geboortes new york

*Unverified author*

R Software Module: /rwasp_centraltendency.wasp (opens new window with default values)

Title produced by software: Central Tendency

Date of computation: Wed, 21 Apr 2010 15:35:54 +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/Apr/21/t1271864392pr04be5ubr1qwaw.htm/, Retrieved Wed, 21 Apr 2010 17:39:55 +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/Apr/21/t1271864392pr04be5ubr1qwaw.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:

kdgp1w52

Dataseries X:

» Textbox « » Textfile « » CSV «

26.663 23.598 26.931 24.740 25.806 24.364 24.477 23.901 23.175 23.227 21.672 21.870 21.439 21.089 23.709 21.669 21.752 20.761 23.479 23.824 23.105 23.110 21.759 22.073 21.937 20.035 23.590 21.672 22.222 22.123 23.950 23.504 22.238 23.142 21.059 21.573 21.548 20.000 22.424 20.615 21.761 22.874 24.104 23.748 23.262 22.907 21.519 22.025 22.604 20.894 24.677 23.673 25.320 23.583 24.671 24.454 24.122 24.252 22.084 22.991 23.287 23.049 25.076 24.037 24.430 24.667 26.451 25.618 25.014 25.110 22.964 23.981 23.798 22.270 24.775 22.646 23.988 24.737 26.276 25.816 25.210 25.199 23.162 24.707 24.364 22.644 25.565 24.062 25.431 24.635 27.009 26.606 26.268 26.462 25.246 25.180 24.657 23.304 26.982 26.199 27.210 26.122 26.706 26.878 26.152 26.379 24.712 25.688 24.990 24.239 26.721 23.475 24.767 26.219 28.361 28.599 27.914 27.784 25.693 26.881 26.217 24.218 27.914 26.975 28.527 27.139 28.982 28.169 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 5 seconds R Server 'George Udny Yule' @ 72.249.76.132 Central Tendency - Ungrouped Data Measure Value S.E. Value/S.E. Arithmetic Mean 25.0593095238095 0.178898597200866 140.075494810466 Geometric Mean 24.9517656724406 Harmonic Mean 24.8434629593482 Quadratic Mean 25.1657262970796 Winsorized Mean ( 1 / 56 ) 25.0551190476190 0.178188696708164 140.610035936534 Winsorized Mean ( 2 / 56 ) 25.0616428571429 0.177033046088316 141.564772289126 Winsorized Mean ( 3 / 56 ) 25.0625892857143 0.176414783234111 142.066264664764 Winsorized Mean ( 4 / 56 ) 25.0636607142857 0.175671420613637 142.673524394213 Winsorized Mean ( 5 / 56 ) 25.0675 0.174840201186556 143.373776911025 Winsorized Mean ( 6 / 56 ) 25.0675 0.174549225537464 143.612782713949 Winsorized Mean ( 7 / 56 ) 25.0812916666667 0.172525319208652 145.377454055502 Winsorized Mean ( 8 / 56 ) 25.0810535714286 0.171506659657938 146.239531581174 Winsorized Mean ( 9 / 56 ) 25.0819107142857 0.171221819018849 146.487818305005 Winsorized Mean ( 10 / 56 ) 25.0770892857143 0.170212096978098 147.328478591865 Winsorized Mean ( 11 / 56 ) 25.0728988095238 0.168107041637026 149.148414994185 Winsorized Mean ( 12 / 56 ) 25.0679702380952 0.167439963114855 149.713185381557 Winsorized Mean ( 13 / 56 ) 25.0646428571429 0.167030216615003 150.060530154947 Winsorized Mean ( 14 / 56 ) 25.0647261904762 0.165423521246806 151.518514426256 Winsorized Mean ( 15 / 56 ) 25.0614226190476 0.164875667419255 152.001947960702 Winsorized Mean ( 16 / 56 ) 25.0433273809524 0.162705072613589 153.918540944499 Winsorized Mean ( 17 / 56 ) 25.0515238095238 0.161060794140625 155.540794041105 Winsorized Mean ( 18 / 56 ) 25.0505595238095 0.159287029264561 157.266788384903 Winsorized Mean ( 19 / 56 ) 25.0594940476190 0.158016858013261 158.587472012106 Winsorized Mean ( 20 / 56 ) 25.0596130952381 0.156729345749439 159.891008128755 Winsorized Mean ( 21 / 56 ) 25.0529880952381 0.155676667142580 160.929627766843 Winsorized Mean ( 22 / 56 ) 25.0562619047619 0.154891627455855 161.766406075777 Winsorized Mean ( 23 / 56 ) 25.0674880952381 0.153110039986756 163.722040026941 Winsorized Mean ( 24 / 56 ) 25.0697738095238 0.152856076625289 164.009010063629 Winsorized Mean ( 25 / 56 ) 25.0720059523810 0.152047549820453 164.895823589315 Winsorized Mean ( 26 / 56 ) 25.0783511904762 0.14751471659628 170.005757860152 Winsorized