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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 11:03:41 -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/t1197308948qqx2nj1uewcmoou.htm/, Retrieved Mon, 10 Dec 2007 18:49:10 +0100

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Dataseries X:

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0.00503304609379793 0.0369990364302084 -0.0242253351525622 0.0774302913819214 -0.00764564307593042 -0.0615028099029395 -0.00325428840227112 -0.0123720899756001 -0.0121167399878335 -0.0555780237857432 0.000566454761534063 -0.0128295409407334 0.0333721592949187 0.0580101905630014 0.068144322930172 -0.00190855402359612 0.0630611837886725 -0.099173840670388 -0.0547062428745422 0.00146161103846953 0.00332756954060009 -0.0129861283501000 0.00828503800214442 0.00490815785100907 -0.0239934193883204 0.00859110731553958 -0.0401668590238771 -0.0151402191409042 -0.0111881596304491 -0.034313519274618 -0.0114415359525752 -0.0408561468763118 -0.00516004612766263 0.0238717452666721 0.0227434563437132 -0.0169648548379087 -0.0284217359364245 -0.04372801472545 -0.0115017844438929 -0.0167654149249827 0.000131664027486877 -0.000197945656498888 -0.0727844280851953 0.0613314010816017 -0.0219983778735946 0.0143970353497691 0.00424764682678269 0.00939639794455438 -0.00770575510573135 -0.0208875226171585 0.0133008235715266 -0.00759397480233925 0.0275323432358752 -0.0519422596420513 -0.0275692601985194 -0.0217925628961622 0.035190209057431 -0.00156089575412199 -0.0112336238504849 0.0136233293094081 0.000331213276318465 -0.0204624539762008 -0.0127689635938335 -0.019167050670025 0.0255498113425121 -0.0214409560932260 0.0369804725779241 -0.0176513890898153 -0.0253928193263784 -0.0237668717208255 0.0413405410035761 -0.00547298468324708 0.0122082838606632 -0.0115049363205761 0.0415860303545941 -0.0118019105819762 0.0104018998342141 0.0195251565982408 0.0713332837677605 0.00176536914999215 0.054369511060961 -0.0274598360070444 -0.0120782054880664 -0.0124868418131703 0.0139227878367221 0.0165768970921327 -0.0537109866158012 0.0250315498933045 0.00888544930718549 -0.0448416547272101 -0.0186545351743934 0.0154273952082749 0.044965398993444 0.0252596703861769 0.0200283930802225 0.0142181875359606 0.0510818777227975 0.00324108655092736 0.0696829862742891 -0.0194434812935693 -0.0208602478491304 -0.0349563408194555 -0.0645277276935783 -0.0727873041575275 0.00773451265950609 -0.0223149917053602 0.050946467850733 0.0233278838704400 -0.0141471722941908 0.0401139422966903 0.084876777442429 -0.0626624161464466 0.0252528267421308 0.00643754378152739 -0.00977534536026603 -0.0455191277539297 -0.0214176684336396 0.0177791357832877 -7.43775976124184e-05 0.0458210429699735 0.0439677925676429 0.00144100703965755 -0.0215577949166317 0.00830477214712921 0.0133426314557363 -0.0296399750462832 0.0357312385014144 -0.0460763442095855 0.0149983540855594 0.0479043557764234 0.0605261105261965 0.00453841177683056 0.000778060657639301 0.0240132737937353 -0.015493232135241 -0.0255503726249735 0.0271469368419943 0.0480546001633302 -0.0051538252567056 -0.000569555116127773 0.084623977811395

