Centrummaten Opdracht 5 Oefening 2

*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 14:30:05 -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/t1243888263hobjoog1w4m62d9.htm/, Retrieved Mon, 01 Jun 2009 22:31:05 +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/t1243888263hobjoog1w4m62d9.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:

Thomas Cammaert

Dataseries X:

» Textbox « » Textfile « » CSV «

8.9722 8.8284 8.7446 8.7519 8.6337 8.7272 8.6330 8.5865 8.5968 8.5114 8.3884 8.2671 8.2410 8.3177 8.4070 8.3917 8.4145 8.5245 8.6289 8.6622 8.9055 8.9770 9.1264 9.1120 9.0576 9.2106 9.2637 9.3107 9.6744 9.5780 9.4166 9.4359 9.2275 9.1828 9.0594 9.1358 9.2208 9.1137 9.2689 9.2489 9.1679 9.1051 9.0818 9.0961 9.1733 9.1455 9.2265 9.1541 9.1559 9.1182 9.1856 9.2378 9.0682 9.0105 8.9939 9.0228 9.1368 9.1763 9.2346 9.1653 9.1277 9.1430 9.1962 9.1861 9.0920 9.0620 8.9981 8.9819 9.0476 9.0852 9.0884 9.1670 9.1931 9.2628 9.4276 9.3398 9.3342 9.4223 9.5614 9.4316 9.3111 9.3414 9.4017 9.3346 9.3310 9.2349 9.2170 9.2098 9.2665 9.2533 9.1008 9.0377 9.0795 9.1896 9.2992 9.2372 9.2061 9.3290 9.1842 9.3231 9.2835 9.1735 9.2889 9.4319 9.4314 9.3642 9.4020 9.3699 9.3106 9.3739 9.4566 9.3984 9.5637 9.8506

