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

Title produced by software: Central Tendency

Date of computation: Mon, 20 Oct 2008 11:25:51 -0600

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2008/Oct/20/t1224523615h88kuod4bogd5xe.htm/, Retrieved Mon, 20 Oct 2008 17:26:55 +0000

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/2008/Oct/20/t1224523615h88kuod4bogd5xe.htm/}, year = {2008}, } @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 = {2008}, note = {{ISBN} 3-900051-07-0}, url = {http://www.R-project.org}, }

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Dataseries X:

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15.22 14.28 14.61 14.19 14.02 14.22 14.80 15.05 15.24 15.85 15.43 15.41 15.53 15.95 15.72 15.68 16.06 15.27 16.01 15.44 15.47 15.49 15.38 16.62 17.25 16.37 16.14 15.76 15.54 15.46 15.26 16.02 15.67 15.67 15.48 16.07 16.65 16.18 16.55 16.58 17.73 17.94 18.66 18.73 19.07 19.48 19.52 19.60 20.32 19.84 19.81 20.64 22.12 21.50 21.77 20.29 21.76 22.35 22.15 23.83 24.46 25.13 24.36 24.45 23.66 25.97 25.20 24.41 25.32 26.36 28.03 28.95 27.25 27.47 28.75 29.24 28.03 27.34 26.47 28.30 27.90 26.69 28.31 28.84 28.56 28.25 28.93 28.22 31.77 31.64 30.60 32.34 31.51 31.39 32.19 33.11 33.99 34.30 34.53 33.67 34.72 34.91 36.24 37.47 36.94 38.55 39.88 37.78 40.09 40.17 40.67 44.82 40.89 41.47 44.67

