Mean

*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: Fri, 10 Dec 2010 11:02:31 +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/10/t12919788674ikgewrjs7lfl36.htm/, Retrieved Fri, 10 Dec 2010 12:01:08 +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/10/t12919788674ikgewrjs7lfl36.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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237,588 164,083 278,261 220,36 253,967 422,31 136,921 143,495 189,785 219,529 217,761 221,754 159,854 209,464 174,283 154,55 153,024 162,49 154,462 249,671 259,473 155,337 151,289 276,614 188,214 181,098 240,898 244,551 250,238 183,129 310,331 281,942 230,343 161,563 392,527 1077,414 248,275 557,386 731,874 301,429 226,36 215,018 157,672 219,118 213,019 390,642 157,124 227,652 239,266 506,343 149,219 213,351 174,517 172,531 320,656 305,011 266,495 361,511 361,019 382,187 196,763 273,212 186,397 294,205 364,685 230,501 217,51 262,297 169,246 260,428 348,187 512,937 164,496 111,187 169,999 240,187 187,158 194,096 265,846 283,319 356,938 240,802 326,662 249,266 277,368 394,618 235,686 227,641 159,593 268,866 206,466 233,064 133,824 486,783 228,859 155,238 2042,451 205,218 373,648 229,151 199,156 234,41 56,519 289,239 199,227 274,513 174,499 217,714 239,717 241,529 155,561 204,107 745,97 241,772 110,2 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 2 seconds R Server 'RServer@AstonUniversity' @ vre.aston.ac.uk Central Tendency - Ungrouped Data Measure Value S.E. Value/S.E. Arithmetic Mean 288.859188679245 32.9164130905632 8.77553662619632 Geometric Mean 236.99692709392 Harmonic Mean 216.617635212221 Quadratic Mean 504.609839879001 Winsorized Mean ( 1 / 53 ) 270.750044025157 18.4862829207293 14.645996990642 Winsorized Mean ( 2 / 53 ) 259.037880503145 11.9090469318582 21.7513527308541 Winsorized Mean ( 3 / 53 ) 252.801578616352 9.48063256738427 26.6650539211964 Winsorized Mean ( 4 / 53 ) 253.01644654088 9.31454437322159 27.1635880836295 Winsorized Mean ( 5 / 53 ) 247.62679245283 7.6962228798986 32.1751067136575 Winsorized Mean ( 6 / 53 ) 246.025509433962 7.28046170347079 33.792569682315 Winsorized Mean ( 7 / 53 ) 245.935918238994 7.19514287632602 34.1808248239503 Winsorized Mean ( 8 / 53 ) 245.239767295598 6.94850906453338 35.2938688023524 Winsorized Mean ( 9 / 53 ) 244.455012578616 6.74316809576599 36.2522495519738 Winsorized Mean ( 10 / 53 ) 242.958974842767 6.40218494629867 37.9493839807347 Winsorized Mean ( 11 / 53 ) 241.466088050315 6.08394927791868 39.6890370086912 Winsorized Mean ( 12 / 53 ) 239.382767295597 5.70628531255164 41.9507182315345 Winsorized Mean ( 13 / 53 ) 239.268056603774 5.67166379078834 42.1865726583409 Winsorized Mean ( 14 / 53 ) 239.110798742138 5.64254714299747 42.3763936184176 Winsorized Mean ( 15 / 53 ) 238.334289308176 5.50680102536372 43.279989273343 Winsorized Mean ( 16 / 53 ) 237.632301886792 5.35166093806547 44.4034673789876 Winsorized Mean ( 17 / 53 ) 236.73258490566 5.19423444055021 45.5760300416059 Winsorized Mean ( 18 / 53 ) 236.590735849057 5.1176355639437 46.2304775111297 Winsorized Mean ( 19 / 53 ) 236.563132075472 5.10559092046075 46.3341336509043 Winsorized Mean ( 20 / 53 ) 236.264767295597 5.00646022269267 47.1919793199765 Winsorized Mean ( 21 / 53 ) 235.231408805031 4.82092962187709 48.7937861066392 Winsorized Mean ( 22 / 53 ) 232.473522012579 4.37490693014008 53.137935440637 Winsorized Mean ( 23 / 53 ) 231.664471698113 4.25221170385458 54.4809355301177 Winsorized Mean ( 24 / 53 ) 230.185679245283 4.04304485159714 56.9337436744862 Winsorized Mean ( 25 / 53 ) 229.919169811321 3.97606220153306 57.8258483286982 