Opgave 5

*Unverified author*

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

Title produced by software: Central Tendency

Date of computation: Wed, 20 Oct 2010 21:38:36 +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/Oct/20/t12876106502wt17oncas4uu9v.htm/, Retrieved Wed, 20 Oct 2010 23:37:30 +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/2010/Oct/20/t12876106502wt17oncas4uu9v.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?

No (this computation is public)

User-defined keywords:

KDGP1W52

Dataseries X:

» Textbox « » Textfile « » CSV «

96,1 96,5 96,9 97,8 98,9 100,2 101,2 101 101,6 102,4 103,7 103,7 104,6 104,5 104,5 105,6 106,1 107,6 107,7 108,3 108,1 108,1 108 108,2 108,9 109,8 109,9 109,8 110,9 111,1 112,2 112,7 114,6 114,2 114,7 114,7 116 116,3 116,4 116,6 118,1 117,2 108,3 109,5 110,5 110,6 111,2 111,1 111 112,4 112,5 112,4 111,8 111,6 112,9 112,8 113,7 113,8 114 113,8 113,9 114,4 114,4 114,5 113,8 114,3 115 115,4 115,3 114,9 114,3 114,5 115,5 115,8 115,8 116 114,9 114,1 114,1 113,5 115 114,7 115,4 116,1 116,6 117,2 118,2 118 117,7 118,5 117,5 118 117,7 116,3 115 115,7 113,6 114,8 114,9 117,3 117,3 117,7 120 119,6 119,2 117,3 117,5 119 112,5 118,9 118,4 119,4 120,6 118,6 122 122,6 120,6 117,4 116,4 122,2 121 122,4 124,9 126,1 124,5 123,2 126,4 123,9 116 126,6 125,9 126,6 116,7 126,4 129 128,7 128,4 129,2 133,3 128,9 132,7 127,7 131,8 133,9

