central tendency werkaanbod

*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, 18 Dec 2010 08:41:16 +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/Dec/18/t1292661607bqekx4lsfdmeebz.htm/, Retrieved Sat, 18 Dec 2010 09:40:09 +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/2010/Dec/18/t1292661607bqekx4lsfdmeebz.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:

Dataseries X:

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10406 11398 14117 10785 10334 12371 7918 9907 12855 11579 9788 8786 12231 13604 15107 10853 13698 11536 8879 11005 13656 12631 10931 8064 12332 12452 14029 10003 12388 10492 9114 9304 9660 10569 8356 5998 10408 11420 11538 10860 10412 9521 7602 8197 10449 11561 8603 8080 10792 11943 11179 9939 10065 11021 9226 9554 11468 9937 8928 8395 11996 12385 15277 12657 11482 16797 11047 11794 13077 11725 10921 9334 11431 13085 16394 15701 14936 18282 12824 14784 16061 14814 14375 13644 16397 19254 21943 16731 22065 20937 18242 19017 20372 20561 18267 16170 23163 22469 26500 23660 23339 26174 24617 23891 23516 25638 21258 17436 26210 25227 21928 25452 22578 23904 20842 21042 24890 23126 16951 16972 19985 19296 21078 19493 18821 19657 15678 16406 18264 18288 15179 15443 19306 19094 25673 20077 21698 25943 19778 21333 25222 24512 20126

