*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, 24 Dec 2010 14:59:34 +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/Dec/24/t1293202668v4zh72bxs6szy0t.htm/, Retrieved Fri, 24 Dec 2010 15:57:48 +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/Dec/24/t1293202668v4zh72bxs6szy0t.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?

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Dataseries X:

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6,7 6,7 6,5 6,3 6,3 6,3 6,5 6,6 6,5 6,3 6,3 6,5 7 7,1 7,3 7,3 7,4 7,4 7,3 7,4 7,5 7,7 7,7 7,7 7,7 7,7 7,8 8 8,1 8,1 8,2 8,2 8,2 8,1 8,1 8,2 8,3 8,3 8,4 8,5 8,5 8,4 8 7,9 8,1 8,5 8,8 8,8 8,6 8,3 8,3 8,3 8,4 8,4 8,5 8,6 8,6 8,6 8,6 8,6 8,5 8,4 8,4 8,4 8,5 8,5 8,6 8,6 8,4 8,2 8 8 8 8 7,9 7,9 7,8 7,8 8 7,8 7,4 7,2 7 7 7,2 7,2 7,2 7 6,9 6,8 6,8 6,8 6,9 7,2 7,2 7,2 7,1 7,2 7,3 7,5 7,6 7,7 7,7 7,7 7,8 8 8,1 8,1 8 8,1 8,2 8,3 8,4 8,4 8,4 8,5 8,5 8,6 8,6 8,5 8,5

