Meassure of central tendency oefening 4

*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: Sun, 03 Oct 2010 14:50:57 +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/03/t1286117625k5xhf2sr0kyezby.htm/, Retrieved Sun, 03 Oct 2010 16:53:46 +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/03/t1286117625k5xhf2sr0kyezby.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:

I estimate the time needed to fill in the survey at 291 seconds

IsPrivate?

No (this computation is public)

User-defined keywords:

Dataseries X:

» Textbox « » Textfile « » CSV «

33,999 37,028 39,047 57,47 59,609 62,156 64,016 70,939 72,844 85,094 86,58 103,898 109,215 131,812 136,452 136,813 137,55 140,321 150,034 156,187 158,047 169,861 171,26 171,328 180,818 183,186 183,613 184,641 187,881 190,157 190,379 191,835 192,797 193,299 197,549 198,296 199,297 199,746 200,156 203,077 204,386 206,771 206,893 207,533 208,108 211,655 213,361 213,511 213,923 216,046 216,548 216,886 217,465 218,761 220,553 221,588 223,166 226,731 229,641 232,444 232,669 235,577 236,302 236,71 238,502 239,89 240,755 241,171 242,205 242,344 246,542 249,148 250,407 251,422 252,64 257,102 257,567 259,7 260,642 261,596 262,517 262,875 263,906 265,777 266,793 274,482 275,562 278,741 287,069 289,714 293,671 295,281 308,16 308,174 308,532 313,906 315,955 324,04 330,563 348,821 350,089 356,725 366,936 380,155 380,531 383,703 386,688 388,3 392,25 401,422 401,915 403,064 403,556 406,167 421,403 426,113 435,9 etc...