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 6 seconds R Server 'Gwilym Jenkins' @ 72.249.127.135 Central Tendency - Ungrouped Data Measure Value S.E. Value/S.E. Arithmetic Mean 15413.6083916084 455.32302579473 33.8520292592390 Geometric Mean 14483.3518089056 Harmonic Mean 13612.4665329346 Quadratic Mean 16340.7046928870 Winsorized Mean ( 1 / 47 ) 15422.7972027972 453.481137298016 34.0097876941279 Winsorized Mean ( 2 / 47 ) 15426.7132867133 452.870481773033 34.0642941141056 Winsorized Mean ( 3 / 47 ) 15424.9300699301 451.713620104421 34.1475868413362 Winsorized Mean ( 4 / 47 ) 15417.8251748252 450.437583224182 34.2285496349264 Winsorized Mean ( 5 / 47 ) 15420.6923076923 449.775583669674 34.2853033103229 Winsorized Mean ( 6 / 47 ) 15419.5594405594 447.787823812099 34.4349681268461 Winsorized Mean ( 7 / 47 ) 15410.4545454545 445.853227128140 34.5639632233177 Winsorized Mean ( 8 / 47 ) 15421.8111888112 444.536603753096 34.6918815202376 Winsorized Mean ( 9 / 47 ) 15412.4335664336 440.097223457153 35.0205198873155 Winsorized Mean ( 10 / 47 ) 15399.8461538462 436.543303213312 35.2767893597058 Winsorized Mean ( 11 / 47 ) 15395.5384615385 434.951126219112 35.3960193076561 Winsorized Mean ( 12 / 47 ) 15360.1258741259 425.95728977471 36.0602488626263 Winsorized Mean ( 13 / 47 ) 15369.1258741259 424.746082266084 36.1842675325674 Winsorized Mean ( 14 / 47 ) 15354.1468531469 420.800992540841 36.4879055071541 Winsorized Mean ( 15 / 47 ) 15342.1888111888 418.393676089602 36.6692655457421 Winsorized Mean ( 16 / 47 ) 15343.3076923077 413.587956494612 37.0980524248113 Winsorized Mean ( 17 / 47 ) 15326.3076923077 410.367929315503 37.3477228541521 Winsorized Mean ( 18 / 47 ) 15334.993006993 408.428282109308 37.5463543508695 Winsorized Mean ( 19 / 47 ) 15279.1888111888 397.16361596458 38.4707666992121 Winsorized Mean ( 20 / 47 ) 15280.5874125874 393.586333281722 38.8239786813173 Winsorized Mean ( 21 / 47 ) 15225.6643356643 385.640380404501 39.4815094822125 Winsorized Mean ( 22 / 47 ) 15207.2027972028 383.277051611592 39.6767892396896 Winsorized Mean ( 23 / 47 ) 15215.0839160839 381.985704767025 39.8315531869541 Winsorized Mean ( 24 / 47 ) 15186.8881118881 376.245912161567 40.3642607693411 Winsorized Mean ( 25 / 47 ) 15170.1048951049 364.098466034814 41.6648415477103 Winsorized Mean ( 26 / 47 ) 15169.5594405594 361.256418631149 41.9911139517992 Winsorized Mean ( 27 / 47 ) 15135.9510489510 357.213667553849 42.3722618246944 Winsorized Mean ( 28 / 47 ) 15129.6853146853 356.315940266295 42.4614326919476 Winsorized Mean ( 29 / 47 ) 15115.8951048951 353.136886858578 42.8046337480135 Winsorized Mean ( 30 / 47 ) 15104.986013986 349.991308862841 43.1581745931455 Winsorized Mean ( 31 / 47 ) 15060.7622377622 341.471829637719 44.1054310504641 Winsorized Mean ( 32 / 47 ) 15066.8041958042 332.262299723969 45.3461142245783 Winsorized Mean ( 33 / 47 ) 15011.6503496504 325.78514896719 46.0783752643132 Winsorized Mean ( 34 / 47 ) 15014.5034965035 323.179483286955 46.4587149648109 Winsorized Mean ( 35 / 47 ) 14993.6993006993 320.547382534034 46.7752978738092 Winsorized Mean ( 36 / 47 ) 14956.9440559441 313.474283386294 47.7134643849321 Winsorized Mean ( 37 / 47 ) 14928.2237762238 309.861641253221 48.1770628847355 Winsorized Mean ( 38 / 47 ) 14904.3076923077 303.415793140555 49.1217267830333 Winsorized Mean ( 39 / 47 ) 14857.6713286713 297.620106085201 49.921598120854 Winsorized Mean ( 40 / 47 ) 14862.1468531469 296.666247492140 50.0971950088141 Winsorized Mean ( 41 / 47 ) 14887.9510489510 291.991899395150 50.9875482155185 Winsorized Mean ( 42 / 47 ) 14905.2797202797 281.352891512166 52.9771691350653 Winsorized Mean ( 43 / 47 ) 14888.7412587413 278.349293221775 53.4894164321756 Winsorized Mean ( 44 / 47 ) 14831.8181818182 271.785020147967 54.5718751303635 Winsorized Mean ( 45 / 47 ) 14675.7342657343 253.666244059907 57.8545021633559 Winsorized Mean ( 46 / 47 ) 14678.3076923077 253.071889178478 58.0005457735999 Winsorized Mean ( 47 / 47 ) 14691.1258741259 251.002518205078 58.5297947573686 Trimmed Mean ( 1 / 47 ) 15401.7588652482 450.050049552716 34.2223245626910 Trimmed Mean ( 2 / 47 ) 15380.1151079137 446.287049028135 34.4623827677869 Trimmed Mean ( 3 / 47 ) 15355.7956204380 442.499127329883 34.7024314219500 Trimmed Mean ( 4 / 47 ) 15331.3851851852 438.784947154193 