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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 0.00114846723444601 0.00287248344802869 0.399816832794693 Geometric Mean NaN Harmonic Mean -0.0247323193481301 Quadratic Mean 0.0340070807226440 Winsorized Mean ( 1 / 47 ) 0.00133381288609017 0.00283122641674783 0.47110781327842 Winsorized Mean ( 2 / 47 ) 0.00123181557605980 0.00281061516037052 0.438272586524228 Winsorized Mean ( 3 / 47 ) 0.00127776648621844 0.00275473924227318 0.46384298978659 Winsorized Mean ( 4 / 47 ) 0.00128386617568398 0.00273737923301869 0.469012901171232 Winsorized Mean ( 5 / 47 ) 0.00127042443452759 0.00272090145847974 0.466913063157172 Winsorized Mean ( 6 / 47 ) 0.00130623919945086 0.00264368774113043 0.494097384925014 Winsorized Mean ( 7 / 47 ) 0.00126364336561335 0.00262287458323963 0.481778036086105 Winsorized Mean ( 8 / 47 ) 0.0012744215615473 0.00260687106377631 0.488870193564992 Winsorized Mean ( 9 / 47 ) 0.00122672839200824 0.00256426573730877 0.478393629084523 Winsorized Mean ( 10 / 47 ) 0.00138454654310224 0.00246454469316460 0.561785934311631 Winsorized Mean ( 11 / 47 ) 0.00117153529694916 0.00241996699581047 0.484112096973786 Winsorized Mean ( 12 / 47 ) 0.00121766833138789 0.00241036105604937 0.505180884968194 Winsorized Mean ( 13 / 47 ) 0.00105371826108041 0.00235775286844290 0.446916330877503 Winsorized Mean ( 14 / 47 ) 0.00132395037789771 0.00231773689180602 0.571225484039332 Winsorized Mean ( 15 / 47 ) 0.00117564985087482 0.00227678302254564 0.516364466544705 Winsorized Mean ( 16 / 47 ) 0.00166981997602570 0.00218939824420772 0.762684441007193 Winsorized Mean ( 17 / 47 ) 0.0016270444939237 0.00216326581685758 0.752124163958357 Winsorized Mean ( 18 / 47 ) 0.00191961241076872 0.00205279229783222 0.935122570751976 Winsorized Mean ( 19 / 47 ) 0.00205069216550612 0.00203040956299893 1.00998941439048 Winsorized Mean ( 20 / 47 ) 0.00199762507770744 0.00199361730096095 1.00201030395581 Winsorized Mean ( 21 / 47 ) 0.00155000014738726 0.00192974490777954 0.803215047304243 Winsorized Mean ( 22 / 47 ) 0.00184503411657383 0.00189800434750058 0.972091617705454 Winsorized Mean ( 23 / 47 ) 0.00166695852868705 0.00186860936872306 0.892085074916534 Winsorized Mean ( 24 / 47 ) 0.00177358912099901 0.00183630053013716 0.96584904915675 Winsorized Mean ( 25 / 47 ) 0.00149235968868155 0.00179067955147529 0.833404104856192 Winsorized Mean ( 26 / 47 ) 0.000457288921445636 0.00165476102220770 0.276347409268526 Winsorized Mean ( 27 / 47 ) 0.00066150727451499 0.00161748753352704 0.408972100744746 Winsorized Mean ( 28 / 47 ) 0.00040722126957836 0.00157446037034986 0.258641803405869 Winsorized Mean ( 29 / 47 ) 0.000389877628527429 0.00156337012659923 0.249382805705468 Winsorized Mean ( 30 / 47 ) 0.000438372167992195 0.0015581549688403 0.28134054491285 Winsorized Mean ( 31 / 47 ) 0.000415410616303979 0.00155003988384307 0.267999953184453 Winsorized Mean ( 32 / 47 ) 0.000189597637017102 0.00152349046586649 0.124449506751109 Winsorized Mean ( 33 / 47 ) 0.000280550619646823 0.00150728059285280 0.186130320377728 Winsorized Mean ( 34 / 47 ) 0.000155983631285574 0.00149201477977722 