Schermbreedte

*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: Thu, 11 Nov 2010 17:48:21 +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/Nov/11/t1289497754tghranb3g3mv45u.htm/, Retrieved Thu, 11 Nov 2010 18:49:14 +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/Nov/11/t1289497754tghranb3g3mv45u.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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1280 1024 1120 1024 1280 1280 1280 1024 1280 1280 1280 1280 1280 1688 1440 1600 1280 1280 1280 1176 1280 1503 1440 1366 1280 1024 1280 2560 1280 1024 1280 1280 1440 1280 1440 1024 1440 1143 1280 1440 1280 1366 1024 1408 1366 1176 1920 1257 1280 1280 1440 1680 1440 1024 1140 1280 1280 1280 1280 1280 1440 1280 1152 1280 1280 1440 1280 1280 1440 1280 1280 1440 1280 1280 1600 1024 1366 1280 1280 1440 1366 1280 1024 1280 1440 1280 1280 1408 1280 1600 1600 1680 1440 1440 917 1280 1760 1280 1280 1280 1024 1366 1440 1280 1280 1920 1024 1024 1600 1117 1440 983 1024 1024 1280 1440 1280 1280 1280 1440 1280 1024 1024 1152 1280 1024 1366 1680 1680 1280 1366 1024 1440 1024 1280 1280 1280 1024 1280