Winsorized Mean ( 26 / 53 ) 230.01679245283 3.8682339797034 59.462998789558 Winsorized Mean ( 27 / 53 ) 229.430603773585 3.79215828320371 60.5013257990265 Winsorized Mean ( 28 / 53 ) 229.058150943396 3.72364656390996 61.5144716374148 Winsorized Mean ( 29 / 53 ) 228.740974842767 3.58629341690997 63.7820022656863 Winsorized Mean ( 30 / 53 ) 228.966635220126 3.55534246187483 64.400725858455 Winsorized Mean ( 31 / 53 ) 228.064905660377 3.43802679936188 66.3359883357243 Winsorized Mean ( 32 / 53 ) 226.905056603774 3.30334263929249 68.6895309934824 Winsorized Mean ( 33 / 53 ) 226.631509433962 3.27137241629523 69.2771964161202 Winsorized Mean ( 34 / 53 ) 225.848226415094 3.18789836779928 70.8454914047356 Winsorized Mean ( 35 / 53 ) 225.702943396226 3.16227872389342 71.3735135650343 Winsorized Mean ( 36 / 53 ) 225.83358490566 3.11403866477158 72.5211242430818 Winsorized Mean ( 37 / 53 ) 225.434962264151 3.05480343388163 73.7968799444809 Winsorized Mean ( 38 / 53 ) 226.230333333333 2.91271671732721 77.6698715627 Winsorized Mean ( 39 / 53 ) 226.102295597484 2.81472442763039 80.3283949853065 Winsorized Mean ( 40 / 53 ) 225.651226415094 2.75512537395344 81.9023440996074 Winsorized Mean ( 41 / 53 ) 225.387433962264 2.6609914015336 84.7005495141274 Winsorized Mean ( 42 / 53 ) 225.723169811321 2.59522328481273 86.9763966485097 Winsorized Mean ( 43 / 53 ) 224.862088050314 2.50256896031124 89.8525042132502 Winsorized Mean ( 44 / 53 ) 224.971672955975 2.48232304806421 90.6294904409861 Winsorized Mean ( 45 / 53 ) 224.478937106918 2.42887165964454 92.4210779995558 Winsorized Mean ( 46 / 53 ) 224.336018867925 2.39015289867156 93.8584385093562 Winsorized Mean ( 47 / 53 ) 222.884044025157 2.23224004707473 99.8477042454457 Winsorized Mean ( 48 / 53 ) 223.319968553459 2.18246571630617 102.324617007698 Winsorized Mean ( 49 / 53 ) 223.376056603774 1.97664879084298 113.007458704139 Winsorized Mean ( 50 / 53 ) 223.509704402516 1.96376827602842 113.816740565006 Winsorized Mean ( 51 / 53 ) 223.501685534591 1.95291263433754 114.445306771446 Winsorized Mean ( 52 / 53 ) 224.191748427673 1.85469813645561 120.877755803492 Winsorized Mean ( 53 / 53 ) 224.440081761006 1.83091880256035 122.583307051711 Trimmed Mean ( 1 / 53 ) 260.703560509554 14.8385286507943 17.5693673304731 Trimmed Mean ( 2 / 53 ) 250.397812903226 9.52940085783155 26.2763437742722 Trimmed Mean ( 3 / 53 ) 245.908366013072 7.92591836430816 31.0258514799297 Trimmed Mean ( 4 / 53 ) 243.488894039735 7.25398797493483 33.566211424816 Trimmed Mean ( 5 / 53 ) 240.947147651007 6.53008540821893 36.8980086152847 Trimmed Mean ( 6 / 53 ) 239.502163265306 6.2153139814787 38.5342018084701 Trimmed Mean ( 7 / 53 ) 239.502163265306 5.96924408132506 40.1226956047241 Trimmed Mean ( 8 / 53 ) 237.09865034965 5.71385082542597 41.4954218431096 Trimmed Mean ( 9 / 53 ) 235.95109929078 5.47954358465005 43.0603563318219 Trimmed Mean ( 10 / 53 ) 234.87026618705 5.25739461077221 44.6742699712534 Trimmed Mean ( 11 / 53 ) 233.931503649635 5.07078859817878 46.1331603793646 Trimmed Mean ( 12 / 53 ) 233.12477037037 4.91606147235706 47.4210446067909 Trimmed Mean ( 13 / 53 ) 232.501323308271 4.80235488255911 48.4140237433628 Trimmed Mean ( 14 / 53 ) 232.501323308271 4.68162597164374 49.6625156978609 Trimmed Mean ( 15 / 53 ) 231.232031007752 4.55198990280191 50.798010528411 Trimmed Mean ( 16 / 53 ) 230.639244094488 4.42677520167094 52.1009614419613 Trimmed Mean ( 17 / 53 ) 230.083296 4.30817663316904 53.4061891122495 Trimmed Mean ( 18 / 53 ) 229.577682926829 4.19672767410999 54.7039743234033 Trimmed Mean ( 19 / 53 ) 229.065710743802 4.08212483429065 56.1143326190332 