean ( 40 / 50 ) 96.2 0.483517135038435 198.958822818871 Trimmed Mean ( 41 / 50 ) 96.235294117647 0.48602852350695 198.003387585690 Trimmed Mean ( 42 / 50 ) 96.2727272727273 0.488346935479092 197.140025417133 Trimmed Mean ( 43 / 50 ) 96.3125 0.490421648030695 196.387130108849 Trimmed Mean ( 44 / 50 ) 96.3548387096774 0.492190075515049 195.767536777022 Trimmed Mean ( 45 / 50 ) 96.4 0.493574532577441 195.30991499217 Trimmed Mean ( 46 / 50 ) 96.448275862069 0.494477923974067 195.050721550771 Trimmed Mean ( 47 / 50 ) 96.5 0.494777924735123 195.036995742405 Trimmed Mean ( 48 / 50 ) 96.5555555555556 0.49431899569863 195.330457449024 Trimmed Mean ( 49 / 50 ) 96.6153846153846 0.492901225923845 196.013682932718 Trimmed Mean ( 50 / 50 ) 96.68 0.49026440180118 197.199714368018 Median 97.5 Midrange 85 Midmean - Weighted Average at Xnp 97.0677966101695 Midmean - Weighted Average at X(n+1)p 97.0677966101695 Midmean - Empirical Distribution Function 97.0677966101695 Midmean - Empirical Distribution Function - Averaging 97.0677966101695 Midmean - Empirical Distribution Function - Interpolation 97.0677966101695 Midmean - Closest Observation 97.0677966101695 Midmean - True Basic - Statistics Graphics Toolkit 97.0677966101695 Midmean - MS Excel (old versions) 97.0677966101695 Number of observations 150

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Nov/12/t1289575751r6f9mc0qbqc3k3m/1lbga1289575804.png (open in new window) http://www.freestatistics.org/blog/date/2010/Nov/12/t1289575751r6f9mc0qbqc3k3m/1lbga1289575804.ps (open in new window) http://www.freestatistics.org/blog/date/2010/Nov/12/t1289575751r6f9mc0qbqc3k3m/2lbga1289575804.png (open in new window) http://www.freestatistics.org/blog/date/2010/Nov/12/t1289575751r6f9mc0qbqc3k3m/2lbga1289575804.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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