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central tendency G29

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

Title produced by software: Central Tendency

Date of computation: Mon, 10 Dec 2007 11:35:25 -0700

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2007/Dec/10/t11973108573tiwb85ho0i4eko.htm/, Retrieved Mon, 10 Dec 2007 19:21:00 +0100

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Dataseries X:

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0.00498291873874305 0.0793223539142789 -0.0625809545639328 0.0280654227924886 0.0186770910482273 -0.0278451405168712 -0.0160415828684045 0.00800891826163896 -0.0284266699553964 0.00358089966203660 -0.0106258926391915 -0.0382814374185135 0.057838663944805 0.102402564588083 0.0746995870753183 0.0127932859545176 0.167725484938012 -0.128004517546978 -0.0735393462043395 0.0147181318738355 0.0102185013252131 -0.0589476023320615 0.00182819684467975 0.0581414158522751 -0.0272344430774991 0.0212995495732571 -0.0623124997311786 -5.83752587663966e-05 -0.0228268581805917 -0.067345143444185 -0.0315427622540225 0.0278186227243244 -0.0427383325146042 -0.00649440817096458 0.0247474807917305 -0.00401872802482828 -0.0255976981173509 -0.0468480706314915 -0.0363519086429775 -0.0530492158953395 0.0183982147919632 0.00422452551721264 -0.0852117605914602 0.0136687391795425 -0.0355419600553288 0.0341683247004703 0.0597143568478087 0.0214081232490564 -0.100731459894530 -0.047051344399291 -0.00658029169493979 -0.0227885142727402 0.0296743493753668 -0.01857996737444 0.0187962800103278 -0.0457667737637948 -0.00366069135268798 0.00367890076878297 -0.079647400200006 -0.0091243185857044 0.0492864925892338 0.0130250746511882 -0.0370922819395680 -0.0180627686095107 0.0332692067764153 -0.0722971672259876 -0.0178566785177168 -0.00334868566024671 -0.03083981570561 0.00408244299952987 0.0651662575662542 0.00411742686205496 0.0112606978192815 0.00215006014629004 0.0660015269583667 -0.0232299374591953 -0.0139150003490922 -0.00855913172763145 0.0488255884062676 -0.0147035752055471 0.107591796121569 0.0119750091944324 -0.0362475666004212 0.0251623283732521 0.0475618270062474 0.019537551882598 -0.101853195244507 0.0204083037138769 -0.032065972743049 -0.0856968557787612 0.0563411939342044 -0.00834749088071352 0.0323182614314677 -0.0649957289713692 0.00287215024827336 0.0459215548055463 0.0523217349874594 -0.0170521880891474 0.0119447347469332 -0.0300746672353176 0.0140385177312430 0.0333951893316602 -0.0089196803612861 0.0215215666160393 0.00243102727727784 -0.00264251063758536 0.0738057587248742 0.05247280805371 -0.0153046984939991 0.0818695834808763 0.0702499252958937 -0.0751547835318593 0.0210770835191783 -0.0139042522041262 -0.0443501136634712 -0.00147348818232285 -0.0257508828596622 0.0417988534479328 0.0124136981987064 0.0487343707199885 0.109803612572215 -0.0235359827120885 -0.0239611038278067 0.0137637477921384 -0.0257678975395814 -0.0385359711280735 0.0458658519725548 -0.020304258604555 -0.0215233594345037 -0.00159379200433651 0.055063884787975 0.0308125037919451 -0.0252862495465696 0.0101609583037332 -0.0192284886412875 0.000548473782408188 -0.000269275150888149 0.0335372325235799 0.0193127888352320 -0.0315397448784029 0.0408624926202439

Text written by user:

Output produced by software:

