Central tendency - Omzetcijfer van de totale industrie

*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: Sat, 13 Dec 2008 14:20:56 -0700

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2008/Dec/13/t122920367173qx1izvh47ha34.htm/, Retrieved Sat, 13 Dec 2008 22:27:53 +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/2008/Dec/13/t122920367173qx1izvh47ha34.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}, }

Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords:

Dataseries X:

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82.2 83.4 93.1 88.7 84.5 95 76.6 73.4 93 91 85.3 89.5 76.1 76.1 91.5 85.4 80 94 72.6 80.8 94.1 94.9 91.9 99.2 84.7 93.7 106.7 93.5 104.8 103.5 83.1 89.6 105.7 110.7 110.4 109 106 100.9 114.3 101.2 109.2 111.6 91.7 93.7 105.7 109.5 105.3 102.8 100.6 97.6 110.3 107.2 107.2 108.1 97.1 92.2 112.2 111.6 115.7 111.3 104.2 103.2 112.7 106.4 102.6 110.6 95.2 89 112.5 116.8 107.2 113.6 101.8 102.6 122.7 110.3 110.5 121.6 100.3 100.7 123.4 127.1 124.1 131.2 111.6 114.2 130.1 125.9 119 133.8 107.5 113.5 134.4 126.8 135.6 139.9 129.8 131 153.1 134.1 144.1 155.9 123.3 128.1 144.3 153 149.9 150.9 141 138.9 157.4 142.9 151.7 161 138.5 135.9 151.5 164 159.1 157 142.1 144.8 152.1 154.9 148.4 157.3 146.4 133.9 157.9