0.104545634131630 Winsorized Mean ( 35 / 47 ) 0.000109656128569957 0.00146605278322099 0.074796848943622 Winsorized Mean ( 36 / 47 ) -0.000323388275053667 0.00136481061251482 -0.236947362577865 Winsorized Mean ( 37 / 47 ) -0.000382904705991142 0.00134353768411503 -0.284997369644570 Winsorized Mean ( 38 / 47 ) -0.000715338763680623 0.00128054128546762 -0.558622179385183 Winsorized Mean ( 39 / 47 ) -0.000770406931457214 0.00121886953015451 -0.632066773676386 Winsorized Mean ( 40 / 47 ) -0.000901745266762517 0.00116677788118182 -0.772850841026525 Winsorized Mean ( 41 / 47 ) -0.000968508739112657 0.00114864853310575 -0.843172398865973 Winsorized Mean ( 42 / 47 ) -0.000768676893254793 0.00109405107440088 -0.702596899944303 Winsorized Mean ( 43 / 47 ) -0.000715562689263892 0.00107833500237695 -0.66358106496274 Winsorized Mean ( 44 / 47 ) -0.000497857196434846 0.00103987363226220 -0.478767016480435 Winsorized Mean ( 45 / 47 ) -0.000222883127250761 0.000996058735107616 -0.223765044565048 Winsorized Mean ( 46 / 47 ) -0.000263373059435435 0.000982310392983336 -0.268115924779698 Winsorized Mean ( 47 / 47 ) -0.000257116571872036 0.00097908768366413 -0.262608320135133 Trimmed Mean ( 1 / 47 ) 0.00126784851284062 0.00275697752612690 0.459869005396551 Trimmed Mean ( 2 / 47 ) 0.00119995817248890 0.00267544436485590 0.448507989271355 Trimmed Mean ( 3 / 47 ) 0.00118332152840187 0.00259781675807053 0.455506157132021 Trimmed Mean ( 4 / 47 ) 0.00114994624255692 0.00253528309719911 0.453577055685553 Trimmed Mean ( 5 / 47 ) 0.00111391053536052 0.00247209963275462 0.450592897066736 Trimmed Mean ( 6 / 47 ) 0.00107969586903097 0.0024069525366638 0.448573809655385 Trimmed Mean ( 7 / 47 ) 0.00103777643387454 0.00235316090052376 0.441013801327208 Trimmed Mean ( 8 / 47 ) 0.00100137959116005 0.00229819075908068 0.435725183909722 Trimmed Mean ( 9 / 47 ) 0.000962254674671638 0.00224052236951221 0.42947782524534 Trimmed Mean ( 10 / 47 ) 0.000928011521187284 0.00218427466604987 0.424860268541931 Trimmed Mean ( 11 / 47 ) 0.000873917875733495 0.00213838933285976 0.408680431717628 Trimmed Mean ( 12 / 47 ) 0.000841311771311266 0.00209445221424988 0.401685827724925 Trimmed Mean ( 13 / 47 ) 0.000802857948868654 0.00204710117590246 0.392192607927509 Trimmed Mean ( 14 / 47 ) 0.000778779457362965 0.00200196014868637 0.389008471459323 Trimmed Mean ( 15 / 47 ) 0.00072931414217931 0.00195713107493007 0.372644505787824 Trimmed Mean ( 16 / 47 ) 0.000690822805833092 0.00191260812339339 0.361194118849302 Trimmed Mean ( 17 / 47 ) 0.000610192781886154 0.00187398697920599 0.325612071298752 Trimmed Mean ( 18 / 47 ) 0.000529870041607558 0.00183402216978634 0.288911470284618 Trimmed Mean ( 19 / 47 ) 0.000424177660781386 0.00180249686886415 0.235327821151047 Trimmed Mean ( 20 / 47 ) 0.000304668257359714 0.0017695516862701 0.172172567619034 Trimmed Mean ( 21 / 47 ) 0.000184109211062225 0.00173671860088115 0.106009811243350 Trimmed Mean ( 22 / 47 ) 8.95630048659405e-05 0.00170728101017248 0.0524594395019321 Trimmed Mean ( 23 / 47 ) -2.88682997995196e-05 0.00167729780179983 -0.0172111951548154 Trimmed Mean ( 24 / 47 ) -0.000140654921032154 0.00164666850575011 -0.0854178728390034 Trimmed Mean ( 25 / 47 ) -0.000264239357811639 0.00161532682152405 -0.163582597831399 Trimmed Mean ( 26 / 47 ) -0.000375556420982668 0.00158494678869189 -0.236952069092885 Trimmed Mean ( 27 / 47 ) -0.000427471183706979 0.00156598542930914 -0.272972644385054 Trimmed Mean ( 28 / 47 ) -0.000494375742578133 0.00154794497085887 -0.319375528126061 Trimmed Mean ( 29 / 47 ) -0.00054907676612119 0.00153169204370073 -0.358477259433015 Trimmed Mean ( 30 / 47 ) -0.000605438013309549 0.00151381445079850 -0.399942022610627 Trimmed Mean ( 31 / 47 ) -0.00066753811270345 0.00149334962987457 -0.447007250913853 Trimmed Mean ( 32 / 47 ) -0.00073150785329417 0.00147022979325972 -0.49754661254164 Trimmed Mean ( 33 / 47 ) -0.000785622800849957 0.00144628131938129 -0.54320192781446 Trimmed Mean ( 34 / 47 ) -0.000848026475524115 0.00141990250444364 -0.597242749322704 Trimmed Mean ( 35 / 47 ) -0.000906669982177042 0.00139065111562665 -0.651975158966079 Trimmed Mean ( 36 / 47 ) -0.000966008276841773 0.00135931123150551 -0.710660115543861 Trimmed Mean ( 37 / 47 ) -0.00100357437147367 0.00133553008332014 -0.75144272975025 Trimmed Mean ( 38 / 47 ) -0.00103996290487617 0.00130971150796563 -0.794039678624755 Trimmed Mean ( 39 / 47 ) -0.00105908237183882 0.00128715913391230 -0.822806088179447 Trimmed Mean ( 40 / 47 ) -0.00107619176111743 0.00126804215098074 -0.848703460121626 Trimmed Mean ( 41 / 47 ) -0.00108661419997507 0.00125155691183150 -0.868209978869398 Trimmed Mean ( 42 / 47 ) -0.00109373994665098 0.00123336662359275 -0.886792236573549 Trimmed Mean ( 43 / 47 ) -0.00111358145770244 0.00121831113952777 -0.914036998901671 Trimmed Mean ( 44 / 47 ) -0.00113820657676774 0.00120118407246894 -0.947570487201224 Trimmed Mean ( 45 / 47 ) -0.00117844243355337 0.00118492599024840 -0.994528302401681 Trimmed Mean ( 46 / 47 ) -0.00123954622592918 0.00117035913048214 -1.05911612397004 Trimmed Mean ( 47 / 47 ) -0.00130320969330921 0.00115305796750384 -1.13022044861320 Median -7.43775976124184e-05 Midrange -0.0071485316139795 Midmean - Weighted Average at Xnp -0.00124452892968976 Midmean - Weighted Average at X(n+1)p -0.00090666998217704 Midmean - Empirical Distribution Function -0.00090666998217704 Midmean - Empirical Distribution Function - Averaging -0.00090666998217704 Midmean - Empirical Distribution Function - Interpolation -0.00090666998217704 Midmean - Closest Observation -0.00118380300810695 Midmean - True Basic - Statistics Graphics Toolkit -0.00090666998217704 Midmean - MS Excel (old versions) -0.00090666998217704 Number of observations 141

Charts produced by software:

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2007/Dec/10/t1197308948qqx2nj1uewcmoou/1ywcl1197309818.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2007/Dec/10/t1197308948qqx2nj1uewcmoou/1ywcl1197309818.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2007/Dec/10/t1197308948qqx2nj1uewcmoou/2v6dj1197309818.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2007/Dec/10/t1197308948qqx2nj1uewcmoou/2v6dj1197309818.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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