*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, 12 Dec 2010 13:19:44 +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/12/t129216012616lds4glwm9e1xc.htm/, Retrieved Sun, 12 Dec 2010 14:22:06 +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/12/t129216012616lds4glwm9e1xc.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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8,7 10,6 9,0 9,2 8,3 7,6 9,0 8,2 9,0 8,7 9,1 8,0 7,7 9,9 8,4 9,0 8,8 8,3 8,8 9,8 8,1 8,9 7,4 8,9 9,8 8,5 9,7 7,7 8,8 9,6 9,6 7,8 9,4 9,4 8,8 10,1 9,0 8,0 7,8 10,0 8,9 8,9 8,6 9,0 9,3 8,9 7,0 9,3 8,4 9,0 8,9 9,4 8,3 8,8 7,5 7,5 8,2 8,1 8,2 8,4 9,3 9,2 8,3 8,6 9,2 9,5 9,2 9,4 8,8 8,4 9,3 9,1 8,9 9,3 8,9 8,8 8,6 9,7 10,4 9,7 10,0 9,8 9,3 9,5 8,4 9,8 8,6 9,7 10,5 8,6 9,3 9,1 9,1 9,9 9,3 9,7 8,9 10,0 9,1 9,7 9,1 10,3 9,7 9,6 9,8 9,8 9,8 8,7 9,1 8,9 10,1 9,5 10,3 9,3 10,2 10,1 10,3 9,8 9,8 9,3 9,9 9,3 9,2 8,4 10,1 9,6 10,6 10,0 10,4 8,6 8,4 9,6 9,1 10,0 10,0 9,3 9,6 9,6 9,9 9,3 9,7 10,0 9,9 10,4 9,8 9,4 9,0 9,4 9,7 10,5 10,5 9,9 8,9 9,4 9,2 10,6 11,3 11,2 10,0 10,6 10,1 11,1 10,9 9,1 10,8 10,6 11,1 11,2 10,7 11,2 11,1 10,7 11,0 11,4 11,5 10,9

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 2 seconds R Server 'RServer@AstonUniversity' @ vre.aston.ac.uk Central Tendency - Ungrouped Data Measure Value S.E. Value/S.E. Arithmetic Mean 9.38693181818182 0.0668541597414428 140.409091288943 Geometric Mean 9.34499153761234 Harmonic Mean 9.30268606826703 Quadratic Mean 9.42850188138459 Winsorized Mean ( 1 / 58 ) 9.38863636363636 0.0663269334549309 141.550888524282 Winsorized Mean ( 2 / 58 ) 9.38863636363636 0.0659440122443689 142.372840900928 Winsorized Mean ( 3 / 58 ) 9.38693181818182 0.0656683776074261 142.944475867793 Winsorized Mean ( 4 / 58 ) 9.38920454545454 0.0653038573661229 143.777181381713 Winsorized Mean ( 5 / 58 ) 9.39204545454546 0.064869715493392 144.78320712694 Winsorized Mean ( 6 / 58 ) 9.38863636363636 0.0643391159544065 145.924236358634 Winsorized Mean ( 7 / 58 ) 9.39261363636364 0.063756944548482 147.319067795373 Winsorized Mean ( 8 / 58 ) 9.39261363636364 0.063756944548482 147.319067795373 Winsorized Mean ( 9 / 58 ) 9.39772727272727 0.061591208606163 152.582283825924 Winsorized Mean ( 10 / 58 ) 9.39204545454546 0.0607659079797974 154.561097937811 Winsorized Mean ( 11 / 58 ) 9.39829545454545 0.0599700922853476 156.716374719365 Winsorized Mean ( 12 / 58 ) 9.39147727272727 0.0590171711500551 159.131267895725 Winsorized Mean ( 13 / 58 ) 9.39147727272727 0.0571274537422628 164.395166553336 Winsorized Mean ( 14 / 58 ) 9.39147727272727 0.0571274537422628 164.395166553336 Winsorized Mean ( 15 / 58 ) 9.38295454545455 0.056040588154133 167.431407387229 Winsorized Mean ( 16 / 58 ) 9.39204545454545 0.0549760466246832 170.838865854872 Winsorized Mean ( 17 / 58 ) 9.39204545454546 0.0549760466246832 170.838865854872 Winsorized Mean ( 18 / 58 ) 9.39204545454546 