opgave 5 oef 2 centrummaten werkloosheid umran celik

*Unverified author*

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

Title produced by software: Central Tendency

Date of computation: Sun, 07 Jun 2009 02:03:18 -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/07/t1244361871h6axobmohgubgyr.htm/, Retrieved Sun, 07 Jun 2009 10:04:34 +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/07/t1244361871h6axobmohgubgyr.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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580 579 572 560 551 537 541 588 607 599 578 563 566 561 554 540 526 512 505 554 584 569 540 522 526 527 516 503 489 479 475 524 552 532 511 492 492 493 481 462 457 442 439 488 521 501 485 464 460 467 460 448 443 436 431 484 510 513 503 471 471 476 475 470 461 455 456 517 525 523 519 509 512 519 517 510 509 501 507 569 580 578 565 547 555 562 561 555 544 537 543 594 611 613 611 594 595 591 589 584 573 567 569 621 629 628 612 595 597 593 590 580 574 573 573 620 626 620 588 566 557 561 549 532 526 511 499 555 565 542 527 510 514 517 508 493 490 469 478 528 534 518 506 502 516

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 532.937931034483 4.01156399175292 132.850412490019 Geometric Mean 530.745836821732 Harmonic Mean 528.538222631524 Quadratic Mean 535.107633388223 Winsorized Mean ( 1 / 48 ) 532.965517241379 4.00448041450374 133.092302140134 Winsorized Mean ( 2 / 48 ) 532.979310344828 3.99311511125289 133.47456697225 Winsorized Mean ( 3 / 48 ) 532.937931034483 3.96675867624448 134.350983896767 Winsorized Mean ( 4 / 48 ) 532.937931034483 3.95815299879178 134.643085094781 Winsorized Mean ( 5 / 48 ) 533.110344827586 3.93158831885338 135.596685510314 Winsorized Mean ( 6 / 48 ) 533.110344827586 3.84624409073269 138.605437473947 Winsorized Mean ( 7 / 48 ) 533.110344827586 3.83253511481139 139.101229044792 Winsorized Mean ( 8 / 48 ) 533.110344827586 3.81700818179661 139.667068928487 Winsorized Mean ( 9 / 48 ) 533.296551724138 3.79161613125261 140.651514621539 Winsorized Mean ( 10 / 48 ) 533.020689655172 3.75310176912609 142.021379233552 Winsorized Mean ( 11 / 48 ) 532.489655172414 3.66299603680503 145.369978515419 Winsorized Mean ( 12 / 48 ) 532.406896551724 3.63115637291638 146.621858679173 Winsorized Mean ( 13 / 48 ) 532.406896551724 3.58525738977433 148.498932899553 Winsorized Mean ( 14 / 48 ) 532.696551724138 3.54743882758167 150.163703340667 Winsorized Mean ( 15 / 48 ) 532.8 3.508495436777 151.859966644119 Winsorized Mean ( 16 / 48 ) 532.910344827586 3.49463076450270 152.494034631845 Winsorized Mean ( 17 / 48 ) 532.910344827586 3.46585585734417 153.760100466482 Winsorized Mean ( 18 / 48 ) 532.662068965517 3.43627288357993 155.011574171195 Winsorized Mean ( 19 / 48 ) 533.055172413793 3.35668229445313 158.804177951145 Winsorized Mean ( 20 / 48 ) 532.91724137931 3.34051673464339 159.531379038639 Winsorized Mean ( 21 / 48 ) 532.91724137931 3.30632019076463 161.181377069251 Winsorized Mean ( 22 / 48 ) 533.220689655172 3.27038945982268 163.045012285504 Winsorized Mean ( 23 / 48 ) 532.744827586207 3.17934213463051 167.56448504971 Winsorized Mean ( 24 / 48 ) 533.075862068966 3.14085186785474 169.723337647588 Winsorized Mean ( 25 / 48 ) 532.903448275862 