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 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 Central Tendency - Ungrouped Data Measure Value S.E. Value/S.E. Arithmetic Mean 24.0509565217391 0.782590809355739 30.7324801597643 Geometric Mean 22.6923322094642 Harmonic Mean 21.474661580707 Quadratic Mean 25.4611002187224 Winsorized Mean ( 1 / 38 ) 24.0511304347826 0.782123317827899 30.7510719685190 Winsorized Mean ( 2 / 38 ) 23.996 0.770085028045298 31.160195466868 Winsorized Mean ( 3 / 38 ) 23.9824347826087 0.766942164455837 31.2701998847916 Winsorized Mean ( 4 / 38 ) 23.9862608695652 0.764214971501951 31.3867979090017 Winsorized Mean ( 5 / 38 ) 23.9727826086957 0.759216822650798 31.5756736329879 Winsorized Mean ( 6 / 38 ) 23.9816521739130 0.757070621350612 31.6769023887492 Winsorized Mean ( 7 / 38 ) 23.9792173913043 0.753631868928473 31.8182104286519 Winsorized Mean ( 8 / 38 ) 23.8880869565217 0.736847366232385 32.4193151136106 Winsorized Mean ( 9 / 38 ) 23.8293913043478 0.726349054308594 32.8070796857178 Winsorized Mean ( 10 / 38 ) 23.8033043478261 0.721749323354453 32.9800161601762 Winsorized Mean ( 11 / 38 ) 23.7631304347826 0.712336625884788 33.359411226773 Winsorized Mean ( 12 / 38 ) 23.6932173913044 0.700345512940177 33.8307548967308 Winsorized Mean ( 13 / 38 ) 23.5451304347826 0.677217073872499 34.7674790597726 Winsorized Mean ( 14 / 38 ) 23.5232173913043 0.67370042195925 34.9164355914968 Winsorized Mean ( 15 / 38 ) 23.5010434782609 0.669829530483048 35.0851110749224 Winsorized Mean ( 16 / 38 ) 23.4704347826087 0.665086533845586 35.2892948334116 Winsorized Mean ( 17 / 38 ) 23.4260869565217 0.65843260589158 35.5785645287122 Winsorized Mean ( 18 / 38 ) 23.3775652173913 0.651270044690119 35.8953484932884 Winsorized Mean ( 19 / 38 ) 23.2916521739130 0.637905694849565 36.512688884845 Winsorized Mean ( 20 / 38 ) 23.1594782608696 0.619977028233648 37.3553812579997 Winsorized Mean ( 21 / 38 ) 23.1558260869565 0.613880679508996 37.7204021235485 Winsorized Mean ( 22 / 38 ) 23.0754782608696 0.603617599654732 38.2286372598623 Winsorized Mean ( 23 / 38 ) 23.0514782608696 0.600127665587483 38.4109575056897 Winsorized Mean ( 24 / 38 ) 23.0326956521739 0.595832620281822 38.6563186843979 Winsorized Mean ( 25 / 38 ) 23.0153043478261 0.591649394211705 38.9002415501345 Winsorized Mean ( 26 / 38 ) 22.8570434782609 0.567671653007233 40.2645496867353 Winsorized Mean ( 27 / 38 ) 22.5612173913043 0.528254066936139 42.7090273476906 Winsorized Mean ( 28 / 38 ) 22.5052173913043 0.518887670073667 43.3720411743629 Winsorized Mean ( 29 / 38 ) 22.5026956521739 0.518061638713308 43.4363287504998 Winsorized Mean ( 30 / 38 ) 22.4896521739130 0.514367961831983 43.7228868100833 Winsorized Mean ( 31 / 38 ) 22.4680869565217 0.511451605143187 43.93003508168 Winsorized Mean ( 32 / 38 ) 22.4346956521739 0.503646661005224 44.5445138212506 Winsorized Mean ( 33 / 38 ) 22.3744347826087 0.494785489140483 45.2204748798847 Winsorized Mean ( 34 / 38 ) 22.4276521739130 0.488333071653043 45.9269573899507 Winsorized Mean ( 35 / 38 ) 22.4672173913043 0.480789849568549 46.7298080678408 Winsorized Mean ( 36 / 38 ) 22.4672173913043 0.478786104072293 46.9253748181296 Winsorized Mean ( 37 / 38 ) 22.4189565217391 0.470981129793009 47.6005408785529 Winsorized Mean ( 38 / 38 ) 22.4288695652174 0.469911116207392 47.7300255125665 Trimmed Mean ( 1 / 38 ) 23.9559292035398 0.769613151682212 31.1272347037953 Trimmed Mean ( 2 / 38 ) 23.8572972972973 0.755578683760826 31.5748681243226 Trimmed Mean ( 3 / 38 ) 23.7841284403670 0.746893569114726 31.8440664425023 Trimmed Mean ( 4 / 38 ) 23.7130841121495 0.738368984336944 32.1154932224624 Trimmed Mean ( 5 / 38 ) 23.6382857142857 0.72957789815172 32.3999476603799 Trimmed Mean ( 6 / 38 ) 23.5635922330097 0.720940803132503 32.6845035412414 Trimmed Mean ( 7 / 38 ) 23.4842574257426 0.711595172854896 33.0022719680974 Trimmed Mean ( 8 / 38 ) 23.4021212121212 0.701658036848898 33.3526019558169 Trimmed Mean ( 9 / 38 ) 23.3301030927835 0.693609289541868 33.6357996418894 Trimmed Mean ( 10 / 38 ) 23.2629473684211 0.686258611479254 33.8982228846309 Trimmed Mean ( 11 / 38 ) 23.1961290322581 0.678550744914127 34.184811093522 Trimmed Mean ( 12 / 38 ) 23.130989010989 0.671145814736606 34.4649232746342 Trimmed Mean ( 13 / 38 ) 23.0704494382022 0.664403026611091 34.7235766758578 Trimmed Mean ( 14 / 38 ) 23.022183908046 0.659936945164323 34.8854297016414 Trimmed Mean ( 15 / 38 ) 22.9737647058824 0.655082349399657 35.0700407772189 Trimmed Mean ( 16 / 38 ) 22.9250602409639 0.649804857198565 35.2799151729925 Trimmed Mean ( 17 / 38 ) 22.8766666666667 0.644139271613343 35.5150938233725 Trimmed Mean ( 18 / 38 ) 22.8296202531646 0.638261301682556 35.7684543822133 Trimmed Mean ( 19 / 38 ) 22.7841558441558 0.63217407831943 36.0409523666728 Trimmed Mean ( 20 / 38 ) 22.7432 0.626637736345819 36.2940159534995 Trimmed Mean ( 21 / 38 ) 22.7104109589041 0.622278288084818 36.4955862895358 Trimmed Mean ( 22 / 38 ) 22.6760563380282 0.617610195248246 36.7158063653946 Trimmed Mean ( 23 / 38 ) 22.6457971014493 0.61314123508385 36.9340631581439 Trimmed Mean ( 24 / 38 ) 22.6155223880597 0.60796039572259 37.1990059667950 Trimmed Mean ( 25 / 38 ) 22.5847692307692 0.602023794719348 37.5147451460748 Trimmed Mean ( 26 / 38 ) 22.5533333333333 0.595156246292753 37.8948107724967 Trimmed Mean ( 27 / 38 ) 22.5313114754098 0.589951117517923 38.1918277741466 Trimmed Mean ( 28 / 38 ) 22.5291525423729 0.588590739254694 38.276430531171 Trimmed Mean ( 29 / 38 ) 22.5308771929825 0.587513039406396 38.3495781059548 Trimmed Mean ( 30 / 38 ) 22.5329090909091 0.585586452296284 38.4792185723387 Trimmed Mean ( 31 / 38 ) 22.5360377358491 0.58301076198798 38.6545827370399 Trimmed Mean ( 32 / 38 ) 22.5409803921569 0.579500951962673 38.8972275469338 Trimmed Mean ( 33 / 38 ) 22.5487755102041 0.57555811664311 39.1772348580848 Trimmed Mean ( 34 / 38 ) 22.5617021276596 0.571193900270875 39.4992000386563 Trimmed Mean ( 35 / 38 ) 22.5717777777778 0.565912893401511 39.8856043765083 Trimmed Mean ( 36 / 38 ) 22.5797674418605 0.559624784158572 40.3480476223197 Trimmed Mean ( 37 / 38 ) 22.5885365853659 0.550936183389471 41.0002778296328 Trimmed Mean ( 38 / 38 ) 22.6020512820513 0.540249252652442 41.8363397470386 Median 22.15 Midrange 29.42 Midmean - Weighted Average at Xnp 22.4184482758621 Midmean - Weighted Average at X(n+1)p 22.5291525423729 Midmean - Empirical Distribution Function 22.5291525423729 Midmean - Empirical Distribution Function - Averaging 22.5291525423729 Midmean - Empirical Distribution Function - Interpolation 22.5308771929825 Midmean - Closest Observation 22.4184482758621 Midmean - True Basic - Statistics Graphics Toolkit 22.5291525423729 Midmean - MS Excel (old versions) 22.5291525423729 Number of observations 115

Charts produced by software:

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Oct/20/t1224523615h88kuod4bogd5xe/1owwi1224523543.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Oct/20/t1224523615h88kuod4bogd5xe/1owwi1224523543.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Oct/20/t1224523615h88kuod4bogd5xe/2q8qv1224523543.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Oct/20/t1224523615h88kuod4bogd5xe/2q8qv1224523543.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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Software written by Ed van Stee & Patrick Wessa

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