Centrummaten - Huisprijzen USA - Yannick Geerts

*Unverified author*

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

Title produced by software: Central Tendency

Date of computation: Fri, 12 Mar 2010 08:56:34 -0700

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2010/Mar/12/t126840958185b7jdvois3ik09.htm/, Retrieved Fri, 12 Mar 2010 16:59:43 +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/Mar/12/t126840958185b7jdvois3ik09.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 «

178600 181600 178500 176700 183500 175900 179800 186500 182700 182800 178600 183300 182900 191400 189300 192200 187900 193900 189100 193100 194800 200200 211500 202100 200300 199200 204900 207300 200000 197700 202200 200200 208300 215100 210700 208100 209000 211000 210200 205500 211400 211700 209300 207500 203300 207100 206900 228700 226900 265000 227100 228100 226500 225200 217800 221300 215300 231300 227100 237800 230200 233400 231100 237200 243700 239700 248400 241000 254500 242800 268300 253900 262100 264100 261000 269300 260400 263200 279200 272200 269200 289600 283200 284300 283000 289100 289600 289100 287400 279600 289300 295000 299600 293600 294400 290200 301000 307900 298800 310300 293900 305000 311300 317300 296200 306800 291800 301900 314600 321500 329400 311700 309700 306500 307100 301300 292200 310100 316800 284400 284600 301200 287600 314300 298200 299400 301900 265500 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 2 seconds R Server 'Gwilym Jenkins' @ 72.249.127.135 Central Tendency - Ungrouped Data Measure Value S.E. Value/S.E. Arithmetic Mean 249465.972222222 3691.80263884181 67.5729437964985 Geometric Mean 245446.240105035 Harmonic Mean 241369.309165968 Quadratic Mean 253342.212152522 Winsorized Mean ( 1 / 48 ) 249416.666666667 3683.12409092513 67.718779087896 Winsorized Mean ( 2 / 48 ) 249383.333333333 3671.94616204250 67.9158468910164 Winsorized Mean ( 3 / 48 ) 249375 3670.32233266249 67.9436238558102 Winsorized Mean ( 4 / 48 ) 249313.888888889 3662.58813895223 68.0704134427223 Winsorized Mean ( 5 / 48 ) 249345.138888889 3655.70740215888 68.2070831876857 Winsorized Mean ( 6 / 48 ) 249311.805555556 3632.59365887368 68.631900225487 Winsorized Mean ( 7 / 48 ) 249345.833333333 3623.33943357953 68.8165814724685 Winsorized Mean ( 8 / 48 ) 249295.833333333 3616.02637320865 68.9419289583674 Winsorized Mean ( 9 / 48 ) 249289.583333333 3613.75022307528 68.9836230909146 Winsorized Mean ( 10 / 48 ) 249289.583333333 3606.92789302957 69.1141022849634 Winsorized Mean ( 11 / 48 ) 249167.361111111 3589.05311778816 69.4242612003098 Winsorized Mean ( 12 / 48 ) 249350.694444444 3549.9741450036 70.2401438036929 Winsorized Mean ( 13 / 48 ) 249450 3531.36902780879 70.6383269592143 Winsorized Mean ( 14 / 48 ) 249537.5 3513.93342603013 71.0137244352734 Winsorized Mean ( 15 / 48 ) 249402.083333333 3493.87707693051 71.3826153129697 Winsorized Mean ( 16 / 48 ) 249290.972222222 3428.41205803785 72.7132468332574 Winsorized Mean ( 17 / 48 ) 249385.416666667 3417.30990146568 72.977114706426 Winsorized Mean ( 18 / 48 ) 249422.916666667 3396.16807218717 73.4424537788071 Winsorized Mean ( 19 / 48 ) 249515.277777778 3382.56925809143 73.7650166898766 Winsorized Mean ( 20 / 48 ) 249612.5 3365.29719472426 74.1724981648916 Winsorized Mean ( 21 / 48 ) 249831.25 3296.13693811288 75.795167097346 Winsorized Mean ( 22 / 48 ) 250029.861111111 3267.77193373383 76.5138651599292 Winsorized Mean ( 23 / 48 ) 250061.805555556 3243.82998634494 77.0884437865743 Winsorized Mean ( 24 / 48 ) 249995.138888889 3229.76221365313 77.4035741182703 Winsorized Mean ( 25 / 48 ) 249647.916666667 3193.94458639007 78.1628828910989 Winsorized Mean ( 26 / 48 ) 249449.305555556 3170.06044317941 78.689132282087 Winsorized Mean ( 27 / 48 ) 249674.305555556 3122.49584928394 79.9598518642744 Winsorized Mean ( 28 / 48 ) 249596.527777778 