Girale deposito's

*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, 12 Dec 2009 07:26:49 -0700

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2009/Dec/12/t1260628154bgjaepajzwdeq6p.htm/, Retrieved Sat, 12 Dec 2009 15:29:17 +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/2009/Dec/12/t1260628154bgjaepajzwdeq6p.htm/}, year = {2009}, } @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 = {2009}, note = {{ISBN} 3-900051-07-0}, url = {http://www.R-project.org}, }

Original text written by user:

IsPrivate?

No (this computation is public)

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Dataseries X:

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1213,8 1245,6 1306,3 1255,8 1257,6 1287,8 1300,4 1320,9 1370,8 1327,3 1320 1345,3 1346,7 1395,4 1462 1491,6 1461,8 1477,9 1490,3 1521,1 1561,9 1552,6 1523,6 1548,3 1552,4 1587 1621,3 1648,7 1641,8 1650,6 1688,6 1670,7 1682,2 1678,9 1650,6 1662,4 1664,5 1683,2 1736,2 1747,6 1749 1759,7 1793,6 1817,4 1858,4 1839,9 1809,1 1877,7 1880,3 1930,9 2039,3 1992,7 1987,8 1984,4 2016,5 2016,7 2064,1 2031,5 2000,3 2057,8 2041,2 2093,2 2158,3 2128,8 2131,9 2170,3 2190,8 2217,7 2254,4 2223,3 2210,5 2250,8 2249,1 2288,6 2329,2 2313,8 2309,8 2345,9 2361,3 2372 2410,4 2398,5 2362,3 2419,1 2421,6 2465 2480,5 2506,1 2506,6 2525,8 2550 2578,3 2807,8 2815,3 2767,7 2815,4 2838,8 2864 2948,6 2922,8 2917,2 2936,8 2993,4 3007,8 3046,3 3011,5 2958,6 3019,8 2998,5 3040,4 3166 3110 3099,2 3150,3 3163,6 3182,6 3244,4 3223,2 3143,6 3217 3182,3 3217,2 3262,5 3227,9 3171,6 3219 3195,4 3221,6 3262,1 3179,5 3133,6 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 1 seconds R Server 'Gwilym Jenkins' @ 72.249.127.135 Central Tendency - Ungrouped Data Measure Value S.E. Value/S.E. Arithmetic Mean 2349.21586206897 58.946003033589 39.8536922126903 Geometric Mean 2239.37406459521 Harmonic Mean 2130.14967598533 Quadratic Mean 2453.39806594853 Winsorized Mean ( 1 / 48 ) 2349.10482758621 58.8659690532452 39.905990937844 Winsorized Mean ( 2 / 48 ) 2348.48965517241 58.735164440745 39.9843888671102 Winsorized Mean ( 3 / 48 ) 2348.38620689655 58.7098841650946 39.9998439835581 Winsorized Mean ( 4 / 48 ) 2349.10896551724 58.5877347631028 40.0955758917079 Winsorized Mean ( 5 / 48 ) 2346.65379310345 58.1268993346887 40.371219176713 Winsorized Mean ( 6 / 48 ) 2346.04965517241 57.9816665280984 40.4619217703151 Winsorized Mean ( 7 / 48 ) 2344.00275862069 57.5433716148558 40.7345397539331 Winsorized Mean ( 8 / 48 ) 2342.68413793103 57.3626913163382 40.8398574783011 Winsorized Mean ( 9 / 48 ) 2342.91379310345 57.2925147867898 40.8938899230108 Winsorized Mean ( 10 / 48 ) 2339.25172413793 56.5378675622798 41.3749549637879 Winsorized Mean ( 11 / 48 ) 2335.77724137931 56.1048462671434 41.6323614943618 Winsorized Mean ( 12 / 48 ) 2337.54 55.8361921759085 41.8642444784867 Winsorized Mean ( 13 / 48 ) 2339.70965517241 55.5693303573483 42.104334173662 Winsorized Mean ( 14 / 48 ) 2344.46965517241 54.6416569010572 42.906269467957 Winsorized Mean ( 15 / 48 ) 2344.42827586207 54.6322339319039 42.9129125267744 Winsorized Mean ( 16 / 48 ) 2344.36206896552 54.2293513069215 43.2305017940773 Winsorized Mean ( 17 / 48 ) 2345.26482758621 54.0065077898064 43.4255967209358 Winsorized Mean ( 18 / 48 ) 2345.22758620690 53.9663631089377 43.4572102157926 Winsorized Mean ( 19 / 48 ) 2348.77862068966 53.5109404270667 43.8934281839234 Winsorized Mean ( 20 / 48 ) 2349.09586206897 53.4708200660893 