RIA VANTHILLO PRIJS BRUIN BROOD CENTRUMMATEN

*Unverified author*

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

Title produced by software: Central Tendency

Date of computation: Sun, 08 Mar 2009 09:20:45 -0600

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2009/Mar/08/t1236525719a3l3pc9vdyitkml.htm/, Retrieved Sun, 08 Mar 2009 16:21:59 +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/2009/Mar/08/t1236525719a3l3pc9vdyitkml.htm/}, year = {2009}, } @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 = {2009}, 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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1.38 1.38 1.38 1.38 1.38 1.38 1.38 1.38 1.38 1.38 1.38 1.38 1.38 1.38 1.38 1.38 1.38 1.38 1.38 1.38 1.38 1.38 1.38 1.43 1.43 1.43 1.43 1.43 1.43 1.43 1.43 1.43 1.43 1.43 1.43 1.43 1.43 1.43 1.43 1.43 1.43 1.43 1.44 1.48 1.48 1.48 1.48 1.48 1.48 1.48 1.48 1.48 1.48 1.48 1.48 1.48 1.48 1.48 1.48 1.48 1.48 1.48 1.48 1.48 1.48 1.48 1.48 1.48 1.48 1.48 1.48 1.48 1.48 1.57 1.58 1.58 1.58 1.58 1.59 1.6 1.6 1.61 1.61 1.61 1.62 1.63 1.63 1.64 1.64 1.64 1.64 1.64 1.65 1.65 1.65 1.65 1.65 1.66 1.66 1.67 1.68 1.68 1.68 1.68 1.69 1.7 1.7 1.71 1.72 1.73 1.74 1.74 1.75 1.75 1.75 1.76 1.79 1.83 1.84 1.85 1.87 1.87 1.87 1.88 1.88 1.88