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 1 seconds R Server 'George Udny Yule' @ 72.249.76.132 Central Tendency - Ungrouped Data Measure Value S.E. Value/S.E. Arithmetic Mean 114.476744186047 2.06148098847124 55.5313121131136 Geometric Mean 112.145769260341 Harmonic Mean 109.875700747593 Quadratic Mean 116.828451390334 Winsorized Mean ( 1 / 43 ) 114.459689922481 2.05626657275780 55.6638382585635 Winsorized Mean ( 2 / 43 ) 114.472093023256 2.04481642125591 55.9815990488516 Winsorized Mean ( 3 / 43 ) 114.444186046512 2.04011516758648 56.096924264282 Winsorized Mean ( 4 / 43 ) 114.444186046512 2.03528256750127 56.2301214946364 Winsorized Mean ( 5 / 43 ) 114.572093023256 2.01624007779059 56.8246283194633 Winsorized Mean ( 6 / 43 ) 114.595348837209 2.0089971020844 57.0410722436149 Winsorized Mean ( 7 / 43 ) 114.611627906977 1.98940861622975 57.6109035479016 Winsorized Mean ( 8 / 43 ) 114.605426356589 1.97239681930074 58.1046497515744 Winsorized Mean ( 9 / 43 ) 114.500775193798 1.95005357215097 58.7167331344136 Winsorized Mean ( 10 / 43 ) 114.578294573643 1.93837250960656 59.110565180735 Winsorized Mean ( 11 / 43 ) 114.518604651163 1.92451002001897 59.5053304269281 Winsorized Mean ( 12 / 43 ) 114.537209302326 1.91213487349288 59.9001727807525 Winsorized Mean ( 13 / 43 ) 114.527131782946 1.90787610207139 60.0286002107805 Winsorized Mean ( 14 / 43 ) 114.820155038760 1.85694582456108 61.8327974462578 Winsorized Mean ( 15 / 43 ) 114.738759689922 1.83559177866539 62.5077759791155 Winsorized Mean ( 16 / 43 ) 114.614728682171 1.80126230931164 63.6302264748831 Winsorized Mean ( 17 / 43 ) 114.364341085271 1.76178266177952 64.9139894303171 Winsorized Mean ( 18 / 43 ) 114.336434108527 1.70922738634087 66.8936356989337 Winsorized Mean ( 19 / 43 ) 114.336434108527 1.69119103152686 67.6070485102447 Winsorized Mean ( 20 / 43 ) 114.336434108527 1.68363969096504 67.9102748183557 Winsorized Mean ( 21 / 43 ) 114.173643410853 1.65346730160167 69.0510440093106 Winsorized Mean ( 22 / 43 ) 114.088372093023 1.62967040078582 70.0070223021849 Winsorized Mean ( 23 / 43 ) 114.034883720930 1.58863402209460 71.7817207329955 Winsorized Mean ( 24 / 43 ) 113.848837209302 1.55978217749450 72.9902154621225 Winsorized Mean ( 25 / 43 ) 113.732558139535 1.52661512307469 74.4998241013562 Winsorized Mean ( 26 / 43 ) 113.692248062016 1.5120877667146 75.1889212813627 Winsorized Mean ( 27 / 43 ) 113.148062015504 1.44367988301462 78.3747583842711 Winsorized Mean ( 28 / 43 ) 113.148062015504 1.42883896596769 79.1888132326188 Winsorized Mean ( 29 / 43 ) 112.900775193798 1.39365928812983 81.0103130337556 Winsorized Mean ( 30 / 43 ) 113.017054263566 1.36580262735800 82.7477206440767 Winsorized Mean ( 31 / 43 ) 112.993023255814 1.35752379901124 83.2346536672969 Winsorized Mean ( 32 / 43 ) 113.017829457364 1.34941150035927 83.7534209744578 Winsorized Mean ( 33 / 43 ) 112.838759689922 1.22069292559662 92.4382842923183 Winsorized Mean ( 34 / 43 ) 112.917829457364 1.20129454640580 93.9967885438315 Winsorized Mean ( 35 / 43 ) 113.107751937984 1.13007930258872 100.088331570080 Winsorized Mean ( 36 / 43 ) 113.331007751938 1.09114032435083 103.864741521091 Winsorized Mean ( 37 / 43 ) 112.929457364341 1.02616414033188 110.050091331215 Winsorized Mean ( 38 / 43 ) 112.664341085271 0.989589584914736 113.849562285944 Winsorized Mean ( 39 / 43 ) 112.634108527132 0.97356377529612 115.692583665485 Winsorized Mean ( 40 / 43 ) 112.448062015504 0.933226111280731 120.493908878293 Winsorized Mean ( 41 / 43 ) 112.066666666667 0.851441104325112 131.619986511569 Winsorized Mean ( 42 / 43 ) 112.099224806202 0.801987369264822 139.776795872686 Winsorized Mean ( 43 / 43 ) 112.065891472868 0.798320287327075 140.377105845682 Trimmed Mean ( 1 / 43 ) 114.416535433071 2.03033542105342 56.3535139300811 Trimmed Mean ( 2 / 43 ) 114.372 2.00180260700683 57.1345044709544 Trimmed Mean ( 3 / 43 ) 114.319512195122 1.97691146483756 57.8273302717253 Trimmed Mean ( 4 / 43 ) 114.275206611570 1.95129937671398 58.5636463452428 