3.00545997617406 177.311776733173 Winsorized Mean ( 26 / 48 ) 533.08275862069 2.98530088987552 178.569188931210 Winsorized Mean ( 27 / 48 ) 533.641379310345 2.92377091873759 182.518191110799 Winsorized Mean ( 28 / 48 ) 533.641379310345 2.8817312648083 185.180827173988 Winsorized Mean ( 29 / 48 ) 533.641379310345 2.838512437942 188.000366733376 Winsorized Mean ( 30 / 48 ) 534.055172413793 2.79479845451761 191.088975146142 Winsorized Mean ( 31 / 48 ) 533.2 2.70326182991452 197.243194906081 Winsorized Mean ( 32 / 48 ) 533.2 2.65694348058137 200.681724657286 Winsorized Mean ( 33 / 48 ) 533.2 2.65694348058137 200.681724657286 Winsorized Mean ( 34 / 48 ) 534.606896551724 2.51370375467299 212.676969415305 Winsorized Mean ( 35 / 48 ) 534.848275862069 2.44115282409411 219.096596732139 Winsorized Mean ( 36 / 48 ) 534.103448275862 2.36359125373749 225.971156151174 Winsorized Mean ( 37 / 48 ) 534.358620689655 2.33892343227333 228.463494493397 Winsorized Mean ( 38 / 48 ) 534.620689655172 2.31389830801589 231.047616830489 Winsorized Mean ( 39 / 48 ) 534.08275862069 2.25892235708802 236.432543573200 Winsorized Mean ( 40 / 48 ) 534.358620689655 2.17887093028695 245.245651434379 Winsorized Mean ( 41 / 48 ) 534.641379310345 2.15257744157106 248.372657347991 Winsorized Mean ( 42 / 48 ) 534.641379310345 2.09671965701701 254.989443877764 Winsorized Mean ( 43 / 48 ) 534.937931034483 2.06974235096841 258.456290844215 Winsorized Mean ( 44 / 48 ) 534.634482758621 1.98161602927056 269.797213416477 Winsorized Mean ( 45 / 48 ) 534.324137931034 1.95090318897208 273.885521819545 Winsorized Mean ( 46 / 48 ) 534.324137931034 1.89127059904052 282.521252221712 Winsorized Mean ( 47 / 48 ) 534.324137931034 1.89127059904052 282.521252221712 Winsorized Mean ( 48 / 48 ) 534.324137931034 1.89127059904052 282.521252221712 Trimmed Mean ( 1 / 48 ) 532.979020979021 3.94732215115792 135.022934680585 Trimmed Mean ( 2 / 48 ) 532.992907801418 3.88513516152178 137.187738815411 Trimmed Mean ( 3 / 48 ) 533 3.82385054211169 139.388293064837 Trimmed Mean ( 4 / 48 ) 533.021897810219 3.76740938311619 141.482340676588 Trimmed Mean ( 5 / 48 ) 533.044444444444 3.70842893709721 143.738616402257 Trimmed Mean ( 6 / 48 ) 533.03007518797 3.65076513997695 146.005030384216 Trimmed Mean ( 7 / 48 ) 533.015267175572 3.60647920780299 147.793800120167 Trimmed Mean ( 8 / 48 ) 533 3.56057424490606 149.694954616530 Trimmed Mean ( 9 / 48 ) 532.984251968504 3.51291623283828 151.721309772843 Trimmed Mean ( 10 / 48 ) 532.944 3.46466595699331 153.822621463483 Trimmed Mean ( 11 / 48 ) 532.934959349593 3.41745914886671 155.944792939610 Trimmed Mean ( 12 / 48 ) 532.98347107438 3.3783051048848 157.766529229027 Trimmed Mean ( 13 / 48 ) 533.042016806723 3.33927342974428 159.628143074089 Trimmed Mean ( 14 / 48 ) 533.102564102564 3.30193846323629 161.451392882731 Trimmed Mean ( 15 / 48 ) 533.139130434783 3.26518951073911 163.279689794820 Trimmed Mean ( 16 / 48 ) 533.16814159292 3.22896045626756 165.120678563287 Trimmed Mean ( 17 / 48 ) 533.189189189189 3.19016490023096 167.135306751882 Trimmed Mean ( 18 / 48 ) 533.211009174312 3.1501412627499 169.265745469728 Trimmed Mean ( 19 / 48 ) 533.252336448598 3.10868469828184 171.53632105029 Trimmed Mean ( 20 / 48 ) 533.266666666667 3.07111279860148 173.639557267159 Trimmed Mean ( 21 / 48 ) 533.291262135922 3.03060821522516 175.968394547595 Trimmed Mean ( 22 / 48 ) 533.316831683168 2.98872238981476 178.443081063887 Trimmed Mean ( 23 / 48 ) 533.323232323232 2.94538440225056 181.070841522662 Trimmed Mean ( 24 / 48 ) 533.360824742268 2.90618584129049 183.526055754724 Trimmed Mean ( 25 / 48 ) 533.378947368421 2.86583844614637 186.116195100127 Trimmed Mean ( 26 / 48 ) 533.408602150538 2.83425733190457 188.200484178371 Trimmed Mean ( 27 / 48 ) 533.428571428571 2.80014576880037 190.500286582259 Trimmed Mean ( 28 / 48 ) 533.415730337079 2.76745131291362 192.746202199846 Trimmed Mean ( 29 / 48 ) 533.402298850575 2.73416608848889 195.087745801636 Trimmed Mean ( 30 / 48 ) 533.388235294118 2.70024867189991 197.533005328292 Trimmed Mean ( 31 / 48 ) 533.349397590361 2.66552713196747 200.091528311208 Trimmed Mean ( 32 / 48 ) 533.358024691358 2.63507377095736 202.407245888065 Trimmed Mean ( 33 / 48 ) 533.367088607595 2.60434169334458 204.799197421221 Trimmed Mean ( 34 / 48 ) 533.376623376623 2.56807779640065 207.694885304561 Trimmed Mean ( 35 / 48 ) 533.306666666667 2.54126118461059 209.859053408707 Trimmed Mean ( 36 / 48 ) 533.219178082192 2.51708368247660 211.840067850882 Trimmed Mean ( 37 / 48 ) 533.169014084507 2.49675732683249 213.544587755716 Trimmed Mean ( 38 / 48 ) 533.101449275362 2.47434792770166 215.451288522121 Trimmed Mean ( 39 / 48 ) 533.014925373134 2.44944289231834 217.606594154416 Trimmed Mean ( 40 / 48 ) 532.953846153846 2.42556801131504 219.723315803832 Trimmed Mean ( 41 / 48 ) 532.873015873016 2.40545676634028 221.526748403690 Trimmed Mean ( 42 / 48 ) 532.770491803279 2.38281569249158 223.588628143619 Trimmed Mean ( 43 / 48 ) 532.661016949153 2.36111720199352 225.597025213073 Trimmed Mean ( 44 / 48 ) 532.526315789474 2.33625469597921 227.940179940986 Trimmed Mean ( 45 / 48 ) 532.4 2.31662124801056 229.817455251784 Trimmed Mean ( 46 / 48 ) 532.283018867925 2.29490781005893 231.940915680728 Trimmed Mean ( 47 / 48 ) 532.156862745098 2.27456051329544 233.960301181038 Trimmed Mean ( 48 / 48 ) 532.020408163265 2.24640487456620 236.831932741422 Median 527 Midrange 530 Midmean - Weighted Average at Xnp 532.783783783784 Midmean - Weighted Average at X(n+1)p 532.783783783784 Midmean - Empirical Distribution Function 532.783783783784 Midmean - Empirical Distribution Function - Averaging 532.783783783784 Midmean - Empirical Distribution Function - Interpolation 532.783783783784 Midmean - Closest Observation 532.783783783784 Midmean - True Basic - Statistics Graphics Toolkit 532.783783783784 Midmean - MS Excel (old versions) 532.783783783784 Number of observations 145

Charts produced by software:

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/07/t1244361871h6axobmohgubgyr/1oqtz1244361796.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/07/t1244361871h6axobmohgubgyr/1oqtz1244361796.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/07/t1244361871h6axobmohgubgyr/2mstm1244361796.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/07/t1244361871h6axobmohgubgyr/2mstm1244361796.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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