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 'RServer@AstonUniversity' @ vre.aston.ac.uk Central Tendency - Ungrouped Data Measure Value S.E. Value/S.E. Arithmetic Mean 291.516340740741 16.2442545367473 17.9458121689291 Geometric Mean 243.987544788437 Harmonic Mean 195.595110261358 Quadratic Mean 346.902197816319 Winsorized Mean ( 1 / 45 ) 289.501896296296 15.3980662211651 18.801185300682 Winsorized Mean ( 2 / 45 ) 288.292533333333 14.9678561695342 19.2607765646578 Winsorized Mean ( 3 / 45 ) 284.4612 13.6670653929612 20.8136269068049 Winsorized Mean ( 4 / 45 ) 282.84117037037 13.2442416543593 21.3557844799121 Winsorized Mean ( 5 / 45 ) 282.758651851852 13.1910383292855 21.435662970071 Winsorized Mean ( 6 / 45 ) 281.419674074074 12.8574499008936 21.8876741689279 Winsorized Mean ( 7 / 45 ) 281.29942962963 12.7071754595206 22.1370540231953 Winsorized Mean ( 8 / 45 ) 280.917148148148 12.5856042241901 22.3205134329755 Winsorized Mean ( 9 / 45 ) 279.466881481481 12.0069612091189 23.2754047101639 Winsorized Mean ( 10 / 45 ) 278.8274 11.840203478211 23.5492067778323 Winsorized Mean ( 11 / 45 ) 276.5812 10.9506219737776 25.2571224412916 Winsorized Mean ( 12 / 45 ) 272.642711111111 10.0905958083824 27.0194858944427 Winsorized Mean ( 13 / 45 ) 271.851059259259 9.3376700363984 29.1133717725706 Winsorized Mean ( 14 / 45 ) 269.611059259259 8.85515188329079 30.4468023601042 Winsorized Mean ( 15 / 45 ) 268.744837037037 8.7148712754918 30.8374993205933 Winsorized Mean ( 16 / 45 ) 268.698614814815 8.68529171781508 30.9372009075603 Winsorized Mean ( 17 / 45 ) 268.826555555556 8.61366284399459 31.2093194758581 Winsorized Mean ( 18 / 45 ) 269.775088888889 8.4218334737802 32.0328215618111 Winsorized Mean ( 19 / 45 ) 269.255755555556 8.12915285195067 33.1222404670303 Winsorized Mean ( 20 / 45 ) 268.833533333333 8.000719764614 33.6011685501528 Winsorized Mean ( 21 / 45 ) 268.301222222222 7.48366171860284 35.8515967598162 Winsorized Mean ( 22 / 45 ) 268.103711111111 7.40304402674318 36.2153338738224 Winsorized Mean ( 23 / 45 ) 268.031474074074 7.39047553519016 36.267148547861 Winsorized Mean ( 24 / 45 ) 269.514318518519 7.20258323131723 37.4191189275891 Winsorized Mean ( 25 / 45 ) 269.861540740741 7.1500668063443 37.74252018195 Winsorized Mean ( 26 / 45 ) 268.177318518519 6.90278725222585 38.8505843682265 Winsorized Mean ( 27 / 45 ) 267.592918518519 6.77852066190354 39.4765955383801 Winsorized Mean ( 28 / 45 ) 267.930577777778 6.67333641391263 40.149418695451 Winsorized Mean ( 29 / 45 ) 267.778274074074 6.54485472048572 40.914319035366 Winsorized Mean ( 30 / 45 ) 267.122718518518 6.44762879903059 41.4296056495499 Winsorized Mean ( 31 / 45 ) 267.370718518519 6.40673272391238 41.7327723881143 Winsorized Mean ( 32 / 45 ) 264.465355555556 5.98015933578885 44.2237975120223 Winsorized Mean ( 33 / 45 ) 262.092044444444 5.65351417668982 46.359138095927 Winsorized Mean ( 34 / 45 ) 261.491125925926 5.34945273950606 48.8818461736837 Winsorized Mean ( 35 / 45 ) 261.356051851852 5.29161210870995 49.3906292605352 Winsorized Mean ( 36 / 45 ) 256.754185185185 4.67988351533473 54.8633709244835 Winsorized Mean ( 37 / 45 ) 255.089459259259 4.46016470935531 57.192833870956 Winsorized Mean ( 38 / 45 ) 252.929088888889 4.19029150715337 60.3607382582109 Winsorized Mean ( 39 / 45 ) 253.181 4.04524799653309 62.5872629359151 Winsorized Mean ( 40 / 45 ) 251.976555555556 3.83244589855596 65.7482355199061 Winsorized Mean ( 41 / 45 ) 252.592162962963 3.75389401657741 67.2880379274166 Winsorized Mean ( 42 / 45 ) 252.625762962963 3.74995678203521 67.367646521477 Winsorized Mean ( 43 / 45 ) 248.727414814815 3.28704675748477 75.6689615833575 Winsorized Mean ( 44 / 45 ) 248.390081481481 3.2142035889169 77.2788887231571 Winsorized Mean ( 45 / 45 ) 248.253414814815 2.96630029180446 83.6912619739511 Trimmed Mean ( 1 / 45 ) 285.825443609023 14.4660212854976 19.7584005973755 Trimmed Mean ( 2 / 45 ) 282.036732824427 13.3933832668437 21.057915479999 Trimmed Mean ( 3 / 45 ) 278.763348837209 12.4317309434155 22.4235345911229 Trimmed Mean ( 4 / 45 ) 276.74442519685 11.9214322592045 23.2140248906064 Trimmed Mean ( 5 / 45 ) 275.098304 