34.940544985919 Trimmed Mean ( 5 / 47 ) 15308.1503759398 435.083177610368 35.1844225741332 Trimmed Mean ( 6 / 47 ) 15283.5801526718 431.166283263382 35.4470670503139 Trimmed Mean ( 7 / 47 ) 15258.4573643411 427.274023983095 35.7111748149351 Trimmed Mean ( 8 / 47 ) 15234.0078740157 423.347413105342 35.9846485473269 Trimmed Mean ( 9 / 47 ) 15207.152 419.224056970386 36.2745213380592 Trimmed Mean ( 10 / 47 ) 15180.6341463415 415.371008785074 36.5471682550585 Trimmed Mean ( 11 / 47 ) 15154.7272727273 411.624688472132 36.8168569503899 Trimmed Mean ( 12 / 47 ) 15128.4201680672 407.676436279898 37.1088903398884 Trimmed Mean ( 13 / 47 ) 15104.8205128205 404.488909450509 37.3429781630852 Trimmed Mean ( 14 / 47 ) 15079.5391304348 401.057077735036 37.5994838829333 Trimmed Mean ( 15 / 47 ) 15054.7168141593 397.69111751169 37.8553006372257 Trimmed Mean ( 16 / 47 ) 15030.0270270270 394.190294504631 38.1288612037363 Trimmed Mean ( 17 / 47 ) 15004.3394495413 390.792187762679 38.3946760436602 Trimmed Mean ( 18 / 47 ) 14979.0280373832 387.317011465378 38.6738191041788 Trimmed Mean ( 19 / 47 ) 14952.0952380952 383.582819718396 38.9800962646664 Trimmed Mean ( 20 / 47 ) 14928.1941747573 380.597580630177 39.2230401203282 Trimmed Mean ( 21 / 47 ) 14903.2475247525 377.551068057389 39.473461435122 Trimmed Mean ( 22 / 47 ) 14881.0707070707 374.911460516559 39.6922267635332 Trimmed Mean ( 23 / 47 ) 14859.2164948454 372.104851134349 39.9328749666863 Trimmed Mean ( 24 / 47 ) 14835.9263157895 368.975498551417 40.2084321968118 Trimmed Mean ( 25 / 47 ) 14813.4408602151 365.957192544082 40.4786165213317 Trimmed Mean ( 26 / 47 ) 14791.0219780220 363.681432528274 40.6702697885795 Trimmed Mean ( 27 / 47 ) 14767.6292134831 361.259985912298 40.8781204378063 Trimmed Mean ( 28 / 47 ) 14745.2068965517 358.811236788274 41.0946073722115 Trimmed Mean ( 29 / 47 ) 14722.1058823529 355.981739540307 41.3563513155596 Trimmed Mean ( 30 / 47 ) 14698.7108433735 352.954958350482 41.6447212190111 Trimmed Mean ( 31 / 47 ) 14698.7108433735 349.688954123127 42.0336721250795 Trimmed Mean ( 32 / 47 ) 14652.2658227848 346.739031209341 42.2573304530536 Trimmed Mean ( 33 / 47 ) 14628.2077922078 344.15562631701 42.5046306775569 Trimmed Mean ( 34 / 47 ) 14606.0533333333 341.73641699459 42.7406989918916 Trimmed Mean ( 35 / 47 ) 14582.5205479452 339.019110144580 43.0138600202398 Trimmed Mean ( 36 / 47 ) 14558.8591549296 335.974867494336 43.3331792449475 Trimmed Mean ( 37 / 47 ) 14535.9420289855 333.066654545327 43.642741867476 Trimmed Mean ( 38 / 47 ) 14513.3134328358 329.893266464604 43.9939668619851 Trimmed Mean ( 39 / 47 ) 14490.6769230769 326.735564912512 44.3498611084992 Trimmed Mean ( 40 / 47 ) 14469.3174603175 323.531287547620 44.7230855785092 Trimmed Mean ( 41 / 47 ) 14446.2950819672 319.583621136165 45.2034901870396 Trimmed Mean ( 42 / 47 ) 14420.1864406780 315.20027260386 45.7492828973567 Trimmed Mean ( 43 / 47 ) 14391.2105263158 311.110996012881 46.2574795193673 Trimmed Mean ( 44 / 47 ) 14361.1272727273 306.318450803611 46.8829978574636 Trimmed Mean ( 45 / 47 ) 14332.2641509434 301.277990468268 47.5715605002117 Trimmed Mean ( 46 / 47 ) 14310.8627450980 297.889683515207 48.0408135529388 Trimmed Mean ( 47 / 47 ) 14310.8627450980 293.410879023960 48.774138139334 Median 14029 Midrange 16249 Midmean - Weighted Average at Xnp 14507.4861111111 Midmean - Weighted Average at X(n+1)p 14582.5205479452 Midmean - Empirical Distribution Function 14582.5205479452 Midmean - Empirical Distribution Function - Averaging 14582.5205479452 Midmean - Empirical Distribution Function - Interpolation 14558.8591549296 Midmean - Closest Observation 14507.4861111111 Midmean - True Basic - Statistics Graphics Toolkit 14582.5205479452 Midmean - MS Excel (old versions) 14582.5205479452 Number of observations 143

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Dec/18/t1292661607bqekx4lsfdmeebz/1bq4h1292661670.png (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/18/t1292661607bqekx4lsfdmeebz/1bq4h1292661670.ps (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/18/t1292661607bqekx4lsfdmeebz/23h321292661670.png (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/18/t1292661607bqekx4lsfdmeebz/23h321292661670.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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