Summary of compuational 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 0.000883693215772588 0.00381497908777709 0.231637761424139 Geometric Mean NaN Harmonic Mean -0.00759473005104579 Quadratic Mean 0.0451480904947742 Winsorized Mean ( 1 / 47 ) 0.000658370165678077 0.00366574656340074 0.179600568203848 Winsorized Mean ( 2 / 47 ) 0.000642908022406176 0.00365596778423613 0.175851665098987 Winsorized Mean ( 3 / 47 ) 0.000852384034795172 0.00357383334638066 0.238506934202293 Winsorized Mean ( 4 / 47 ) 0.000283649682457422 0.00346314909078859 0.0819051317229986 Winsorized Mean ( 5 / 47 ) 0.000390640137239578 0.00341416630314336 0.114417430949372 Winsorized Mean ( 6 / 47 ) 0.000385101832098561 0.00335093396931762 0.114923730406118 Winsorized Mean ( 7 / 47 ) 0.000420926391244163 0.00333111129323564 0.126362151903757 Winsorized Mean ( 8 / 47 ) 0.000289655216740413 0.00328876243649385 0.0880742292377963 Winsorized Mean ( 9 / 47 ) 0.000334567479140982 0.00319946331261976 0.104569875147915 Winsorized Mean ( 10 / 47 ) 0.000441953655077388 0.00316590567131300 0.139597859494688 Winsorized Mean ( 11 / 47 ) 0.000205014723012848 0.00307782256893101 0.0666103124599719 Winsorized Mean ( 12 / 47 ) 9.3994624052898e-05 0.00305616652823960 0.0307557272106636 Winsorized Mean ( 13 / 47 ) 0.000376320094913968 0.00300788462213202 0.125111213423881 Winsorized Mean ( 14 / 47 ) 0.000813290520202619 0.00290755615687747 0.279716186488395 Winsorized Mean ( 15 / 47 ) 0.00131547800422593 0.00280747100389601 0.468563344875298 Winsorized Mean ( 16 / 47 ) 0.00104452163923693 0.00276498560500066 0.377767478191513 Winsorized Mean ( 17 / 47 ) 0.00115667628196448 0.00274654404415233 0.421138806940729 Winsorized Mean ( 18 / 47 ) 0.000950048754572734 0.00267375779751412 0.355323416150867 Winsorized Mean ( 19 / 47 ) 0.00110513146628986 0.00263971088845282 0.418656251760054 Winsorized Mean ( 20 / 47 ) 0.00168827241668016 0.00256931494271403 0.657090490781483 Winsorized Mean ( 21 / 47 ) 0.00155154752244042 0.00254236583240238 0.610277050873636 Winsorized Mean ( 22 / 47 ) 0.00148116051620905 0.00248884759470825 0.595119009841452 Winsorized Mean ( 23 / 47 ) 0.00159284435069683 0.00247438815423986 0.643732612430874 Winsorized Mean ( 24 / 47 ) 0.000918349630345223 0.00238579367124465 0.384924162308691 Winsorized Mean ( 25 / 47 ) 0.000877435750452227 0.00235167130346629 0.373111560769106 Winsorized Mean ( 26 / 47 ) 0.000284012376020746 0.00213639925943876 0.132939746522547 Winsorized Mean ( 27 / 47 ) 0.000263354180472341 0.00211194663908726 0.124697364790503 Winsorized Mean ( 28 / 47 ) 0.000235746216951752 0.00210871086526128 0.111796368499549 Winsorized Mean ( 29 / 47 ) 0.000353791975170846 0.00209037877538192 0.169247783864533 Winsorized Mean ( 30 / 47 ) 0.000314260725244207 0.00205042700514257 0.153265990184497 Winsorized Mean ( 31 / 47 ) 0.000345533270296382 0.00197570660598662 0.174890982927007 Winsorized Mean ( 32 / 47 ) 0.000219207034142486 0.00193372138755970 0.113360195296345 Winsorized Mean ( 33 / 47 ) -1.44210632738358e-05 0.00187831993394541 -0.00767763947622299 Winsorized Mean ( 34 / 47 ) 0.000279701957801477 0.001835726247978 0.152365832383538 