Mean ( 27 / 56 ) 25.0994047619048 0.143585010382678 174.805188194859 Winsorized Mean ( 28 / 56 ) 25.0935714285714 0.141526951241867 177.305956274625 Winsorized Mean ( 29 / 56 ) 25.0737202380952 0.139322622692841 179.968764249969 Winsorized Mean ( 30 / 56 ) 25.0871130952381 0.132282401561485 189.648152733133 Winsorized Mean ( 31 / 56 ) 25.0599880952381 0.128272388585841 195.365412397133 Winsorized Mean ( 32 / 56 ) 25.0573214285714 0.125837414882931 199.124572384793 Winsorized Mean ( 33 / 56 ) 25.06125 0.125174436243505 200.210608108892 Winsorized Mean ( 34 / 56 ) 25.0480952380952 0.121579845542670 206.021772163744 Winsorized Mean ( 35 / 56 ) 25.0562202380952 0.120096000897351 208.634925816650 Winsorized Mean ( 36 / 56 ) 25.0562202380952 0.119888438252298 208.996135101584 Winsorized Mean ( 37 / 56 ) 25.0621666666667 0.119099455324240 210.43057332577 Winsorized Mean ( 38 / 56 ) 25.0651071428571 0.118510771828258 211.500665772227 Winsorized Mean ( 39 / 56 ) 25.0579107142857 0.117239097167476 213.733398837852 Winsorized Mean ( 40 / 56 ) 25.0619583333333 0.115257910960307 217.442413492678 Winsorized Mean ( 41 / 56 ) 25.0668392857143 0.114097539528878 219.696580567979 Winsorized Mean ( 42 / 56 ) 25.0723392857143 0.113435571462367 221.027134279763 Winsorized Mean ( 43 / 56 ) 25.0365059523810 0.109252687382904 229.161465517402 Winsorized Mean ( 44 / 56 ) 25.0773630952381 0.104708510026502 239.49689560945 Winsorized Mean ( 45 / 56 ) 25.0669166666667 0.103542250686686 242.093604305724 Winsorized Mean ( 46 / 56 ) 25.0658214285714 0.102183355177738 245.30239181295 Winsorized Mean ( 47 / 56 ) 25.0837261904762 0.0997905229343987 251.363811440952 Winsorized Mean ( 48 / 56 ) 25.0820119047619 0.099268653357942 252.667997966301 Winsorized Mean ( 49 / 56 ) 25.0793869047619 0.098603506777045 254.345790778715 Winsorized Mean ( 50 / 56 ) 25.1017083333333 0.0966109961893554 259.822476979065 Winsorized Mean ( 51 / 56 ) 25.0740833333333 0.0921253904681538 272.173428041003 Winsorized Mean ( 52 / 56 ) 25.08275 0.0907509815027505 276.390950099419 Winsorized Mean ( 53 / 56 ) 25.0818035714286 0.087861470263517 285.469882261273 Winsorized Mean ( 54 / 56 ) 25.0840535714286 0.0865843377159241 289.706593976929 Winsorized Mean ( 55 / 56 ) 25.0804523809524 0.0818314160555631 306.489287242969 Winsorized Mean ( 56 / 56 ) 25.0917857142857 0.0799853356350805 313.704824953948 Trimmed Mean ( 1 / 56 ) 25.0600240963855 0.175946506223741 142.429790930422 Trimmed Mean ( 2 / 56 ) 25.0650487804878 0.173534539088152 144.438386226705 Trimmed Mean ( 3 / 56 ) 25.0668148148148 0.171582868365036 146.091594421223 Trimmed Mean ( 4 / 56 ) 25.06829375 0.16971734446524 147.706139457858 Trimmed Mean ( 5 / 56 ) 25.0695253164557 0.167926269103870 149.288884045587 Trimmed Mean ( 6 / 56 ) 25.0699615384615 0.166196528278907 150.845278166038 Trimmed Mean ( 7 / 56 ) 25.0704090909091 0.164388628884876 152.506954166923 Trimmed Mean ( 8 / 56 ) 25.0686907894737 0.162809980033786 153.975148109910 Trimmed Mean ( 9 / 56 ) 25.06696 0.161270005749248 155.434731235612 Trimmed Mean ( 10 / 56 ) 25.0650743243243 0.159642920655413 157.007114511686 Trimmed Mean ( 11 / 56 ) 25.0636917808219 0.158021312926977 158.609565485663 Trimmed Mean ( 12 / 56 ) 25.0627152777778 0.156540889805070 160.103314277738 Trimmed Mean ( 13 / 56 ) 25.0621971830986 0.155013079653279 161.677951558383 Trimmed Mean ( 14 / 56 ) 25.0619714285714 0.153397219605904 163.379567719406 Trimmed Mean ( 15 / 56 ) 25.0617318840580 0.151820957880862 165.074257427124 Trimmed Mean ( 16 / 56 ) 25.0617573529412 0.150160152519995 166.900185784001 Trimmed Mean ( 17 / 56 ) 25.0632014925373 0.148578789885816 168.686267480026 Trimmed Mean ( 18 / 56 ) 25.0640757575758 0.147019678115175 170.481095312565 Trimmed Mean ( 19 / 56 ) 25.0650461538462 0.145490473436059 172.279638397506 Trimmed Mean ( 20 / 56 ) 25.0654296875 