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 'Gwilym Jenkins' @ 72.249.127.135 Central Tendency - Ungrouped Data Measure Value S.E. Value/S.E. Arithmetic Mean 9.1153149122807 0.0286582964269475 318.068972994135 Geometric Mean 9.11010029515385 Harmonic Mean 9.10475708711343 Quadratic Mean 9.12040419163864 Winsorized Mean ( 1 / 38 ) 9.11399824561404 0.0282858308788818 322.21073104197 Winsorized Mean ( 2 / 38 ) 9.1131947368421 0.0277820415334893 328.024660313635 Winsorized Mean ( 3 / 38 ) 9.11467894736842 0.0272716488223342 334.218110784117 Winsorized Mean ( 4 / 38 ) 9.11471403508772 0.0272326654669024 334.697829933886 Winsorized Mean ( 5 / 38 ) 9.11078859649123 0.0264746789813925 344.13216503568 Winsorized Mean ( 6 / 38 ) 9.11009385964912 0.0262591875903752 346.929768040053 Winsorized Mean ( 7 / 38 ) 9.11579824561404 0.0248937499359894 366.188230742815 Winsorized Mean ( 8 / 38 ) 9.11669649122807 0.0246950697383782 369.170712527284 Winsorized Mean ( 9 / 38 ) 9.1215754385965 0.0236839603441507 385.137253485112 Winsorized Mean ( 10 / 38 ) 9.12214561403509 0.0234656394932489 388.74481203291 Winsorized Mean ( 11 / 38 ) 9.12473157894737 0.0228016737454749 400.178148358878 Winsorized Mean ( 12 / 38 ) 9.12456315789474 0.0226498242492909 402.853596454744 Winsorized Mean ( 13 / 38 ) 9.12297807017544 0.0224478914534887 406.406904144113 Winsorized Mean ( 14 / 38 ) 9.12644122807018 0.0217759806091017 419.105866775782 Winsorized Mean ( 15 / 38 ) 9.1345596491228 0.0201532365827190 453.255218417648 Winsorized Mean ( 16 / 38 ) 9.13356315789474 0.0193287618035130 472.537416040519 Winsorized Mean ( 17 / 38 ) 9.1340552631579 0.0190698394521424 478.979138030013 Winsorized Mean ( 18 / 38 ) 9.14523421052632 0.0168913904951523 541.413935883544 Winsorized Mean ( 19 / 38 ) 9.15428421052632 0.0143994064905413 635.740383920655 Winsorized Mean ( 20 / 38 ) 9.1657052631579 0.0126745488497784 723.158305024649 Winsorized Mean ( 21 / 38 ) 9.16563157894737 0.0124396900816466 736.805460488943 Winsorized Mean ( 22 / 38 ) 9.1665 0.0123041701093744 744.991325584499 Winsorized Mean ( 23 / 38 ) 9.1682754385965 0.0119085523184943 769.890007902802 Winsorized Mean ( 24 / 38 ) 9.16873859649123 0.0117435275859796 780.748248715116 Winsorized Mean ( 25 / 38 ) 9.17016403508772 0.0112416950405977 815.727877510558 Winsorized Mean ( 26 / 38 ) 9.17023245614035 0.0105657966493296 867.916803672554 Winsorized Mean ( 27 / 38 ) 9.17366666666667 0.0101268269883125 905.877692712052 Winsorized Mean ( 28 / 38 ) 9.17607368421053 0.00983886511012463 932.635378318983 Winsorized Mean ( 29 / 38 ) 9.17571754385965 0.00919948546970614 997.416385304944 Winsorized Mean ( 30 / 38 ) 9.17348070175438 0.00882760758122632 1039.18084456582 Winsorized Mean ( 31 / 38 ) 9.17271929824561 0.00857791860480946 1069.34091133747 Winsorized Mean ( 32 / 38 ) 9.17036140350877 0.00791899736980107 1158.02051386957 Winsorized Mean ( 33 / 38 ) 9.17293771929825 0.00747444857146837 1227.23939185472 Winsorized Mean ( 34 / 38 ) 9.17278859649123 0.00730647210598742 1255.43332862031 Winsorized Mean ( 35 / 38 ) 9.17355614035088 0.00716151337146955 1280.95217651859 Winsorized Mean ( 36 / 38 ) 9.17156666666667 0.00672414882384116 1363.97437161830 Winsorized Mean ( 37 / 38 ) 9.17130701754386 0.00644365312612656 1423.30861671584 Winsorized Mean ( 38 / 38 ) 9.16897368421053 0.00590642631722068 1552.37248240575 Trimmed Mean ( 1 / 38 ) 9.11655625 0.0273136557338106 333.772832858654 Trimmed Mean ( 2 / 38 ) 9.11920727272727 0.0262171249227389 347.833993986805 Trimmed Mean ( 3 / 38 ) 9.12238055555556 0.0252834161590712 360.804904612648 Trimmed Mean ( 4 / 38 ) 9.12514150943396 0.0244487982079852 373.234767280038 Trimmed Mean ( 5 / 38 ) 9.12799903846154 0.0235160406179806 388.160540575108 Trimmed Mean ( 6 / 38 ) 9.13184607843137 0.0226699086381430 402.817947976494 Trimmed Mean ( 7 / 38 ) 9.135979 0.0217555532580915 419.937792048661 Trimmed Mean ( 8 / 38 ) 9.13933265306122 0.0210370221469458 434.440416006696 Trimmed Mean ( 9 / 38 ) 9.14269270833333 0.0202571650874186 451.331302720721 Trimmed Mean ( 10 / 38 ) 9.14553829787234 0.0195726289483459 467.261619377157 Trimmed Mean ( 11 / 38 ) 9.14843695652174 0.0188270095697433 485.920874615377 Trimmed Mean ( 12 / 38 ) 9.15116666666667 0.0180922791348860 505.805078422715 Trimmed Mean ( 13 / 38 ) 9.15403863636364 0.0172655228592259 530.191799634504 Trimmed Mean ( 14 / 38 ) 9.15720581395349 0.0163291244304123 560.789762670837 Trimmed Mean ( 15 / 38 ) 9.1601880952381 0.0153538553210838 596.605080852844 Trimmed Mean ( 16 / 38 ) 9.16256341463415 0.0145125510800249 631.354429976513 Trimmed Mean ( 17 / 38 ) 9.16514625 0.0136584052741204 671.02608731093 Trimmed Mean ( 18 / 38 ) 9.16781923076923 0.0126806296567041 722.978233649644 Trimmed Mean ( 19 / 38 ) 9.16970131578947 0.0119334041691646 768.406163555876 Trimmed Mean ( 20 / 38 ) 9.17095135135135 0.0114831022520710 798.647538795305 Trimmed Mean ( 21 / 38 ) 9.17136666666667 0.0112265420534942 816.936027404106 Trimmed Mean ( 22 / 38 ) 9.17181142857143 0.0109568588505577 837.08401775246 Trimmed Mean ( 23 / 38 ) 9.17221617647059 0.0106567408935321 860.696179827125 Trimmed Mean ( 24 / 38 ) 9.17251212121212 0.0103594211291579 885.427091615664 Trimmed Mean ( 25 / 38 ) 9.1727921875 0.0100282273494996 914.697270795094 Trimmed Mean ( 26 / 38 ) 9.17298548387097 0.00970950290035735 944.743060278952 Trimmed Mean ( 27 / 38 ) 9.17318666666667 0.00943176849131823 972.583951261146 Trimmed Mean ( 28 / 38 ) 9.17315172413793 0.00916418772224061 1000.97815563900 Trimmed Mean ( 29 / 38 ) 9.17293928571429 0.00888212515468292 1032.74150340902 Trimmed Mean ( 30 / 38 ) 9.17273703703704 0.00864189100820753 1061.42706825686 Trimmed Mean ( 31 / 38 ) 9.17268269230769 0.00840619910646007 1091.18075555201 Trimmed Mean ( 32 / 38 ) 9.17268 0.00815338367220153 1125.01513099079 Trimmed Mean ( 33 / 38 ) 9.17285208333333 0.00795305652335516 1153.37443615497 Trimmed Mean ( 34 / 38 ) 9.17284565217391 0.00777739677180634 1179.42364538044 Trimmed Mean ( 35 / 38 ) 9.17285 0.00757855722405713 1210.36890384386 Trimmed Mean ( 36 / 38 ) 9.17279523809524 0.00734469393941353 1248.90094995949 Trimmed Mean ( 37 / 38 ) 9.1728925 0.00712923413326586 1286.65889330218 Trimmed Mean ( 38 / 38 ) 9.17302105263158 0.00690141733839725 1329.15031838400 Median 9.1749 Midrange 9.0458 Midmean - Weighted Average at Xnp 9.17074035087719 Midmean - Weighted Average at X(n+1)p 9.17315172413793 Midmean - Empirical Distribution Function 9.17315172413793 Midmean - Empirical Distribution Function - Averaging 9.17315172413793 Midmean - Empirical Distribution Function - Interpolation 9.17293928571428 Midmean - Closest Observation 9.17315172413793 Midmean - True Basic - Statistics Graphics Toolkit 9.17315172413793 Midmean - MS Excel (old versions) 9.17315172413793 Number of observations 114

Charts produced by software:

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/01/t1243888263hobjoog1w4m62d9/1w6541243888203.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/01/t1243888263hobjoog1w4m62d9/1w6541243888203.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/01/t1243888263hobjoog1w4m62d9/28el31243888203.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/01/t1243888263hobjoog1w4m62d9/28el31243888203.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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