43.9322953933662 Winsorized Mean ( 21 / 48 ) 2352.41241379310 53.0613376620435 44.3338317020202 Winsorized Mean ( 22 / 48 ) 2353.00413793103 52.9925372002817 44.4025567041264 Winsorized Mean ( 23 / 48 ) 2349.60965517241 52.6039534075489 44.6660279878362 Winsorized Mean ( 24 / 48 ) 2349.03034482759 52.2066487956409 44.9948502540872 Winsorized Mean ( 25 / 48 ) 2353.30620689655 51.7518314520415 45.4729067719539 Winsorized Mean ( 26 / 48 ) 2358.95448275862 51.071181065458 46.1895423905538 Winsorized Mean ( 27 / 48 ) 2361.30068965517 50.5270070181788 46.7334368094595 Winsorized Mean ( 28 / 48 ) 2361.55172413793 50.275232357542 46.9724676226915 Winsorized Mean ( 29 / 48 ) 2361.45172413793 50.1845262163052 47.0553754748945 Winsorized Mean ( 30 / 48 ) 2358.7 49.88017065257 47.2873281935829 Winsorized Mean ( 31 / 48 ) 2359.79034482759 49.4746128571036 47.696994651445 Winsorized Mean ( 32 / 48 ) 2358.04689655172 49.1870151351681 47.9404348906252 Winsorized Mean ( 33 / 48 ) 2354.08689655172 48.4638851125877 48.5740441791425 Winsorized Mean ( 34 / 48 ) 2353.47724137931 48.0021653481181 49.028564113964 Winsorized Mean ( 35 / 48 ) 2341.50482758621 46.5640102247412 50.2857210168311 Winsorized Mean ( 36 / 48 ) 2340.28827586207 46.3858395486757 50.4526445706831 Winsorized Mean ( 37 / 48 ) 2336.40965517241 45.701821200456 51.1229004403243 Winsorized Mean ( 38 / 48 ) 2346.70896551724 44.2638184250776 53.0164149640492 Winsorized Mean ( 39 / 48 ) 2348.78 43.8672571690158 53.5428962643004 Winsorized Mean ( 40 / 48 ) 2346.60068965517 43.5633523954661 53.8663936685322 Winsorized Mean ( 41 / 48 ) 2348.18413793103 43.1260432343788 54.4493294960835 Winsorized Mean ( 42 / 48 ) 2347.92344827586 41.1584193192125 57.046006312003 Winsorized Mean ( 43 / 48 ) 2349.55448275862 40.4247048882964 58.1217473139515 Winsorized Mean ( 44 / 48 ) 2348.49241379310 39.8232388748756 58.9729133075302 Winsorized Mean ( 45 / 48 ) 2351.13034482759 38.7343177675281 60.698896491178 Winsorized Mean ( 46 / 48 ) 2355.22275862069 38.0167918352063 61.9521702102066 Winsorized Mean ( 47 / 48 ) 2344.23448275862 35.6915274616712 65.6804191212066 Winsorized Mean ( 48 / 48 ) 2336.75310344828 34.7731760838302 67.1998754964141 Trimmed Mean ( 1 / 48 ) 2347.81468531469 58.4934011398833 40.1381119846328 Trimmed Mean ( 2 / 48 ) 2346.48794326241 58.0845686126453 40.3977854929195 Trimmed Mean ( 3 / 48 ) 2345.44388489209 57.7089105052211 40.6426644405267 Trimmed Mean ( 4 / 48 ) 2344.40583941606 57.3053000598455 40.9108029618156 Trimmed Mean ( 5 / 48 ) 2343.14296296296 56.8974839414989 41.1818379415889 Trimmed Mean ( 6 / 48 ) 2342.37744360902 56.5617874578673 41.412719591895 Trimmed Mean ( 7 / 48 ) 2341.7 56.2202704576802 41.6522364787042 Trimmed Mean ( 8 / 48 ) 2341.33023255814 55.923111566012 41.8669520882152 Trimmed Mean ( 9 / 48 ) 2341.13700787402 55.6215473776787 42.0904688605181 Trimmed Mean ( 10 / 48 ) 2340.908 55.2949224245363 42.3349540492575 Trimmed Mean ( 11 / 48 ) 2341.10325203252 55.0383409420846 42.5358615823104 Trimmed Mean ( 12 / 48 ) 2341.68347107438 54.8058442112405 42.7268935416583 Trimmed Mean ( 13 / 48 ) 2342.10420168067 54.5748564814423 42.9154440832489 Trimmed Mean ( 14 / 48 ) 2342.33247863248 54.3429632267876 43.1027742977008 Trimmed Mean ( 15 / 48 ) 2342.14 54.1842671371209 43.2254623666476 Trimmed Mean ( 16 / 48 ) 2341.94424778761 53.9974286497705 43.3714031639831 Trimmed Mean ( 17 / 48 ) 2341.74684684685 53.8218974648378 43.5091841267158 