11.4944070311032 23.9332314625366 Trimmed Mean ( 6 / 45 ) 273.416764227642 11.0310198912132 24.7861727133167 Trimmed Mean ( 7 / 45 ) 271.928619834711 10.5958192081226 25.663765537473 Trimmed Mean ( 8 / 45 ) 270.409941176471 10.1400423294762 26.6675357350742 Trimmed Mean ( 9 / 45 ) 268.894478632479 9.65043517179917 27.8634562945152 Trimmed Mean ( 10 / 45 ) 267.515469565217 9.21289317985675 29.0370749277891 Trimmed Mean ( 11 / 45 ) 266.164044247788 8.74775885482701 30.4265410906839 Trimmed Mean ( 12 / 45 ) 265.01227027027 8.38193353647111 31.6170808462224 Trimmed Mean ( 13 / 45 ) 264.224724770642 8.11437886011007 32.5625324286446 Trimmed Mean ( 14 / 45 ) 263.484570093458 7.92719061620299 33.2380767475052 Trimmed Mean ( 15 / 45 ) 262.921933333333 7.78563548407523 33.7701314004637 Trimmed Mean ( 16 / 45 ) 262.41313592233 7.64559967963727 34.3221129692707 Trimmed Mean ( 17 / 45 ) 261.888049504951 7.4916741163256 34.9572132261136 Trimmed Mean ( 18 / 45 ) 261.331484848485 7.32694880885141 35.6671640086771 Trimmed Mean ( 19 / 45 ) 260.678628865979 7.16402174123407 36.3871912009406 Trimmed Mean ( 20 / 45 ) 260.037126315789 7.01618335439862 37.0624758762563 Trimmed Mean ( 21 / 45 ) 259.398677419355 6.86404354380073 37.7909428697653 Trimmed Mean ( 22 / 45 ) 258.769769230769 6.75330890085722 38.3174785915572 Trimmed Mean ( 23 / 45 ) 258.126213483146 6.63572200156017 38.899491784384 Trimmed Mean ( 24 / 45 ) 257.457942528736 6.5017546986396 39.5982245504595 Trimmed Mean ( 25 / 45 ) 256.660094117647 6.36747650780791 40.3079766062625 Trimmed Mean ( 26 / 45 ) 255.801204819277 6.2171722093852 41.1443010108566 Trimmed Mean ( 27 / 45 ) 255.007864197531 6.07557209285507 41.9726505257706 Trimmed Mean ( 28 / 45 ) 254.211341772152 5.92642714776032 42.8945358533973 Trimmed Mean ( 29 / 45 ) 253.352298701299 5.76390235822058 43.9549948898706 Trimmed Mean ( 30 / 45 ) 252.456893333333 5.58913681770749 45.1692097666137 Trimmed Mean ( 31 / 45 ) 251.552835616438 5.39633686693445 46.6154804304017 Trimmed Mean ( 32 / 45 ) 250.582633802817 5.17083457757718 48.4607716691313 Trimmed Mean ( 33 / 45 ) 249.733826086957 4.97132714723551 50.2348404541894 Trimmed Mean ( 34 / 45 ) 248.979253731343 4.78597514530912 52.0226800541109 Trimmed Mean ( 35 / 45 ) 248.214953846154 4.60930695349673 53.850818865047 Trimmed Mean ( 36 / 45 ) 247.410396825397 4.40313325021162 56.1896228812757 Trimmed Mean ( 37 / 45 ) 246.835983606557 4.2618691728126 57.9173066083723 Trimmed Mean ( 38 / 45 ) 246.325576271186 4.12704506981705 59.6857005688348 Trimmed Mean ( 39 / 45 ) 246.325576271186 4.00874969226542 61.4469835186899 Trimmed Mean ( 40 / 45 ) 245.456636363636 3.88497281456921 63.1810434922835 Trimmed Mean ( 41 / 45 ) 245.041452830189 3.76908863121974 65.0134493523145 Trimmed Mean ( 42 / 45 ) 244.553960784314 3.63476406882863 67.2819352655056 Trimmed Mean ( 43 / 45 ) 244.024469387755 3.46333665167593 70.4593557977304 Trimmed Mean ( 44 / 45 ) 243.710319148936 3.34896386410717 72.7718569199638 Trimmed Mean ( 45 / 45 ) 243.391244444444 3.21611019902589 75.6787639049694 Median 241.171 Midrange 669.961 Midmean - Weighted Average at Xnp 248.160426470588 Midmean - Weighted Average at X(n+1)p 249.733826086957 Midmean - Empirical Distribution Function 249.733826086957 Midmean - Empirical Distribution Function - Averaging 249.733826086957 Midmean - Empirical Distribution Function - Interpolation 248.979253731343 Midmean - Closest Observation 248.160426470588 Midmean - True Basic - Statistics Graphics Toolkit 249.733826086957 Midmean - MS Excel (old versions) 249.733826086957 Number of observations 135

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Oct/03/t1286117625k5xhf2sr0kyezby/1h02j1286117453.png (open in new window) http://www.freestatistics.org/blog/date/2010/Oct/03/t1286117625k5xhf2sr0kyezby/1h02j1286117453.ps (open in new window) http://www.freestatistics.org/blog/date/2010/Oct/03/t1286117625k5xhf2sr0kyezby/2h02j1286117453.png (open in new window) http://www.freestatistics.org/blog/date/2010/Oct/03/t1286117625k5xhf2sr0kyezby/2h02j1286117453.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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