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 1309.15107913669 18.1361034320425 72.1848044174532 Geometric Mean 1293.57970868797 Harmonic Mean 1279.11501047029 Quadratic Mean 1326.37372794663 Winsorized Mean ( 1 / 46 ) 1305.02158273381 16.2544876590135 80.286848168367 Winsorized Mean ( 2 / 46 ) 1305.61151079137 16.1749168023151 80.7182829283237 Winsorized Mean ( 3 / 46 ) 1302.15827338129 15.3230879456001 84.9801474744653 Winsorized Mean ( 4 / 46 ) 1300.08633093525 14.9029791873146 87.2366735935513 Winsorized Mean ( 5 / 46 ) 1299.79856115108 14.8491429792018 87.5335743599224 Winsorized Mean ( 6 / 46 ) 1299.79856115108 14.8491429792018 87.5335743599224 Winsorized Mean ( 7 / 46 ) 1299.79856115108 14.8491429792018 87.5335743599224 Winsorized Mean ( 8 / 46 ) 1299.79856115108 14.8491429792018 87.5335743599224 Winsorized Mean ( 9 / 46 ) 1294.61870503597 13.9557719085507 92.7658257471778 Winsorized Mean ( 10 / 46 ) 1294.61870503597 13.9557719085507 92.7658257471778 Winsorized Mean ( 11 / 46 ) 1294.61870503597 13.9557719085507 92.7658257471778 Winsorized Mean ( 12 / 46 ) 1294.61870503597 13.9557719085507 92.7658257471778 Winsorized Mean ( 13 / 46 ) 1294.61870503597 13.9557719085507 92.7658257471778 Winsorized Mean ( 14 / 46 ) 1284.84892086331 12.5578586450577 102.314332178677 Winsorized Mean ( 15 / 46 ) 1278.05035971223 11.7887308977624 108.412887765113 Winsorized Mean ( 16 / 46 ) 1278.05035971223 11.7887308977624 108.412887765113 Winsorized Mean ( 17 / 46 ) 1278.05035971223 11.7887308977624 108.412887765113 Winsorized Mean ( 18 / 46 ) 1278.05035971223 11.7887308977624 108.412887765113 Winsorized Mean ( 19 / 46 ) 1278.05035971223 11.7887308977624 108.412887765113 Winsorized Mean ( 20 / 46 ) 1278.05035971223 11.7887308977624 108.412887765113 Winsorized Mean ( 21 / 46 ) 1278.05035971223 11.7887308977624 108.412887765113 Winsorized Mean ( 22 / 46 ) 1278.05035971223 11.7887308977624 108.412887765113 Winsorized Mean ( 23 / 46 ) 1293.43884892086 9.53781861068176 135.611600693716 Winsorized Mean ( 24 / 46 ) 1293.95683453237 9.46862012235895 136.657381731564 Winsorized Mean ( 25 / 46 ) 1297.55395683453 9.00075398932673 144.160584588046 Winsorized Mean ( 26 / 46 ) 1298.11510791367 8.92984671503075 145.368128853620 Winsorized Mean ( 27 / 46 ) 1299.86330935252 8.71228979528908 149.198814536149 Winsorized Mean ( 28 / 46 ) 1299.86330935252 8.71228979528908 149.198814536149 Winsorized Mean ( 29 / 46 ) 1304.87050359712 8.11560098248362 160.785443544292 Winsorized Mean ( 30 / 46 ) 1304.87050359712 8.11560098248362 160.785443544292 Winsorized Mean ( 31 / 46 ) 1322.93525179856 6.35311986859668 208.233951060454 Winsorized Mean ( 32 / 46 ) 1328.23021582734 5.99847334474374 221.428043352268 Winsorized Mean ( 33 / 46 ) 1328.23021582734 5.99847334474374 221.428043352268 Winsorized Mean ( 34 / 46 ) 1328.23021582734 5.99847334474374 221.428043352268 Winsorized Mean ( 35 / 46 ) 1328.23021582734 5.99847334474374 221.428043352268 Winsorized Mean ( 36 / 46 ) 1319.94244604317 4.89701861793514 269.540009753879 Winsorized Mean ( 37 / 46 ) 1319.94244604317 4.89701861793514 269.540009753879 Winsorized Mean ( 38 / 46 ) 1308.46043165468 3.44480385038404 379.835975714206 Winsorized Mean ( 39 / 46 ) 1308.46043165468 3.44480385038404 379.835975714206 Winsorized Mean ( 40 / 46 ) 1308.46043165468 3.44480385038404 379.835975714206 Winsorized Mean ( 41 / 46 ) 1308.46043165468 3.44480385038404 379.835975714206 Winsorized Mean ( 42 / 46 ) 1308.46043165468 3.44480385038404 379.835975714206 Winsorized Mean ( 43 / 46 ) 1308.46043165468 3.44480385038404 379.835975714206 Winsorized Mean ( 44 / 46 ) 1308.46043165468 3.44480385038404 379.835975714206 Winsorized Mean ( 45 / 46 ) 1308.46043165468 3.44480385038404 379.835975714206 Winsorized Mean ( 46 / 46 ) 1280 0 Inf Trimmed Mean ( 1 / 46 ) 1302.88321167883 15.6878944671937 83.0502279578308 Trimmed Mean ( 2 / 46 ) 1300.68148148148 15.0578565498305 86.3789263217627 Trimmed Mean ( 3 / 46 ) 1298.10526315789 14.4006059179482 90.1424058511319 Trimmed Mean ( 4 / 46 ) 1296.67175572519 14.0295152458187 92.4245587253378 Trimmed Mean ( 5 / 46 ) 1295.75193798450 13.7556631704785 94.1977076587154 Trimmed Mean ( 6 / 46 ) 1294.86614173228 13.4685140296478 96.1402378081158 