datareeks-max.prijs-seda hovhannesian

*Unverified author*

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

Title produced by software: Central Tendency

Date of computation: Mon, 01 Jun 2009 09:24:26 -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/Jun/01/t12438699099tkgpyx7o7sjw6k.htm/, Retrieved Mon, 01 Jun 2009 17:25:09 +0200

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/Jun/01/t12438699099tkgpyx7o7sjw6k.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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5,44 5,44 5,44 5,44 5,44 5,49 5,49 5,49 5,49 5,49 5,49 5,60 5,60 5,60 5,60 5,60 5,60 5,60 5,67 5,67 5,67 5,67 5,67 5,67 5,67 5,67 5,67 5,82 5,82 5,95 5,95 5,95 5,95 5,95 5,95 6,02 6,02 6,05 6,05 6,05 6,12 6,12 6,12 6,12 6,12 6,12 6,12 6,12 6,17 6,17 6,17 6,17 6,17 6,28 6,27 6,28 6,28 6,27 6,27 6,28 6,59 6,59 6,59 6,59 6,59 6,63 6,63 6,63 6,63 6,63 6,63 6,63 6,63 6,63 6,63 6,63 6,63 6,63 6,63 6,63 6,63 6,63 6,79 6,79 6,79 6,81 6,80 6,80 6,85 6,85 6,85 6,85 6,85 6,85 6,86 6,86 6,88 6,88 6,88 6,91 6,91 6,91 6,91 6,99 6,99 6,99 7,02 7,02 7,05 7,05 7,05 7,05 7,10 7,10 7,10 7,10 7,12 7,13 7,18