0.0549760466246832 170.838865854872 Winsorized Mean ( 19 / 58 ) 9.39204545454546 0.0549760466246832 170.838865854872 Winsorized Mean ( 20 / 58 ) 9.39204545454546 0.0523130138375247 179.535545088561 Winsorized Mean ( 21 / 58 ) 9.39204545454546 0.0523130138375247 179.535545088561 Winsorized Mean ( 22 / 58 ) 9.39204545454546 0.0523130138375247 179.535545088561 Winsorized Mean ( 23 / 58 ) 9.37897727272727 0.0507707528770035 184.731892699103 Winsorized Mean ( 24 / 58 ) 9.37897727272727 0.0507707528770035 184.731892699103 Winsorized Mean ( 25 / 58 ) 9.37897727272727 0.0507707528770035 184.731892699103 Winsorized Mean ( 26 / 58 ) 9.36420454545455 0.049117037749487 190.650840818517 Winsorized Mean ( 27 / 58 ) 9.37954545454546 0.0474431866785906 197.700578548576 Winsorized Mean ( 28 / 58 ) 9.39545454545455 0.0458102961674215 205.094822157824 Winsorized Mean ( 29 / 58 ) 9.37897727272727 0.0440012602789888 213.152469117024 Winsorized Mean ( 30 / 58 ) 9.36193181818182 0.04224040011656 221.634543999301 Winsorized Mean ( 31 / 58 ) 9.36193181818182 0.04224040011656 221.634543999301 Winsorized Mean ( 32 / 58 ) 9.36193181818182 0.04224040011656 221.634543999301 Winsorized Mean ( 33 / 58 ) 9.36193181818182 0.04224040011656 221.634543999301 Winsorized Mean ( 34 / 58 ) 9.38125 0.0403105336528385 232.724530039543 Winsorized Mean ( 35 / 58 ) 9.36136363636364 0.0383495850429102 244.105995563942 Winsorized Mean ( 36 / 58 ) 9.36136363636364 0.0383495850429102 244.105995563942 Winsorized Mean ( 37 / 58 ) 9.38238636363636 0.0363494036675896 258.116651635802 Winsorized Mean ( 38 / 58 ) 9.38238636363636 0.0363494036675896 258.116651635802 Winsorized Mean ( 39 / 58 ) 9.38238636363636 0.0363494036675896 258.116651635802 Winsorized Mean ( 40 / 58 ) 9.38238636363636 0.0363494036675896 258.116651635802 Winsorized Mean ( 41 / 58 ) 9.38238636363636 0.0363494036675896 258.116651635802 Winsorized Mean ( 42 / 58 ) 9.38238636363636 0.0363494036675896 258.116651635802 Winsorized Mean ( 43 / 58 ) 9.35795454545454 0.0340496503578572 274.832617871365 Winsorized Mean ( 44 / 58 ) 9.38295454545455 0.0317911527125241 295.143577532442 Winsorized Mean ( 45 / 58 ) 9.38295454545455 0.0317911527125241 295.143577532442 Winsorized Mean ( 46 / 58 ) 9.38295454545455 0.0317911527125241 295.143577532442 Winsorized Mean ( 47 / 58 ) 9.38295454545455 0.0317911527125241 295.143577532442 Winsorized Mean ( 48 / 58 ) 9.38295454545455 0.0317911527125241 295.143577532442 Winsorized Mean ( 49 / 58 ) 9.35511363636364 0.0292855388093341 319.444818730189 Winsorized Mean ( 50 / 58 ) 9.35511363636364 0.0292855388093341 319.444818730189 Winsorized Mean ( 51 / 58 ) 9.35511363636364 0.0292855388093341 319.444818730189 Winsorized Mean ( 52 / 58 ) 9.35511363636364 0.0292855388093341 319.444818730189 Winsorized Mean ( 53 / 58 ) 9.35511363636364 0.0292855388093341 319.444818730189 Winsorized Mean ( 54 / 58 ) 9.35511363636364 