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 3 seconds R Server 'Herman Ole Andreas Wold' @ 193.190.124.10:1001 Central Tendency - Ungrouped Data Measure Value S.E. Value/S.E. Arithmetic Mean 1.54444444444444 0.0129984397381417 118.817679318275 Geometric Mean 1.53786042044277 Harmonic Mean 1.53153584074654 Quadratic Mean 1.55126676346416 Winsorized Mean ( 1 / 42 ) 1.54444444444444 0.0129984397381417 118.817679318275 Winsorized Mean ( 2 / 42 ) 1.54444444444444 0.0129984397381417 118.817679318275 Winsorized Mean ( 3 / 42 ) 1.54420634920635 0.0129498927737686 119.244720877868 Winsorized Mean ( 4 / 42 ) 1.54420634920635 0.0129498927737686 119.244720877868 Winsorized Mean ( 5 / 42 ) 1.54420634920635 0.0129498927737686 119.244720877868 Winsorized Mean ( 6 / 42 ) 1.54325396825397 0.0127624595157006 120.921360522667 Winsorized Mean ( 7 / 42 ) 1.54269841269841 0.0126568446622861 121.886493344998 Winsorized Mean ( 8 / 42 ) 1.54206349206349 0.0125388627419385 122.982723696765 Winsorized Mean ( 9 / 42 ) 1.53920634920635 0.012037825661706 127.864150259526 Winsorized Mean ( 10 / 42 ) 1.53682539682540 0.0116568125969055 131.839247139769 Winsorized Mean ( 11 / 42 ) 1.53595238095238 0.0115250884768445 133.270333155214 Winsorized Mean ( 12 / 42 ) 1.53595238095238 0.0115250884768445 133.270333155214 Winsorized Mean ( 13 / 42 ) 1.53595238095238 0.0115250884768445 133.270333155214 Winsorized Mean ( 14 / 42 ) 1.53484126984127 0.0113622790732969 135.082166169319 Winsorized Mean ( 15 / 42 ) 1.53484126984127 0.0113622790732969 135.082166169319 Winsorized Mean ( 16 / 42 ) 1.53357142857143 0.0111813133713121 137.154856289612 Winsorized Mean ( 17 / 42 ) 1.53222222222222 0.0109943066876200 139.365061004489 Winsorized Mean ( 18 / 42 ) 1.53079365079365 0.0108018829484982 141.715445176758 Winsorized Mean ( 19 / 42 ) 1.52928571428571 0.0106046881345393 144.208457135562 Winsorized Mean ( 20 / 42 ) 1.52928571428571 0.0106046881345393 144.208457135562 Winsorized Mean ( 21 / 42 ) 1.52761904761905 0.0103931775982887 146.982867671826 Winsorized Mean ( 22 / 42 ) 1.52587301587302 0.0101782649478906 149.914845377379 Winsorized Mean ( 23 / 42 ) 1.535 0.00923468272759628 166.221195170346 Winsorized Mean ( 24 / 42 ) 1.535 0.00923468272759628 166.221195170346 Winsorized Mean ( 25 / 42 ) 1.535 0.00923468272759628 166.221195170346 Winsorized Mean ( 26 / 42 ) 1.53293650793651 0.00897903551954073 170.72396078626 Winsorized Mean ( 27 / 42 ) 1.53079365079365 0.00872114975280404 175.526586996338 Winsorized Mean ( 28 / 42 ) 1.53079365079365 0.00872114975280404 175.526586996338 Winsorized Mean ( 29 / 42 ) 1.52849206349206 0.00845234443691345 180.836461989974 Winsorized Mean ( 30 / 42 ) 1.52849206349206 0.00845234443691345 180.836461989974 Winsorized Mean ( 31 / 42 ) 1.52849206349206 0.00845234443691345 180.836461989974 Winsorized Mean ( 32 / 42 ) 1.52849206349206 0.00845234443691345 180.836461989974 Winsorized Mean ( 33 / 42 ) 1.52849206349206 0.00845234443691345 180.836461989974 Winsorized Mean ( 34 / 42 ) 1.52579365079365 0.00814577750163065 187.310990324522 Winsorized Mean ( 35 / 42 ) 1.52579365079365 0.00814577750163065 187.310990324522 Winsorized Mean ( 36 / 42 ) 1.52579365079365 0.00814577750163065 187.310990324522 Winsorized Mean ( 37 / 42 ) 1.52579365079365 0.00814577750163065 187.310990324522 Winsorized Mean ( 38 / 42 ) 1.52579365079365 0.00814577750163065 187.310990324522 Winsorized Mean ( 39 / 42 ) 1.52269841269841 0.00780184162094159 195.171664163395 Winsorized Mean ( 40 / 42 ) 1.52269841269841 0.00780184162094159 195.171664163395 Winsorized Mean ( 41 / 42 ) 1.51944444444444 0.00744700264029194 204.034363600666 Winsorized Mean ( 42 / 42 ) 1.51944444444444 0.00677184231391392 224.376820074868 Trimmed Mean ( 1 / 42 ) 1.54306451612903 0.0128571084462924 120.016450244223 Trimmed Mean ( 2 / 42 ) 1.54163934426230 0.0126997577048778 121.391240690377 Trimmed Mean ( 3 / 42 ) 1.54016666666667 0.0125244765028857 122.972538318213 Trimmed Mean ( 4 / 42 ) 1.53872881355932 0.012348779109872 