Trimmed Mean ( 20 / 53 ) 228.538470588235 3.95569520134809 57.7745399873959 Trimmed Mean ( 21 / 53 ) 228.013478632479 3.82645694166765 59.5886696514363 Trimmed Mean ( 22 / 53 ) 227.538260869565 3.70495748121597 61.4145403889729 Trimmed Mean ( 23 / 53 ) 227.222610619469 3.62266776981469 62.7224534672392 Trimmed Mean ( 24 / 53 ) 226.945972972973 3.54474039258918 64.0232987012076 Trimmed Mean ( 25 / 53 ) 226.749064220183 3.48080121513212 65.1427789769882 Trimmed Mean ( 26 / 53 ) 226.560635514019 3.41638825887651 66.3158336659674 Trimmed Mean ( 27 / 53 ) 226.359342857143 3.35528721247135 67.4634773487595 Trimmed Mean ( 28 / 53 ) 226.359342857143 3.2948151675525 68.70168168653 Trimmed Mean ( 29 / 53 ) 226.183747572816 3.23401541847539 69.9389824428991 Trimmed Mean ( 30 / 53 ) 225.871565656566 3.17971028676571 71.0352658846521 Trimmed Mean ( 31 / 53 ) 225.702453608247 3.1213245879288 72.3098310509307 Trimmed Mean ( 32 / 53 ) 225.574905263158 3.06775518524739 73.5309343939605 Trimmed Mean ( 33 / 53 ) 225.503838709677 3.02111336312452 74.6426272718397 Trimmed Mean ( 34 / 53 ) 225.444131868132 2.97126255573999 75.8748604806434 Trimmed Mean ( 35 / 53 ) 225.422898876405 2.92311617440387 77.1173246038968 Trimmed Mean ( 36 / 53 ) 225.408275862069 2.87062467333394 78.5223780579716 Trimmed Mean ( 37 / 53 ) 225.386176470588 2.81552490054619 80.0512104960836 Trimmed Mean ( 38 / 53 ) 225.38365060241 2.7586247902359 81.7014518973913 Trimmed Mean ( 39 / 53 ) 225.339913580247 2.70871958067417 83.190565456821 Trimmed Mean ( 40 / 53 ) 225.300569620253 2.66177313860091 84.6430397665958 Trimmed Mean ( 41 / 53 ) 225.282467532468 2.61383288770751 86.1885503820613 Trimmed Mean ( 42 / 53 ) 225.27704 2.56862633239517 87.70331330752 Trimmed Mean ( 43 / 53 ) 225.253904109589 2.52312296510067 89.2758328568427 Trimmed Mean ( 44 / 53 ) 225.274309859155 2.48046993540322 90.8192059270151 Trimmed Mean ( 45 / 53 ) 225.29015942029 2.4321799856896 92.6289011281427 Trimmed Mean ( 46 / 53 ) 225.332940298507 2.38135077607558 94.6240018742016 Trimmed Mean ( 47 / 53 ) 225.385953846154 2.32554727393017 96.9173821460324 Trimmed Mean ( 48 / 53 ) 225.520301587302 2.27921352009117 98.9465443230088 Trimmed Mean ( 49 / 53 ) 225.639786885246 2.23018581084231 101.175330677951 Trimmed Mean ( 50 / 53 ) 225.764288135593 2.1994795357008 102.644414040279 Trimmed Mean ( 51 / 53 ) 225.890070175439 2.1627882608604 104.443913564416 Trimmed Mean ( 52 / 53 ) 226.025454545455 2.11825287703239 106.703716537427 Trimmed Mean ( 53 / 53 ) 226.131245283019 2.0788089230117 108.779235445751 Median 227.906 Midrange 2499.076 Midmean - Weighted Average at Xnp 224.7697875 Midmean - Weighted Average at X(n+1)p 225.339913580247 Midmean - Empirical Distribution Function 225.339913580247 Midmean - Empirical Distribution Function - Averaging 225.339913580247 Midmean - Empirical Distribution Function - Interpolation 225.300569620253 Midmean - Closest Observation 224.7697875 Midmean - True Basic - Statistics Graphics Toolkit 225.339913580247 Midmean - MS Excel (old versions) 225.339913580247 Number of observations 159

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Dec/10/t12919788674ikgewrjs7lfl36/1p3tc1291978947.png (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/10/t12919788674ikgewrjs7lfl36/1p3tc1291978947.ps (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/10/t12919788674ikgewrjs7lfl36/2p3tc1291978947.png (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/10/t12919788674ikgewrjs7lfl36/2p3tc1291978947.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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