0.0292855388093341 319.444818730189 Winsorized Mean ( 55 / 58 ) 9.38636363636364 0.0265965972382129 352.915959597933 Winsorized Mean ( 56 / 58 ) 9.38636363636364 0.0265965972382129 352.915959597933 Winsorized Mean ( 57 / 58 ) 9.38636363636364 0.0265965972382129 352.915959597933 Winsorized Mean ( 58 / 58 ) 9.38636363636364 0.0265965972382129 352.915959597933 Trimmed Mean ( 1 / 58 ) 9.38850574712644 0.0650807166848632 144.259409320704 Trimmed Mean ( 2 / 58 ) 9.38837209302326 0.0637405428237883 147.290432072057 Trimmed Mean ( 3 / 58 ) 9.38823529411765 0.0625138955909037 150.178375629557 Trimmed Mean ( 4 / 58 ) 9.38869047619048 0.0613008027660252 153.15770842391 Trimmed Mean ( 5 / 58 ) 9.38855421686747 0.060104646788827 156.203467093874 Trimmed Mean ( 6 / 58 ) 9.38780487804878 0.0589243478781068 159.319622806327 Trimmed Mean ( 7 / 58 ) 9.38765432098765 0.057766664483699 162.509890520626 Trimmed Mean ( 8 / 58 ) 9.386875 0.0566291163622438 165.760576943392 Trimmed Mean ( 9 / 58 ) 9.38607594936709 0.0553984661006387 169.428444685021 Trimmed Mean ( 10 / 58 ) 9.38461538461539 0.0544173882812871 172.456188748083 Trimmed Mean ( 11 / 58 ) 9.38376623376623 0.0534797993559898 175.463751673841 Trimmed Mean ( 12 / 58 ) 9.38223684210526 0.0525748812334023 178.454741541945 Trimmed Mean ( 13 / 58 ) 9.38133333333333 0.0517210437673275 181.383294883534 Trimmed Mean ( 14 / 58 ) 9.3804054054054 0.0510296517468397 183.82264201884 Trimmed Mean ( 15 / 58 ) 9.3804054054054 0.0502795004033621 186.565207095378 Trimmed Mean ( 16 / 58 ) 9.37916666666667 0.0495891727379682 189.137389248792 Trimmed Mean ( 17 / 58 ) 9.3781690140845 0.0489538565294613 191.571608019085 Trimmed Mean ( 18 / 58 ) 9.37714285714286 0.048262118939231 194.296128376585 Trimmed Mean ( 19 / 58 ) 9.37608695652174 0.0475080304427508 197.357938629351 Trimmed Mean ( 20 / 58 ) 9.375 0.046684753731136 200.81502526482 Trimmed Mean ( 21 / 58 ) 9.37388059701493 0.0460531705469365 203.544739389034 Trimmed Mean ( 22 / 58 ) 9.37272727272727 0.0453619227491212 206.621031576728 Trimmed Mean ( 23 / 58 ) 9.37153846153846 0.0446043310798942 210.103777697112 Trimmed Mean ( 24 / 58 ) 9.37109375 0.0439240399902206 213.347719200839 Trimmed Mean ( 25 / 58 ) 9.37063492063492 0.0431765289019645 217.03076090048 Trimmed Mean ( 26 / 58 ) 9.37016129032258 0.0423537089562656 221.235908760628 Trimmed Mean ( 27 / 58 ) 9.37049180327869 0.0416058974660603 225.220278229128 Trimmed Mean ( 28 / 58 ) 9.37 0.0409378842167699 228.883348010488 Trimmed Mean ( 29 / 58 ) 9.36864406779661 0.0403465207813552 232.20450949332 Trimmed Mean ( 30 / 58 ) 9.36864406779661 0.0398573005194055 235.054656128436 Trimmed Mean ( 31 / 58 ) 9.36842105263158 0.0394677323049943 237.369124231293 Trimmed Mean ( 32 / 58 ) 9.36875 0.0390325255008633 240.024181878592 Trimmed Mean ( 33 / 58 ) 9.3690909090909 0.0385462570926885 243.060977011645 Trimmed Mean ( 34 / 58 ) 9.36944444444445 