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 'RServer@AstonUniversity' @ vre.aston.ac.uk Central Tendency - Ungrouped Data Measure Value S.E. Value/S.E. Arithmetic Mean 7.7892561983471 0.0621891902958961 125.250966627574 Geometric Mean 7.75818115708727 Harmonic Mean 7.72583262373508 Quadratic Mean 7.81899044444025 Winsorized Mean ( 1 / 40 ) 7.7892561983471 0.0621891902958961 125.250966627574 Winsorized Mean ( 2 / 40 ) 7.78595041322314 0.0617837001105009 126.019490566248 Winsorized Mean ( 3 / 40 ) 7.78595041322314 0.0617837001105009 126.019490566248 Winsorized Mean ( 4 / 40 ) 7.78595041322314 0.0617837001105009 126.019490566248 Winsorized Mean ( 5 / 40 ) 7.79421487603306 0.0602142355318931 129.44139881847 Winsorized Mean ( 6 / 40 ) 7.79421487603306 0.0602142355318931 129.44139881847 Winsorized Mean ( 7 / 40 ) 7.79421487603306 0.0602142355318931 129.44139881847 Winsorized Mean ( 8 / 40 ) 7.79421487603306 0.0602142355318931 129.44139881847 Winsorized Mean ( 9 / 40 ) 7.80165289256198 0.058915631313346 132.420763703074 Winsorized Mean ( 10 / 40 ) 7.8099173553719 0.0575486972933541 135.709715817908 Winsorized Mean ( 11 / 40 ) 7.8099173553719 0.0575486972933541 135.709715817908 Winsorized Mean ( 12 / 40 ) 7.8099173553719 0.0549029316066554 142.249550740296 Winsorized Mean ( 13 / 40 ) 7.8099173553719 0.0549029316066554 142.249550740296 Winsorized Mean ( 14 / 40 ) 7.8099173553719 0.0549029316066554 142.249550740296 Winsorized Mean ( 15 / 40 ) 7.82231404958678 0.0530539462874783 147.440757888221 Winsorized Mean ( 16 / 40 ) 7.82231404958678 0.0530539462874783 147.440757888221 Winsorized Mean ( 17 / 40 ) 7.83636363636364 0.0510765643617231 153.42385953892 Winsorized Mean ( 18 / 40 ) 7.83636363636364 0.0510765643617231 153.42385953892 Winsorized Mean ( 19 / 40 ) 7.83636363636364 0.0510765643617231 153.42385953892 Winsorized Mean ( 20 / 40 ) 7.83636363636364 0.0510765643617231 153.42385953892 Winsorized Mean ( 21 / 40 ) 7.85371900826446 0.0487734025527831 161.024628121138 Winsorized Mean ( 22 / 40 ) 7.85371900826446 0.0487734025527831 161.024628121138 Winsorized Mean ( 23 / 40 ) 7.85371900826446 0.0443508631995847 177.081536675435 Winsorized Mean ( 24 / 40 ) 7.85371900826446 0.0443508631995847 177.081536675435 Winsorized Mean ( 25 / 40 ) 7.85371900826446 0.0443508631995847 177.081536675435 Winsorized Mean ( 26 / 40 ) 7.85371900826446 0.0443508631995847 177.081536675435 Winsorized Mean ( 27 / 40 ) 7.85371900826446 0.0443508631995847 177.081536675435 Winsorized Mean ( 28 / 40 ) 7.85371900826446 0.0443508631995847 177.081536675435 Winsorized Mean ( 29 / 40 ) 7.85371900826446 0.0443508631995847 177.081536675435 Winsorized Mean ( 30 / 40 ) 7.85371900826446 0.0443508631995847 177.081536675435 Winsorized Mean ( 31 / 40 ) 7.8793388429752 0.0412764207960841 190.892007858461 Winsorized Mean ( 32 / 40 ) 7.8793388429752 0.0412764207960841 190.892007858461 Winsorized Mean ( 33 / 40 ) 7.8793388429752 0.0412764207960841 190.892007858461 Winsorized Mean ( 34 / 40 ) 7.85123966942149 0.0384284190651245 204.308162043201 Winsorized Mean ( 35 / 40 ) 7.8801652892562 0.0350446357391817 224.860813161364 Winsorized Mean ( 36 / 40 ) 7.8801652892562 0.0350446357391817 224.860813161364 Winsorized Mean ( 37 / 40 ) 7.8801652892562 0.0350446357391817 224.860813161364 Winsorized Mean ( 38 / 40 ) 7.8801652892562 0.0350446357391817 224.860813161364 Winsorized Mean ( 39 / 40 ) 7.91239669421488 0.0314386509134663 251.677360965439 Winsorized Mean ( 40 / 40 ) 7.8793388429752 0.0281651308212153 279.755094801126 Trimmed Mean ( 1 / 40 ) 7.79327731092437 0.061386569488755 126.954110252927 Trimmed Mean ( 2 / 40 ) 7.7974358974359 0.0604953218416412 128.893204632373 Trimmed Mean ( 3 / 40 ) 7.80347826086957 0.0597340972301691 130.636916312655 Trimmed Mean ( 4 / 40 ) 7.80973451327434 0.0588818671228164 132.633948189596 Trimmed Mean ( 5 / 40 ) 7.81621621621622 0.0579267879388989 134.932670951145 Trimmed Mean ( 6 / 40 ) 7.82110091743119 0.057278186776646 136.545888715529 Trimmed Mean ( 7 / 40 ) 7.82616822429907 0.0565469743165114 138.401184482365 Trimmed Mean ( 8 / 40 ) 7.83142857142857 0.0557222686119018 140.5439650344 Trimmed Mean ( 9 / 40 ) 7.8368932038835 0.0547911996512886 143.031969618486 Trimmed Mean ( 10 / 40 ) 7.84158415841584 0.0539759265505965 145.279287629555 Trimmed Mean ( 11 / 40 ) 7.84545454545455 0.053283695346715 147.239310156784 Trimmed Mean ( 12 / 40 ) 7.84948453608247 0.0524961893425621 149.524844267475 Trimmed Mean ( 13 / 40 ) 7.85368421052632 0.0519886826842824 151.065266612356 Trimmed Mean ( 14 / 40 ) 7.85806451612903 0.0514020940266571 152.874404534061 Trimmed Mean ( 15 / 40 ) 7.86263736263736 0.0507248641963399 155.005587244228 Trimmed Mean ( 16 / 40 ) 7.86629213483146 0.0502024456281748 156.691412866482 Trimmed Mean ( 17 / 40 ) 7.87011494252874 0.0495937773247987 158.691581223707 Trimmed Mean ( 18 / 40 ) 7.87294117647059 0.0491492962325158 160.184209743823 Trimmed Mean ( 19 / 40 ) 7.87590361445783 0.0486246444001173 161.973495366864 Trimmed Mean ( 20 / 40 ) 7.87901234567901 0.0480070741116501 164.121902687816 Trimmed Mean ( 21 / 40 ) 7.88227848101266 0.047281141151325 166.710834152355 Trimmed Mean ( 22 / 40 ) 7.88441558441558 0.0467342560352314 168.707416214603 Trimmed Mean ( 23 / 40 ) 7.88666666666667 0.0460838770474417 171.137221344194 Trimmed Mean ( 24 / 40 ) 7.88904109589041 0.0458540486119615 172.046773070164 Trimmed Mean ( 25 / 40 ) 7.89154929577465 0.0455569813176158 173.223709463014 Trimmed Mean ( 26 / 40 ) 7.89420289855072 0.0451805159276019 174.725824539068 Trimmed Mean ( 27 / 40 ) 7.89701492537313 0.0447097352013154 176.628532685669 Trimmed Mean ( 28 / 40 ) 7.9 0.0441261304060914 179.03224069948 Trimmed Mean ( 29 / 40 ) 7.9031746031746 0.043406428600753 182.073827724161 Trimmed Mean ( 30 / 40 ) 7.90655737704918 0.0425208950537202 185.945224508096 Trimmed Mean ( 31 / 40 ) 7.90655737704918 0.0414307894818673 190.837719385231 Trimmed Mean ( 32 / 40 ) 7.91228070175439 0.0405993764720102 194.886754165036 Trimmed Mean ( 33 / 40 ) 7.91454545454545 0.0395614155645275 200.057185558395 Trimmed Mean ( 34 / 40 ) 7.91698113207547 0.0382619351648451 206.915334991983 Trimmed Mean ( 35 / 40 ) 7.92156862745098 0.0370811220392238 213.628072502004 Trimmed Mean ( 36 / 40 ) 7.92448979591837 0.0362496319761869 218.608834460005 Trimmed Mean ( 37 / 40 ) 7.92765957446808 0.0351686997720891 225.418045757828 Trimmed Mean ( 38 / 40 ) 7.93111111111111 0.0337582346440846 234.938562242054 Trimmed Mean ( 39 / 40 ) 7.93488372093023 0.0318988783151632 248.751183114749 Trimmed Mean ( 40 / 40 ) 7.93658536585366 0.030394980643267 261.114999841651 Median 8 Midrange 7.55 Midmean - Weighted Average at Xnp 7.88666666666667 Midmean - Weighted Average at X(n+1)p 7.88666666666667 Midmean - Empirical Distribution Function 7.88666666666667 Midmean - Empirical Distribution Function - Averaging 7.88666666666667 Midmean - Empirical Distribution Function - Interpolation 7.88666666666667 Midmean - Closest Observation 7.88666666666667 Midmean - True Basic - Statistics Graphics Toolkit 7.88666666666667 Midmean - MS Excel (old versions) 7.88666666666667 Number of observations 121

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Dec/24/t1293202668v4zh72bxs6szy0t/1ndht1293202770.png (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/24/t1293202668v4zh72bxs6szy0t/1ndht1293202770.ps (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/24/t1293202668v4zh72bxs6szy0t/2xngw1293202770.png (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/24/t1293202668v4zh72bxs6szy0t/2xngw1293202770.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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