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 6.33798319327731 0.0495355985949239 127.948048939633 Geometric Mean 6.31476031063177 Harmonic Mean 6.29122418121108 Quadratic Mean 6.36078426537076 Winsorized Mean ( 1 / 39 ) 6.33756302521008 0.0494768193485533 128.091561031103 Winsorized Mean ( 2 / 39 ) 6.33739495798319 0.0494541436364585 128.146895123084 Winsorized Mean ( 3 / 39 ) 6.33689075630252 0.0493873227361724 128.310068358114 Winsorized Mean ( 4 / 39 ) 6.33689075630252 0.0493873227361724 128.310068358114 Winsorized Mean ( 5 / 39 ) 6.33899159663866 0.0490716254685067 129.178349730985 Winsorized Mean ( 6 / 39 ) 6.33899159663866 0.0490716254685067 129.178349730985 Winsorized Mean ( 7 / 39 ) 6.33605042016807 0.0486955928962506 130.115479519214 Winsorized Mean ( 8 / 39 ) 6.33605042016807 0.0486955928962506 130.115479519214 Winsorized Mean ( 9 / 39 ) 6.33605042016807 0.0486955928962506 130.115479519214 Winsorized Mean ( 10 / 39 ) 6.33605042016807 0.0486955928962506 130.115479519214 Winsorized Mean ( 11 / 39 ) 6.34344537815126 0.0469213776563283 135.193076056149 Winsorized Mean ( 12 / 39 ) 6.34344537815126 0.0469213776563283 135.193076056149 Winsorized Mean ( 13 / 39 ) 6.34016806722689 0.0465271625816757 136.268100512192 Winsorized Mean ( 14 / 39 ) 6.34016806722689 0.0465271625816757 136.268100512192 Winsorized Mean ( 15 / 39 ) 6.34016806722689 0.0465271625816757 136.268100512192 Winsorized Mean ( 16 / 39 ) 6.32941176470588 0.0453058249778253 139.704149914581 Winsorized Mean ( 17 / 39 ) 6.32941176470588 0.0453058249778253 139.704149914581 Winsorized Mean ( 18 / 39 ) 6.34 0.0438981483566351 144.425226059489 Winsorized Mean ( 19 / 39 ) 6.34 0.0438981483566351 144.425226059489 Winsorized Mean ( 20 / 39 ) 6.33495798319328 0.0433520800871069 146.128120506894 Winsorized Mean ( 21 / 39 ) 6.33495798319328 0.0433520800871069 146.128120506894 Winsorized Mean ( 22 / 39 ) 6.33495798319328 0.0433520800871069 146.128120506894 Winsorized Mean ( 23 / 39 ) 6.33109243697479 0.0429443998354266 147.425332784649 Winsorized Mean ( 24 / 39 ) 6.33109243697479 0.0429443998354266 147.425332784649 Winsorized Mean ( 25 / 39 ) 6.32899159663866 0.0427262103993746 148.129018171274 Winsorized Mean ( 26 / 39 ) 6.32899159663866 0.0427262103993746 148.129018171274 Winsorized Mean ( 27 / 39 ) 6.36302521008403 0.038455725494013 165.463663169602 Winsorized Mean ( 28 / 39 ) 6.36302521008403 0.038455725494013 165.463663169602 Winsorized Mean ( 29 / 39 ) 6.39470588235294 0.0348375732430261 183.557730549818 Winsorized Mean ( 30 / 39 ) 6.39470588235294 0.0348375732430261 183.557730549818 Winsorized Mean ( 31 / 39 ) 6.38428571428571 0.0337024885271648 189.430691717018 Winsorized Mean ( 32 / 39 ) 6.38159663865546 0.0334158843142282 190.974944090832 Winsorized Mean ( 33 / 39 ) 6.38159663865546 0.0334158843142282 190.974944090832 Winsorized Mean ( 34 / 39 ) 6.37873949579832 0.0331139337900287 192.630073377724 Winsorized Mean ( 35 / 39 ) 6.39932773109244 0.030911871712005 207.018448792513 Winsorized Mean ( 36 / 39 ) 6.39932773109244 0.030911871712005 207.018448792513 Winsorized Mean ( 37 / 39 ) 6.35890756302521 0.0249428316348388 254.939280997408 Winsorized Mean ( 38 / 39 ) 6.35890756302521 0.0249428316348388 254.939280997408 Winsorized Mean ( 39 / 39 ) 6.35890756302521 0.0249428316348388 254.939280997408 Trimmed Mean ( 1 / 39 ) 6.33846153846154 0.0492655482442357 128.659108938327 Trimmed Mean ( 2 / 39 ) 6.33939130434783 0.0490229926217431 129.314653498655 Trimmed Mean ( 3 / 39 ) 6.3404424778761 0.0487585107778128 130.037656538954 Trimmed Mean ( 4 / 39 ) 6.34171171171171 0.0484826055881602 130.803855006927 Trimmed Mean ( 5 / 39 ) 6.34302752293578 0.0481673138352757 131.687383370139 Trimmed Mean ( 6 / 39 ) 6.34392523364486 0.0478890957448545 132.471184410002 Trimmed Mean ( 7 / 39 ) 6.34485714285714 0.0475695200312353 133.380726538568 Trimmed Mean ( 8 / 39 ) 6.34631067961165 0.0472770832661676 134.236510401503 Trimmed Mean ( 9 / 39 ) 6.34782178217822 0.0469395237545597 135.234047438788 Trimmed Mean ( 10 / 39 ) 6.34939393939394 0.0465511907669241 136.395951097890 Trimmed Mean ( 11 / 39 ) 6.35103092783505 0.0461055221160047 137.749897113309 Trimmed Mean ( 12 / 39 ) 6.3518947368421 0.0458624690082762 138.498752339213 Trimmed Mean ( 13 / 39 ) 6.35279569892473 0.0455747067367643 139.393013225909 Trimmed Mean ( 14 / 39 ) 6.35406593406593 0.0452889186709382 140.300676645285 Trimmed Mean ( 15 / 39 ) 6.35539325842697 0.0449509027871903 141.385219525292 Trimmed Mean ( 16 / 39 ) 6.3567816091954 0.0445532321003468 142.678349235766 Trimmed Mean ( 17 / 39 ) 6.35917647058824 0.0442371416265956 143.751974851039 Trimmed Mean ( 18 / 39 ) 6.36168674698795 0.0438591028347876 145.048264460669 Trimmed Mean ( 19 / 39 ) 6.36345679012346 0.0435904623777187 145.982777952274 Trimmed Mean ( 20 / 39 ) 6.3653164556962 0.0432623074488411 147.133077985343 Trimmed Mean ( 21 / 39 ) 6.36766233766234 0.0429280725833058 148.333292283396 Trimmed Mean ( 22 / 39 ) 6.37013333333333 0.0425207922995066 149.812197488316 Trimmed Mean ( 23 / 39 ) 6.3727397260274 0.0420277777760552 151.631612786774 Trimmed Mean ( 24 / 39 ) 6.37577464788732 0.0414814505934067 153.701824711519 Trimmed Mean ( 25 / 39 ) 6.37898550724638 0.0408212501534354 156.266294718305 Trimmed Mean ( 26 / 39 ) 6.38253731343284 0.0400510434630323 159.36007558265 Trimmed Mean ( 27 / 39 ) 6.38630769230769 0.0391192513783478 163.252298223745 Trimmed Mean ( 28 / 39 ) 6.38793650793651 0.0386346328520783 165.342234062226 Trimmed Mean ( 29 / 39 ) 6.38967213114754 0.0380321744815968 168.007015592532 Trimmed Mean ( 30 / 39 ) 6.3893220338983 0.0377972260684239 169.042088494319 Trimmed Mean ( 31 / 39 ) 6.38894736842105 0.0374782177427212 170.470949613443 Trimmed Mean ( 32 / 39 ) 6.38927272727273 0.0372161350778344 171.680178876987 Trimmed Mean ( 33 / 39 ) 6.38981132075472 0.0368965629100406 173.181749647902 Trimmed Mean ( 34 / 39 ) 6.39039215686275 0.0364621326904822 175.261063611094 Trimmed Mean ( 35 / 39 ) 6.39122448979592 0.0359310477385066 177.874704247674 Trimmed Mean ( 36 / 39 ) 6.39063829787234 0.0355977166883570 179.523826031307 Trimmed Mean ( 37 / 39 ) 6.39 0.0351245978444932 181.923791079129 Trimmed Mean ( 38 / 39 ) 6.39232558139535 0.0354481469124137 180.328906816757 Trimmed Mean ( 39 / 39 ) 6.39487804878049 0.0357448989217931 178.903234913937 Median 6.28 Midrange 6.31 Midmean - Weighted Average at Xnp 6.418 Midmean - Weighted Average at X(n+1)p 6.418 Midmean - Empirical Distribution Function 6.418 Midmean - Empirical Distribution Function - Averaging 6.418 Midmean - Empirical Distribution Function - Interpolation 6.418 Midmean - Closest Observation 6.418 Midmean - True Basic - Statistics Graphics Toolkit 6.418 Midmean - MS Excel (old versions) 6.418 Number of observations 119

Charts produced by software:

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/01/t12438699099tkgpyx7o7sjw6k/18ak31243869861.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/01/t12438699099tkgpyx7o7sjw6k/18ak31243869861.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/01/t12438699099tkgpyx7o7sjw6k/2w83p1243869861.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/01/t12438699099tkgpyx7o7sjw6k/2w83p1243869861.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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