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 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 115.092361111111 0.627897386577005 183.298041322547 Geometric Mean 114.845486773045 Harmonic Mean 114.596136321190 Quadratic Mean 115.337028180218 Winsorized Mean ( 1 / 48 ) 115.090972222222 0.62645550271875 183.717712946474 Winsorized Mean ( 2 / 48 ) 115.088194444444 0.62364265704229 184.541889726187 Winsorized Mean ( 3 / 48 ) 115.088194444444 0.616261361583436 186.752247696877 Winsorized Mean ( 4 / 48 ) 115.046527777778 0.597532735701965 192.535941386750 Winsorized Mean ( 5 / 48 ) 115.084722222222 0.58812163911684 195.681836150495 Winsorized Mean ( 6 / 48 ) 115.113888888889 0.581653100535015 197.90814969095 Winsorized Mean ( 7 / 48 ) 115.113888888889 0.578406274253214 199.019087470158 Winsorized Mean ( 8 / 48 ) 115.119444444444 0.571978461745744 201.265348511702 Winsorized Mean ( 9 / 48 ) 115.125694444444 0.556841627069764 206.747643940098 Winsorized Mean ( 10 / 48 ) 115.139583333333 0.531015705453819 216.828960331658 Winsorized Mean ( 11 / 48 ) 115.139583333333 0.531015705453819 216.828960331658 Winsorized Mean ( 12 / 48 ) 115.189583333333 0.518670187455093 222.086378047912 Winsorized Mean ( 13 / 48 ) 115.189583333333 0.518670187455093 222.086378047912 Winsorized Mean ( 14 / 48 ) 115.170138888889 0.512891387744696 224.550736551298 Winsorized Mean ( 15 / 48 ) 115.253472222222 0.495159076330643 232.760496033525 Winsorized Mean ( 16 / 48 ) 115.197916666667 0.471260758349494 244.446231997179 Winsorized Mean ( 17 / 48 ) 115.327777777778 0.441608326670344 261.153992831908 Winsorized Mean ( 18 / 48 ) 115.265277777778 0.429350442065941 268.464327701973 Winsorized Mean ( 19 / 48 ) 115.2125 0.411722266047119 279.830627345315 Winsorized Mean ( 20 / 48 ) 115.143055555556 0.398911510414039 288.64310141376 Winsorized Mean ( 21 / 48 ) 115.113888888889 0.395124486288849 291.335750841665 Winsorized Mean ( 22 / 48 ) 115.098611111111 0.389310582084723 295.64727086217 Winsorized Mean ( 23 / 48 ) 115.082638888889 0.383279272894590 300.25792425394 Winsorized Mean ( 24 / 48 ) 114.915972222222 0.362973645224376 316.595911946129 Winsorized Mean ( 25 / 48 ) 114.950694444444 0.341796689864869 336.313071053704 Winsorized Mean ( 26 / 48 ) 115.059027777778 0.328678768853172 350.065287694859 Winsorized Mean ( 27 / 48 ) 115.002777777778 0.309040398326229 372.128622667573 Winsorized Mean ( 28 / 48 ) 114.925 0.300408456722245 382.562465963662 Winsorized Mean ( 29 / 48 ) 114.904861111111 0.293659244045468 391.28637507941 Winsorized Mean ( 30 / 48 ) 114.988194444444 0.274591765450535 418.760534409246 Winsorized Mean ( 31 / 48 ) 114.966666666667 0.267553885385882 429.695373329582 Winsorized Mean ( 32 / 48 ) 115.011111111111 0.257685123878523 446.324216858282 Winsorized Mean ( 33 / 48 ) 114.965277777778 0.247972194511050 463.621649211379 Winsorized Mean ( 34 / 48 ) 114.965277777778 0.242926983420813 473.250341147273 Winsorized Mean ( 35 / 48 ) 114.940972222222 0.240467875484239 477.988887250579 Winsorized Mean ( 36 / 48 ) 114.915972222222 0.232692808813567 493.852701371156 Winsorized Mean ( 37 / 48 ) 114.993055555556 0.218833642634262 525.481613207637 Winsorized Mean ( 38 / 48 ) 115.019444444444 0.210533320678571 546.32418314462 Winsorized Mean ( 39 / 48 ) 115.127777777778 0.199166494631901 578.047919106858 Winsorized Mean ( 40 / 48 ) 115.1 0.185180879255818 621.554452395676 Winsorized Mean ( 41 / 48 ) 115.1 0.185180879255818 621.554452395676 Winsorized Mean ( 42 / 48 ) 115.129166666667 0.182222410253944 631.805750490421 Winsorized Mean ( 43 / 48 ) 115.069444444444 0.176397951115946 652.328690421179 Winsorized Mean ( 44 / 48 ) 115.130555555556 0.170233618950992 676.30915834962 Winsorized Mean ( 45 / 48 ) 115.130555555556 0.164089272095881 701.63365395565 Winsorized Mean ( 46 / 48 ) 115.130555555556 0.157844226078961 729.393519266024 Winsorized Mean ( 47 / 48 ) 115.326388888889 0.139136482884172 828.872388451097 Winsorized Mean ( 48 / 48 ) 115.359722222222 0.136099366396226 847.613954986207 Trimmed Mean ( 1 / 48 ) 115.093661971831 0.608108903656373 189.264885417411 Trimmed Mean ( 2 / 48 ) 115.096428571429 0.587942753254172 195.761284469258 Trimmed Mean ( 3 / 48 ) 115.100724637681 0.567363647861256 202.869403197697 Trimmed Mean ( 4 / 48 ) 115.105147058824 0.547706964744637 210.158267957191 Trimmed Mean ( 5 / 48 ) 115.120895522388 