124.605744411544 Trimmed Mean ( 5 / 42 ) 1.53724137931034 0.0121525697129510 126.495170619931 Trimmed Mean ( 6 / 42 ) 1.53570175438596 0.0119331375483287 128.692202546601 Trimmed Mean ( 7 / 42 ) 1.53428571428571 0.0117320156499904 130.777673680223 Trimmed Mean ( 8 / 42 ) 1.53290909090909 0.0115289427678146 132.961809402725 Trimmed Mean ( 9 / 42 ) 1.53157407407407 0.0113238935375634 135.251543030987 Trimmed Mean ( 10 / 42 ) 1.53056603773585 0.0111832166226170 136.862772973602 Trimmed Mean ( 11 / 42 ) 1.52980769230769 0.0110864118712196 137.989433378267 Trimmed Mean ( 12 / 42 ) 1.52911764705882 0.0109959337900027 139.06210025101 Trimmed Mean ( 13 / 42 ) 1.5284 0.0108922361377638 140.320130840808 Trimmed Mean ( 14 / 42 ) 1.52765306122449 0.0107735728562710 141.796327142791 Trimmed Mean ( 15 / 42 ) 1.52697916666667 0.0106603460491406 143.239174378375 Trimmed Mean ( 16 / 42 ) 1.52627659574468 0.0105304126916404 144.939865173216 Trimmed Mean ( 17 / 42 ) 1.52565217391304 0.0104054273342457 146.620809016840 Trimmed Mean ( 18 / 42 ) 1.52511111111111 0.0102858574038796 148.272628253224 Trimmed Mean ( 19 / 42 ) 1.52465909090909 0.0101721710226178 149.885318239245 Trimmed Mean ( 20 / 42 ) 1.52430232558140 0.0100648250398478 151.448467265601 Trimmed Mean ( 21 / 42 ) 1.52392857142857 0.0099396022544157 153.318868544419 Trimmed Mean ( 22 / 42 ) 1.52365853658537 0.00981998802767366 155.158899612866 Trimmed Mean ( 23 / 42 ) 1.5235 0.00970628792672336 156.960107870435 Trimmed Mean ( 24 / 42 ) 1.52269230769231 0.0096744770947605 157.392724462283 Trimmed Mean ( 25 / 42 ) 1.52184210526316 0.00963129133881774 158.01018282248 Trimmed Mean ( 26 / 42 ) 1.52094594594595 0.00957475878984462 158.849531286274 Trimmed Mean ( 27 / 42 ) 1.52013888888889 0.00953433186839356 159.438428394565 Trimmed Mean ( 28 / 42 ) 1.51942857142857 0.00951164855051304 159.743977435606 Trimmed Mean ( 29 / 42 ) 1.51867647058824 0.00947688934178001 160.250522699782 Trimmed Mean ( 30 / 42 ) 1.51803030303030 0.0094615396100983 160.442207673063 Trimmed Mean ( 31 / 42 ) 1.51734375 0.0094339868829114 160.838017778941 Trimmed Mean ( 32 / 42 ) 1.51661290322581 0.00939171509617693 161.484125923195 Trimmed Mean ( 33 / 42 ) 1.51583333333333 0.00933159285628155 162.441006233245 Trimmed Mean ( 34 / 42 ) 1.515 0.00924967912002095 163.789465595707 Trimmed Mean ( 35 / 42 ) 1.51428571428571 0.00918729056782992 164.823971017975 Trimmed Mean ( 36 / 42 ) 1.51351851851852 0.00910056174845734 166.310449876908 Trimmed Mean ( 37 / 42 ) 1.51269230769231 0.00898345800310036 168.386417253829 Trimmed Mean ( 38 / 42 ) 1.5118 0.00882801662611826 171.250243857407 Trimmed Mean ( 39 / 42 ) 1.51083333333333 0.00862349448949798 175.199663567163 Trimmed Mean ( 40 / 42 ) 1.51 0.00842700971600385 179.185743328661 Trimmed Mean ( 41 / 42 ) 1.50909090909091 0.00816594655061256 184.802937386078 Trimmed Mean ( 42 / 42 ) 1.50833333333333 0.00790416367046267 190.827694898307 Median 1.48 Midrange 1.63 Midmean - Weighted Average at Xnp 1.51148648648649 Midmean - Weighted Average at X(n+1)p 1.51148648648649 Midmean - Empirical Distribution Function 1.51148648648649 Midmean - Empirical Distribution Function - Averaging 1.51148648648649 Midmean - Empirical Distribution Function - Interpolation 1.51148648648649 Midmean - Closest Observation 1.51148648648649 Midmean - True Basic - Statistics Graphics Toolkit 1.51148648648649 Midmean - MS Excel (old versions) 1.51148648648649 Number of observations 126

Charts produced by software:

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Mar/08/t1236525719a3l3pc9vdyitkml/152kh1236525640.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Mar/08/t1236525719a3l3pc9vdyitkml/152kh1236525640.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Mar/08/t1236525719a3l3pc9vdyitkml/2kjna1236525640.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Mar/08/t1236525719a3l3pc9vdyitkml/2kjna1236525640.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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