0.0380026217722786 246.54731719797 Trimmed Mean ( 35 / 58 ) 9.3688679245283 0.0375666692787067 249.393095113671 Trimmed Mean ( 36 / 58 ) 9.36923076923077 0.0372474548924003 251.540160161182 Trimmed Mean ( 37 / 58 ) 9.36960784313725 0.0368848422185961 254.023259408533 Trimmed Mean ( 38 / 58 ) 9.369 0.0366444836478587 255.672861706362 Trimmed Mean ( 39 / 58 ) 9.36836734693878 0.0363665601390996 257.609389260502 Trimmed Mean ( 40 / 58 ) 9.36770833333333 0.0360462298095034 259.880392008808 Trimmed Mean ( 41 / 58 ) 9.36702127659574 0.035677843024664 262.544494915804 Trimmed Mean ( 42 / 58 ) 9.36630434782609 0.0352547609534237 265.67487892487 Trimmed Mean ( 43 / 58 ) 9.36555555555556 0.0347691193906141 269.364186372916 Trimmed Mean ( 44 / 58 ) 9.36590909090909 0.0344340101415949 271.995885823227 Trimmed Mean ( 45 / 58 ) 9.36511627906977 0.0342505231513848 273.429875440928 Trimmed Mean ( 46 / 58 ) 9.36428571428571 0.034027884061417 275.194475724206 Trimmed Mean ( 47 / 58 ) 9.36341463414634 0.0337602380613571 277.350373452016 Trimmed Mean ( 48 / 58 ) 9.3625 0.0334406237450155 279.973844728166 Trimmed Mean ( 49 / 58 ) 9.3625 0.0330606950100571 283.191263739371 Trimmed Mean ( 50 / 58 ) 9.36184210526316 0.032872273031488 284.794486109784 Trimmed Mean ( 51 / 58 ) 9.36216216216216 0.0326369584637783 286.857679233579 Trimmed Mean ( 52 / 58 ) 9.3625 0.0323467555994272 289.441702158401 Trimmed Mean ( 53 / 58 ) 9.36285714285714 0.0319919392391147 292.663007168059 Trimmed Mean ( 54 / 58 ) 9.36323529411765 0.0315605534293789 296.675256822387 Trimmed Mean ( 55 / 58 ) 9.36363636363636 0.0310377140042951 301.685760824415 Trimmed Mean ( 56 / 58 ) 9.3625 0.0307398841277985 304.571740123554 Trimmed Mean ( 57 / 58 ) 9.36129032258065 0.0303648568325024 308.293576822018 Trimmed Mean ( 58 / 58 ) 9.36 0.0298962424183117 313.082823889162 Median 9.3 Midrange 9.25 Midmean - Weighted Average at Xnp 9.33020833333333 Midmean - Weighted Average at X(n+1)p 9.37191011235955 Midmean - Empirical Distribution Function 9.33020833333333 Midmean - Empirical Distribution Function - Averaging 9.37191011235955 Midmean - Empirical Distribution Function - Interpolation 9.37191011235955 Midmean - Closest Observation 9.33020833333333 Midmean - True Basic - Statistics Graphics Toolkit 9.37191011235955 Midmean - MS Excel (old versions) 9.33020833333333 Number of observations 176

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Dec/12/t129216012616lds4glwm9e1xc/19a3y1292159979.png (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/12/t129216012616lds4glwm9e1xc/19a3y1292159979.ps (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/12/t129216012616lds4glwm9e1xc/2k1k11292159979.png (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/12/t129216012616lds4glwm9e1xc/2k1k11292159979.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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