Winsorized Mean ( 35 / 47 ) -0.000375438386101774 0.00176588845687414 -0.212605946111880 Winsorized Mean ( 36 / 47 ) -0.000442245919517171 0.00175096175711644 -0.252573145998048 Winsorized Mean ( 37 / 47 ) -0.00120703476619565 0.00165752376126843 -0.72821566387197 Winsorized Mean ( 38 / 47 ) -0.000880476685574094 0.00161779239035404 -0.544245782600948 Winsorized Mean ( 39 / 47 ) -0.00079292101070291 0.00160288633837008 -0.49468324217499 Winsorized Mean ( 40 / 47 ) -0.000769210599691731 0.00158789297818663 -0.484422193597812 Winsorized Mean ( 41 / 47 ) -0.000846471036532936 0.00155702548839174 -0.543646229842557 Winsorized Mean ( 42 / 47 ) -0.00109442233287301 0.00153073944100445 -0.714963176329259 Winsorized Mean ( 43 / 47 ) -0.000777139729983428 0.00148534975816764 -0.523203188818049 Winsorized Mean ( 44 / 47 ) -0.00055789116103337 0.00143206844631901 -0.389570179042333 Winsorized Mean ( 45 / 47 ) -0.000252599352150286 0.00139479639837915 -0.181101236312213 Winsorized Mean ( 46 / 47 ) -0.000132005944442227 0.00136548765962384 -0.09667311418881 Winsorized Mean ( 47 / 47 ) -0.00118630066217503 0.00123261396639171 -0.962426756892702 Trimmed Mean ( 1 / 47 ) 0.000610645870740294 0.00355804845476813 0.171623820895966 Trimmed Mean ( 2 / 47 ) 0.000561528165731335 0.00343947437224904 0.163259877806316 Trimmed Mean ( 3 / 47 ) 0.000519029796134473 0.00331420939981213 0.156607423829012 Trimmed Mean ( 4 / 47 ) 0.000401227922322046 0.00320987765408981 0.124997886386987 Trimmed Mean ( 5 / 47 ) 0.000432866341827603 0.00313072195982081 0.138264064130555 Trimmed Mean ( 6 / 47 ) 0.000442097186551497 0.00305673273495655 0.144630631751251 Trimmed Mean ( 7 / 47 ) 0.000452643571036882 0.00298992907981782 0.151389400535368 Trimmed Mean ( 8 / 47 ) 0.000457754568009195 0.00292041972756978 0.156742732453090 Trimmed Mean ( 9 / 47 ) 0.000481841975050758 0.00285171417131088 0.168965732925914 Trimmed Mean ( 10 / 47 ) 0.000500910573694724 0.0027914115416924 0.179447052580082 Trimmed Mean ( 11 / 47 ) 0.000507896225396442 0.00273018887992377 0.186029702608203 Trimmed Mean ( 12 / 47 ) 0.000541079047335903 0.00267591189541442 0.202203610762792 Trimmed Mean ( 13 / 47 ) 0.000586759412323514 0.00261885662742483 0.224051750744556 Trimmed Mean ( 14 / 47 ) 0.000606958148712041 0.00256230189723722 0.236880029385487 Trimmed Mean ( 15 / 47 ) 0.000588236871762124 0.0025129681622361 0.234080511087214 Trimmed Mean ( 16 / 47 ) 0.000525520664008365 0.00247084090849668 0.212688992723576 Trimmed Mean ( 17 / 47 ) 0.000482775840698068 0.00242913550948945 0.198743890084393 Trimmed Mean ( 18 / 47 ) 0.000429543368866940 0.00238468740828200 0.180125649749790 Trimmed Mean ( 19 / 47 ) 0.000389958007818117 0.00234366011342224 0.166388464600652 Trimmed Mean ( 20 / 47 ) 0.000337410088253492 0.00230153664697227 0.146602092431317 Trimmed Mean ( 21 / 47 ) 0.000241212316380683 0.00226210057832275 0.106632003321237 Trimmed Mean ( 22 / 47 ) 0.000150511646741791 0.00222069648431214 0.067776775351816 Trimmed Mean ( 23 / 47 ) 6.0740598610268e-05 0.00218000898937405 0.0278625450199215 Trimmed Mean ( 24 / 47 ) -4.02536178666865e-05 0.00213538785048103 -0.018850729087748 Trimmed Mean ( 25 / 47 ) -0.000102141464935313 0.00209518650706516 -0.0487505358548664 Trimmed Mean ( 26 / 47 ) -0.000164218043528411 0.00205323961991382 -0.0799799701582337 Trimmed Mean ( 27 / 47 ) -0.000192158135993676 0.00202963795340502 -0.0946760655866248 Trimmed Mean ( 28 / 47 ) -0.00022014386001185 0.00200493013406694 -0.109801262533420 Trimmed Mean ( 29 / 47 ) -0.000247803283786320 0.00197657478378015 -0.125370052183101 Trimmed Mean ( 30 / 47 ) -0.000283914365741603 0.00194565993084874 -0.145921885546439 Trimmed Mean ( 31 / 47 ) -0.000319501997736961 0.00191426718363701 -0.166905644346848 Trimmed Mean ( 32 / 47 ) -0.000358785605945047 0.00188623895031526 -0.190212171095863 Trimmed Mean ( 33 / 47 ) -0.00039274267355019 0.00185818084390038 -0.211358692475707 Trimmed Mean ( 34 / 47 ) -0.00041488603056512 0.00183161294402874 -0.226514030662260 Trimmed Mean ( 35 / 47 ) -0.000455456414309813 0.00180502524222777 -0.252326894746185 Trimmed Mean ( 36 / 47 ) -0.000460128274341835 0.00178182941297391 -0.258233628310059 Trimmed Mean ( 37 / 47 ) -0.000461173635880093 0.00175561289527616 -0.262685263431919 Trimmed Mean ( 38 / 47 ) -0.000417445394975938 0.00173549867724058 -0.240533398527085 Trimmed Mean ( 39 / 47 ) -0.000390174128487074 0.00171579134370923 -0.22740185158155 Trimmed Mean ( 40 / 47 ) -0.000366303884522201 0.00169318967434733 -0.216339545457835 Trimmed Mean ( 41 / 47 ) -0.000342231915522665 0.00166707582565538 -0.205288751870733 Trimmed Mean ( 42 / 47 ) -0.000311809272791622 0.00163893221300277 -0.190251476124410 Trimmed Mean ( 43 / 47 ) -0.000264039384708732 0.00160750580081524 -0.164254078943183 Trimmed Mean ( 44 / 47 ) -0.000232294255843557 0.00157532660111778 -0.147457838697533 Trimmed Mean ( 45 / 47 ) -0.000211835626774144 0.00154341693897611 -0.137251070287381 Trimmed Mean ( 46 / 47 ) -0.000209228966784105 0.00150904605564401 -0.138649821853723 Trimmed Mean ( 47 / 47 ) -0.000214265250849880 0.00147006819088816 -0.145751912855436 Median 0.000548473782408188 Midrange 0.019860483695517 Midmean - Weighted Average at Xnp -0.00082142476841784 Midmean - Weighted Average at X(n+1)p -0.000455456414309813 Midmean - Empirical Distribution Function -0.000455456414309813 Midmean - Empirical Distribution Function - Averaging -0.000455456414309813 Midmean - Empirical Distribution Function - Interpolation -0.000455456414309813 Midmean - Closest Observation -0.000807018096605252 Midmean - True Basic - Statistics Graphics Toolkit -0.000455456414309813 Midmean - MS Excel (old versions) -0.000455456414309813 Number of observations 141

Charts produced by software:

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2007/Dec/10/t11973108573tiwb85ho0i4eko/1sor01197311722.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2007/Dec/10/t11973108573tiwb85ho0i4eko/1sor01197311722.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2007/Dec/10/t11973108573tiwb85ho0i4eko/2sokt1197311722.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2007/Dec/10/t11973108573tiwb85ho0i4eko/2sokt1197311722.ps (open in new window)

Parameters:

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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