Trimmed Mean ( 7 / 46 ) 1293.952 13.1516605403174 98.3869676405723 Trimmed Mean ( 8 / 46 ) 1293.0081300813 12.8009786124585 101.008537645933 Trimmed Mean ( 9 / 46 ) 1292.03305785124 12.4114379725335 104.100190542829 Trimmed Mean ( 10 / 46 ) 1291.69747899160 12.1415038852767 106.386942770571 Trimmed Mean ( 11 / 46 ) 1291.35042735043 11.8421519564196 109.046939450088 Trimmed Mean ( 12 / 46 ) 1290.99130434783 11.5090750890489 112.171594533798 Trimmed Mean ( 13 / 46 ) 1290.61946902655 11.1369642166682 115.886110785463 Trimmed Mean ( 14 / 46 ) 1290.23423423423 10.7191452327924 120.367268678019 Trimmed Mean ( 15 / 46 ) 1290.72477064220 10.4549652443333 123.455673020223 Trimmed Mean ( 16 / 46 ) 1291.82242990654 10.2567963549090 125.947945655396 Trimmed Mean ( 17 / 46 ) 1292.96190476190 10.0337244865175 128.861611308869 Trimmed Mean ( 18 / 46 ) 1294.14563106796 9.78190117848841 132.300010749847 Trimmed Mean ( 19 / 46 ) 1295.37623762376 9.49657417631053 136.404582702583 Trimmed Mean ( 20 / 46 ) 1296.65656565657 9.17176348568054 141.374836767322 Trimmed Mean ( 21 / 46 ) 1297.98969072165 8.79976636440773 147.502744615085 Trimmed Mean ( 22 / 46 ) 1299.37894736842 8.3703628361242 155.235677688983 Trimmed Mean ( 23 / 46 ) 1300.82795698925 7.86945889348672 165.300813511574 Trimmed Mean ( 24 / 46 ) 1301.31868131868 7.62903455775939 170.574490319372 Trimmed Mean ( 25 / 46 ) 1301.79775280899 7.36251548476134 176.814263481469 Trimmed Mean ( 26 / 46 ) 1302.06896551724 7.11968167655507 182.88303110586 Trimmed Mean ( 27 / 46 ) 1302.31764705882 6.8489957505633 190.147241214409 Trimmed Mean ( 28 / 46 ) 1302.46987951807 6.56546269701668 198.382039412075 Trimmed Mean ( 29 / 46 ) 1302.62962962963 6.23382956146314 208.961380285779 Trimmed Mean ( 30 / 46 ) 1302.49367088608 5.93305926828539 219.531545529712 Trimmed Mean ( 31 / 46 ) 1302.35064935065 5.57677313292673 233.531222860982 Trimmed Mean ( 32 / 46 ) 1301.12 5.38402575526282 241.663034157697 Trimmed Mean ( 33 / 46 ) 1299.50684931507 5.17866199551601 250.934865113857 Trimmed Mean ( 34 / 46 ) 1297.80281690141 4.92669073281292 263.422830310362 Trimmed Mean ( 35 / 46 ) 1296 4.61363116187984 280.906720656001 Trimmed Mean ( 36 / 46 ) 1294.08955223881 4.21696361786026 306.877096771217 Trimmed Mean ( 37 / 46 ) 1292.55384615385 3.96220308091822 326.220998711228 Trimmed Mean ( 38 / 46 ) 1290.92063492063 3.63654022057835 354.985936252158 Trimmed Mean ( 39 / 46 ) 1289.86885245902 3.53866044009494 364.507664494763 Trimmed Mean ( 40 / 46 ) 1288.74576271186 3.41307634468121 377.590663836216 Trimmed Mean ( 41 / 46 ) 1287.54385964912 3.25099465938310 396.04613189166 Trimmed Mean ( 42 / 46 ) 1286.25454545455 3.03916280579816 423.226601418197 Trimmed Mean ( 43 / 46 ) 1284.86792452830 2.75591957367270 466.221125174569 Trimmed Mean ( 44 / 46 ) 1283.37254901961 2.36078431372549 543.621262458472 Trimmed Mean ( 45 / 46 ) 1281.75510204082 1.75510204081633 730.302325581395 Trimmed Mean ( 46 / 46 ) 1280 0 Inf Median 1280 Midrange 1738.5 Midmean - Weighted Average at Xnp 1326.78260869565 Midmean - Weighted Average at X(n+1)p 1326.78260869565 Midmean - Empirical Distribution Function 1326.78260869565 Midmean - Empirical Distribution Function - Averaging 1326.78260869565 Midmean - Empirical Distribution Function - Interpolation 1326.78260869565 Midmean - Closest Observation 1326.78260869565 Midmean - True Basic - Statistics Graphics Toolkit 1326.78260869565 Midmean - MS Excel (old versions) 1326.78260869565 Number of observations 139

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Nov/11/t1289497754tghranb3g3mv45u/1e8751289497696.png (open in new window) http://www.freestatistics.org/blog/date/2010/Nov/11/t1289497754tghranb3g3mv45u/1e8751289497696.ps (open in new window) http://www.freestatistics.org/blog/date/2010/Nov/11/t1289497754tghranb3g3mv45u/2e8751289497696.png (open in new window) http://www.freestatistics.org/blog/date/2010/Nov/11/t1289497754tghranb3g3mv45u/2e8751289497696.ps (open in new window)

Parameters (Session):

par2 = grey ; par3 = FALSE ; par4 = Unknown ;

Parameters (R input):

par2 = grey ; par3 = FALSE ; par4 = Unknown ;

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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