Trimmed Mean ( 18 / 48 ) 2341.47155963303 53.6376047537253 43.6535443814799 Trimmed Mean ( 19 / 48 ) 2341.18878504673 53.4236445474537 43.8230825485364 Trimmed Mean ( 20 / 48 ) 2340.63714285714 53.2183626675331 43.9817579033692 Trimmed Mean ( 21 / 48 ) 2340.04174757282 52.9794312375589 44.1688725777389 Trimmed Mean ( 22 / 48 ) 2339.19603960396 52.7389597084573 44.3542317204418 Trimmed Mean ( 23 / 48 ) 2338.27676767677 52.4620063919962 44.5708604853036 Trimmed Mean ( 24 / 48 ) 2337.54020618557 52.1760647267401 44.8010063316941 Trimmed Mean ( 25 / 48 ) 2336.80947368421 51.8791900116805 45.0432914075583 Trimmed Mean ( 26 / 48 ) 2335.78064516129 51.5735162550592 45.2903120588012 Trimmed Mean ( 27 / 48 ) 2334.36043956044 51.2778781826394 45.523733085172 Trimmed Mean ( 28 / 48 ) 2332.73483146067 50.9788143247959 45.7589071530454 Trimmed Mean ( 29 / 48 ) 2331.01954022989 50.6462124623268 46.0255451868945 Trimmed Mean ( 30 / 48 ) 2329.22941176471 50.2586966100381 46.3448033648268 Trimmed Mean ( 31 / 48 ) 2327.51325301205 49.8311105546511 46.7080349425366 Trimmed Mean ( 32 / 48 ) 2325.64938271605 49.3657197286908 47.1106143189564 Trimmed Mean ( 33 / 48 ) 2323.79113924051 48.8448481667935 47.5749485658204 Trimmed Mean ( 34 / 48 ) 2322.06233766234 48.3078943053608 48.0679684149399 Trimmed Mean ( 35 / 48 ) 2320.276 47.7204609010916 48.6222462270251 Trimmed Mean ( 36 / 48 ) 2319.07123287671 47.189539506237 49.1437563735964 Trimmed Mean ( 37 / 48 ) 2317.86760563380 46.5717835738561 49.7697839284596 Trimmed Mean ( 38 / 48 ) 2316.81449275362 45.9131650691166 50.4607880825891 Trimmed Mean ( 39 / 48 ) 2315.11194029851 45.2914790121702 51.1158388021822 Trimmed Mean ( 40 / 48 ) 2313.18615384615 44.5835454337892 51.8843024111094 Trimmed Mean ( 41 / 48 ) 2311.26349206349 43.7625175598078 52.8137689726103 Trimmed Mean ( 42 / 48 ) 2309.12295081967 42.8199781263387 53.9262991682689 Trimmed Mean ( 43 / 48 ) 2306.85254237288 41.9530032874749 54.9865888400317 Trimmed Mean ( 44 / 48 ) 2304.32631578947 40.9892754882555 56.217785953541 Trimmed Mean ( 45 / 48 ) 2301.68 39.8880585490798 57.7034852966816 Trimmed Mean ( 46 / 48 ) 2298.67358490566 38.6920129499248 59.4095114120995 Trimmed Mean ( 47 / 48 ) 2295.17843137255 37.305791414321 61.5233813399673 Trimmed Mean ( 48 / 48 ) 2292.08979591837 36.0140846933551 63.644260722841 Median 2254.4 Midrange 2449.4 Midmean - Weighted Average at Xnp 2309.05277777778 Midmean - Weighted Average at X(n+1)p 2319.07123287671 Midmean - Empirical Distribution Function 2319.07123287671 Midmean - Empirical Distribution Function - Averaging 2319.07123287671 Midmean - Empirical Distribution Function - Interpolation 2319.07123287671 Midmean - Closest Observation 2310.46486486487 Midmean - True Basic - Statistics Graphics Toolkit 2319.07123287671 Midmean - MS Excel (old versions) 2319.07123287671 Number of observations 145

Charts produced by software:

http://www.freestatistics.org/blog/date/2009/Dec/12/t1260628154bgjaepajzwdeq6p/1qdc71260628007.png (open in new window) http://www.freestatistics.org/blog/date/2009/Dec/12/t1260628154bgjaepajzwdeq6p/1qdc71260628007.ps (open in new window) http://www.freestatistics.org/blog/date/2009/Dec/12/t1260628154bgjaepajzwdeq6p/2oev91260628007.png (open in new window) http://www.freestatistics.org/blog/date/2009/Dec/12/t1260628154bgjaepajzwdeq6p/2oev91260628007.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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