0.532122741346606 216.342746846451 Trimmed Mean ( 6 / 48 ) 115.128787878788 0.517511450314264 222.466165355133 Trimmed Mean ( 7 / 48 ) 115.131538461538 0.502933593925766 228.919960511789 Trimmed Mean ( 8 / 48 ) 115.134375 0.487519479597692 236.163640261124 Trimmed Mean ( 9 / 48 ) 115.136507936508 0.47170693508011 244.084831860601 Trimmed Mean ( 10 / 48 ) 115.137903225806 0.456933060290665 251.979804552914 Trimmed Mean ( 11 / 48 ) 115.137704918033 0.444922471654972 258.781500717994 Trimmed Mean ( 12 / 48 ) 115.1375 0.431597031847022 266.770833680826 Trimmed Mean ( 13 / 48 ) 115.132203389831 0.418673362254893 274.992903225920 Trimmed Mean ( 14 / 48 ) 115.126724137931 0.404250945854575 284.790240612935 Trimmed Mean ( 15 / 48 ) 115.122807017544 0.388946473092901 295.986247418797 Trimmed Mean ( 16 / 48 ) 115.111607142857 0.374322093253404 307.520205773509 Trimmed Mean ( 17 / 48 ) 115.104545454545 0.361272393157539 318.608749615563 Trimmed Mean ( 18 / 48 ) 115.087037037037 0.350577066167469 328.278852621981 Trimmed Mean ( 19 / 48 ) 115.073584905660 0.340184670229958 338.267990817672 Trimmed Mean ( 20 / 48 ) 115.063461538462 0.330763531829954 347.872272683361 Trimmed Mean ( 21 / 48 ) 115.057843137255 0.321773249692461 357.574295710483 Trimmed Mean ( 22 / 48 ) 115.054 0.312100799567879 368.643720744384 Trimmed Mean ( 23 / 48 ) 115.051020408163 0.301878001846893 381.117602820609 Trimmed Mean ( 24 / 48 ) 115.048958333333 0.29102433578107 395.324184915868 Trimmed Mean ( 25 / 48 ) 115.057446808511 0.281238596908374 409.109731286263 Trimmed Mean ( 26 / 48 ) 115.064130434783 0.272749364382388 421.867639161445 Trimmed Mean ( 27 / 48 ) 115.064444444444 0.264694538627648 434.706530180089 Trimmed Mean ( 28 / 48 ) 115.068181818182 0.257877688917326 446.212242328074 Trimmed Mean ( 29 / 48 ) 115.076744186047 0.251080697938267 458.325730058072 Trimmed Mean ( 30 / 48 ) 115.086904761905 0.244073645114632 471.525324693917 Trimmed Mean ( 31 / 48 ) 115.092682926829 0.238362251091848 482.84777643957 Trimmed Mean ( 32 / 48 ) 115.1 0.232596788074953 494.84776188272 Trimmed Mean ( 33 / 48 ) 115.105128205128 0.227130072974955 506.780659634712 Trimmed Mean ( 34 / 48 ) 115.113157894737 0.221939948455031 518.668039242431 Trimmed Mean ( 35 / 48 ) 115.121621621622 0.216492095378186 531.759006815089 Trimmed Mean ( 36 / 48 ) 115.131944444444 0.210380332138208 547.256215798773 Trimmed Mean ( 37 / 48 ) 115.144285714286 0.204186369160822 563.917592479424 Trimmed Mean ( 38 / 48 ) 115.152941176471 0.198805371889608 579.22449520334 Trimmed Mean ( 39 / 48 ) 115.160606060606 0.193554396417119 594.977991677489 Trimmed Mean ( 40 / 48 ) 115.1625 0.188910041999503 609.615554478057 Trimmed Mean ( 41 / 48 ) 115.166129032258 0.185271301182101 621.608032638919 Trimmed Mean ( 42 / 48 ) 115.17 0.180822040054556 636.924569401229 Trimmed Mean ( 43 / 48 ) 115.172413793103 0.175835970686046 654.999163958001 Trimmed Mean ( 44 / 48 ) 115.178571428571 0.170612233801741 675.089756824905 Trimmed Mean ( 45 / 48 ) 115.181481481481 0.165215359827135 697.159644248549 Trimmed Mean ( 46 / 48 ) 115.184615384615 0.159571083641191 721.838899356087 Trimmed Mean ( 47 / 48 ) 115.188 0.153639918282313 749.727032452218 Trimmed Mean ( 48 / 48 ) 115.179166666667 0.149643735705621 769.689196300518 Median 114.95 Midrange 115 Midmean - Weighted Average at Xnp 115.022972972973 Midmean - Weighted Average at X(n+1)p 115.131944444444 Midmean - Empirical Distribution Function 115.022972972973 Midmean - Empirical Distribution Function - Averaging 115.131944444444 Midmean - Empirical Distribution Function - Interpolation 115.131944444444 Midmean - Closest Observation 115.022972972973 Midmean - True Basic - Statistics Graphics Toolkit 115.131944444444 Midmean - MS Excel (old versions) 115.068 Number of observations 144

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Oct/20/t12876106502wt17oncas4uu9v/1vubl1287610712.png (open in new window) http://www.freestatistics.org/blog/date/2010/Oct/20/t12876106502wt17oncas4uu9v/1vubl1287610712.ps (open in new window) http://www.freestatistics.org/blog/date/2010/Oct/20/t12876106502wt17oncas4uu9v/2vubl1287610712.png (open in new window) http://www.freestatistics.org/blog/date/2010/Oct/20/t12876106502wt17oncas4uu9v/2vubl1287610712.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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