0.143937292265670 174.141317326131 Trimmed Mean ( 21 / 56 ) 25.0658174603175 0.142354718768492 176.079990021837 Trimmed Mean ( 22 / 56 ) 25.0666451612903 0.140712711917745 178.140587439913 Trimmed Mean ( 23 / 56 ) 25.0672950819672 0.138976702130488 180.370484388319 Trimmed Mean ( 24 / 56 ) 25.0672833333333 0.137229889100923 182.666352771720 Trimmed Mean ( 25 / 56 ) 25.0671355932203 0.135321156624840 185.241807108667 Trimmed Mean ( 26 / 56 ) 25.0668534482759 0.133284202922823 188.070700792581 Trimmed Mean ( 27 / 56 ) 25.0662017543860 0.131457029696791 190.67981234782 Trimmed Mean ( 28 / 56 ) 25.0643571428571 0.129791655551856 193.112238504755 Trimmed Mean ( 29 / 56 ) 25.0627636363636 0.128126336557498 195.609773210963 Trimmed Mean ( 30 / 56 ) 25.0621759259259 0.126471873521710 198.164028317520 Trimmed Mean ( 31 / 56 ) 25.0608584905660 0.125260811423481 200.069424792727 Trimmed Mean ( 32 / 56 ) 25.0609038461538 0.124250854090430 201.696028808900 Trimmed Mean ( 33 / 56 ) 25.0610882352941 0.123315403028735 203.227558113356 Trimmed Mean ( 34 / 56 ) 25.06108 0.122303383898939 204.909130075324 Trimmed Mean ( 35 / 56 ) 25.0617346938776 0.121462121806213 206.333746860296 Trimmed Mean ( 36 / 56 ) 25.0620104166667 0.120619618773516 207.777231195904 Trimmed Mean ( 37 / 56 ) 25.0622978723404 0.119659676064690 209.446479353591 Trimmed Mean ( 38 / 56 ) 25.0623043478261 0.118619520806935 211.283136007752 Trimmed Mean ( 39 / 56 ) 25.0621666666667 0.117468843320521 213.351608462535 Trimmed Mean ( 40 / 56 ) 25.062375 0.116256640255404 215.578008662047 Trimmed Mean ( 41 / 56 ) 25.0623953488372 0.115041597519333 217.855070594142 Trimmed Mean ( 42 / 56 ) 25.0621785714286 0.113740420666435 220.345400734257 Trimmed Mean ( 43 / 56 ) 25.0616829268293 0.112288788487045 223.189538906823 Trimmed Mean ( 44 / 56 ) 25.0629125 0.111025541869379 225.740060151982 Trimmed Mean ( 45 / 56 ) 25.0622051282051 0.110008111829643 227.821427996294 Trimmed Mean ( 46 / 56 ) 25.0619736842105 0.108913479219418 230.109017394627 Trimmed Mean ( 47 / 56 ) 25.0617837837838 0.107748387553888 232.595441590712 Trimmed Mean ( 48 / 56 ) 25.0606944444444 0.106612250715831 235.063928171279 Trimmed Mean ( 49 / 56 ) 25.0596285714286 0.10529744947536 237.988941767223 Trimmed Mean ( 50 / 56 ) 25.0586323529412 0.103788505879846 241.439378479455 Trimmed Mean ( 51 / 56 ) 25.0586323529412 0.102207748415982 245.173509262266 Trimmed Mean ( 52 / 56 ) 25.05553125 0.100869129736036 248.396425304428 Trimmed Mean ( 53 / 56 ) 25.0541129032258 0.0993990619102628 252.055828513197 Trimmed Mean ( 54 / 56 ) 25.05265 0.0979779112227375 255.696918696774 Trimmed Mean ( 55 / 56 ) 25.0509655172414 0.0963864441797057 259.901334989966 Trimmed Mean ( 56 / 56 ) 25.0493571428571 0.0950967293897682 263.409239240906 Median 24.957 Midrange 25 Midmean - Weighted Average at Xnp 25.041 Midmean - Weighted Average at X(n+1)p 25.0621785714286 Midmean - Empirical Distribution Function 25.041 Midmean - Empirical Distribution Function - Averaging 25.0621785714286 Midmean - Empirical Distribution Function - Interpolation 25.0621785714286 Midmean - Closest Observation 25.041 Midmean - True Basic - Statistics Graphics Toolkit 25.0621785714286 Midmean - MS Excel (old versions) 25.0623953488372 Number of observations 168

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Apr/21/t1271864392pr04be5ubr1qwaw/1uq621271864149.png (open in new window) http://www.freestatistics.org/blog/date/2010/Apr/21/t1271864392pr04be5ubr1qwaw/1uq621271864149.ps (open in new window) http://www.freestatistics.org/blog/date/2010/Apr/21/t1271864392pr04be5ubr1qwaw/25in51271864149.png (open in new window) http://www.freestatistics.org/blog/date/2010/Apr/21/t1271864392pr04be5ubr1qwaw/25in51271864149.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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