Trimmed Mean ( 5 / 43 ) 114.229411764706 1.92448386876763 59.3558686661554 Trimmed Mean ( 6 / 43 ) 114.153846153846 1.89969305013614 60.0906794630141 Trimmed Mean ( 7 / 43 ) 114.071304347826 1.8737830590217 60.877540651575 Trimmed Mean ( 8 / 43 ) 113.983185840708 1.84890155257063 61.6491373930813 Trimmed Mean ( 9 / 43 ) 113.892792792793 1.82428055073317 62.4316214668955 Trimmed Mean ( 10 / 43 ) 113.812844036697 1.80061062099012 63.2079155315179 Trimmed Mean ( 11 / 43 ) 113.720560747664 1.77591834788146 64.0347912860542 Trimmed Mean ( 12 / 43 ) 113.631428571429 1.75033660513986 64.919757855575 Trimmed Mean ( 13 / 43 ) 113.536893203883 1.72336160852984 65.8810621299261 Trimmed Mean ( 14 / 43 ) 113.439603960396 1.69357322128607 66.9824029658736 Trimmed Mean ( 15 / 43 ) 113.311111111111 1.66672101883477 67.9844496053265 Trimmed Mean ( 16 / 43 ) 113.184536082474 1.63917708130612 69.0496087172515 Trimmed Mean ( 17 / 43 ) 113.063157894737 1.61244950275998 70.1188829177039 Trimmed Mean ( 18 / 43 ) 112.956989247312 1.58722650557908 71.1662694960484 Trimmed Mean ( 19 / 43 ) 112.848351648352 1.56494985243249 72.1098835677992 Trimmed Mean ( 20 / 43 ) 112.734831460674 1.54154925613815 73.1308655962732 Trimmed Mean ( 21 / 43 ) 112.616091954023 1.51550383282815 74.3093415632378 Trimmed Mean ( 22 / 43 ) 112.503529411765 1.48931530435802 75.540437328857 Trimmed Mean ( 23 / 43 ) 112.391566265060 1.46201408143515 76.8744758974784 Trimmed Mean ( 24 / 43 ) 112.277777777778 1.43545278269890 78.2176739848425 Trimmed Mean ( 25 / 43 ) 112.170886075949 1.40826391137190 79.651892781002 Trimmed Mean ( 26 / 43 ) 112.066233766234 1.38074792553436 81.1634272221438 Trimmed Mean ( 27 / 43 ) 111.958666666667 1.35032207480501 82.9125649025873 Trimmed Mean ( 28 / 43 ) 111.880821917808 1.32393183378557 84.5064821788466 Trimmed Mean ( 29 / 43 ) 111.798591549296 1.29461738629309 86.356473142549 Trimmed Mean ( 30 / 43 ) 111.727536231884 1.26476595636239 88.3385069544605 Trimmed Mean ( 31 / 43 ) 111.644776119403 1.23287231518696 90.556641384613 Trimmed Mean ( 32 / 43 ) 111.558461538462 1.19579570448464 93.2922414088626 Trimmed Mean ( 33 / 43 ) 111.465079365079 1.15222165404135 96.7392679820957 Trimmed Mean ( 34 / 43 ) 111.377049180328 1.11978821534585 99.4626016366216 Trimmed Mean ( 35 / 43 ) 111.277966101695 1.08303982601640 102.745959500855 Trimmed Mean ( 36 / 43 ) 111.159649122807 1.04907424175738 105.959754513270 Trimmed Mean ( 37 / 43 ) 111.018181818182 1.01279388521716 109.615770235794 Trimmed Mean ( 38 / 43 ) 110.892452830189 0.97971386279397 113.188612554632 Trimmed Mean ( 39 / 43 ) 110.774509803922 0.945170772565362 117.200523989183 Trimmed Mean ( 40 / 43 ) 110.648979591837 0.904199962312023 122.372245303914 Trimmed Mean ( 41 / 43 ) 110.525531914894 0.860358701978099 128.464478432982 Trimmed Mean ( 42 / 43 ) 110.417777777778 0.822482623247648 134.249374584697 Trimmed Mean ( 43 / 43 ) 110.297674418605 0.783675416261076 140.744078645259 Median 110.3 Midrange 118.3 Midmean - Weighted Average at Xnp 111.2109375 Midmean - Weighted Average at X(n+1)p 111.558461538462 Midmean - Empirical Distribution Function 111.558461538462 Midmean - Empirical Distribution Function - Averaging 111.558461538462 Midmean - Empirical Distribution Function - Interpolation 111.558461538462 Midmean - Closest Observation 111.307575757576 Midmean - True Basic - Statistics Graphics Toolkit 111.558461538462 Midmean - MS Excel (old versions) 111.558461538462 Number of observations 129

Charts produced by software:

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/13/t122920367173qx1izvh47ha34/1p3qi1229203254.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/13/t122920367173qx1izvh47ha34/1p3qi1229203254.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/13/t122920367173qx1izvh47ha34/28w0o1229203254.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/13/t122920367173qx1izvh47ha34/28w0o1229203254.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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