3110.71340557162 80.2377124587317 Winsorized Mean ( 29 / 48 ) 249757.638888889 3081.21778678385 81.0580933162742 Winsorized Mean ( 30 / 48 ) 249799.305555556 3017.45689796039 82.7847137516377 Winsorized Mean ( 31 / 48 ) 249842.361111111 2995.60325632901 83.4030209385213 Winsorized Mean ( 32 / 48 ) 249886.805555556 2937.5977635086 85.0650176343736 Winsorized Mean ( 33 / 48 ) 249863.888888889 2926.25739367268 85.3868458151218 Winsorized Mean ( 34 / 48 ) 249887.5 2919.15476209438 85.6026899446454 Winsorized Mean ( 35 / 48 ) 249911.805555556 2911.85292015926 85.8256966982682 Winsorized Mean ( 36 / 48 ) 249936.805555556 2884.56488825086 86.6462760375316 Winsorized Mean ( 37 / 48 ) 249988.194444444 2879.35736088826 86.8208294809661 Winsorized Mean ( 38 / 48 ) 250093.75 2853.09119882985 87.657117340859 Winsorized Mean ( 39 / 48 ) 250120.833333333 2839.71324675839 88.0796093122618 Winsorized Mean ( 40 / 48 ) 250370.833333333 2814.67182829033 88.9520514671906 Winsorized Mean ( 41 / 48 ) 250086.111111111 2759.61387453216 90.623588111039 Winsorized Mean ( 42 / 48 ) 250115.277777778 2745.34559134781 91.1052067783516 Winsorized Mean ( 43 / 48 ) 250145.138888889 2724.95497098249 91.7978981497438 Winsorized Mean ( 44 / 48 ) 249411.805555556 2650.21137546101 94.1101558407468 Winsorized Mean ( 45 / 48 ) 249411.805555556 2638.16158686294 94.5400034620827 Winsorized Mean ( 46 / 48 ) 250465.972222222 2527.74275846773 99.0868122886246 Winsorized Mean ( 47 / 48 ) 250172.222222222 2487.88096855906 100.556347101734 Winsorized Mean ( 48 / 48 ) 250938.888888889 2400.59827897938 104.531812376195 Trimmed Mean ( 1 / 48 ) 249421.126760563 3664.42110717779 68.0656287761258 Trimmed Mean ( 2 / 48 ) 249425.714285714 3643.76819109706 68.4526844751388 Trimmed Mean ( 3 / 48 ) 249447.826086957 3627.16781573079 68.7720664605363 Trimmed Mean ( 4 / 48 ) 249473.529411765 3609.31125109654 69.1194280725921 Trimmed Mean ( 5 / 48 ) 249516.417910448 3591.73123532127 69.4696795396856 Trimmed Mean ( 6 / 48 ) 249553.787878788 3573.81295396941 69.8284412455359 Trimmed Mean ( 7 / 48 ) 249598.461538462 3558.6549462367 70.1384273860025 Trimmed Mean ( 8 / 48 ) 249639.0625 3543.29420897379 70.4539470269675 Trimmed Mean ( 9 / 48 ) 249688.095238095 3527.17785603702 70.789766047872 Trimmed Mean ( 10 / 48 ) 249739.516129032 3509.3344893705 71.1643523538362 Trimmed Mean ( 11 / 48 ) 249792.622950820 3490.2180389094 71.569346145742 Trimmed Mean ( 12 / 48 ) 249860.833333333 3471.10285589193 71.9831257403432 Trimmed Mean ( 13 / 48 ) 249912.711864407 3454.57611187239 72.3425114315844 Trimmed Mean ( 14 / 48 ) 249956.896551724 3438.03756306768 72.7033640460558 Trimmed Mean ( 15 / 48 ) 249994.736842105 3421.20610406591 73.0721065138404 Trimmed Mean ( 16 / 48 ) 250045.535714286 3404.20473224832 73.4519676051158 Trimmed Mean ( 17 / 48 ) 250107.272727273 3391.85348645046 73.7376404158917 Trimmed Mean ( 18 / 48 ) 250163.888888889 3378.52170230224 74.0453698191191 Trimmed Mean ( 19 / 48 ) 250219.811320755 3365.07868747322 74.3577890918921 Trimmed Mean ( 20 / 48 ) 250271.153846154 3350.65192487256 74.6932714760196 Trimmed Mean ( 21 / 48 ) 250317.647058824 3335.44189136712 75.0478213116836 Trimmed Mean ( 22 / 48 ) 250351 3324.44344700331 75.3061389044441 Trimmed Mean ( 23 / 48 ) 250372.448979592 3313.86061357996 75.55310200845 Trimmed Mean ( 24 / 48 ) 250392.708333333 3303.19364496272 75.8032181114103 Trimmed Mean ( 25 / 48 ) 250418.085106383 3291.38937588905 76.0827895176461 Trimmed Mean ( 26 / 48 ) 250466.304347826 3280.30662524091 76.354540280036 Trimmed Mean ( 27 / 48 ) 250528.888888889 3268.77377751969 76.6430796195958 Trimmed Mean ( 28 / 48 ) 250580.681818182 3259.01284566338 76.8885222872374 Trimmed Mean ( 29 / 48 ) 250639.534883721 3247.60430657200 77.1767466795493 Trimmed Mean ( 30 / 48 ) 250691.666666667 3236.05672593765 77.4682546994068 Trimmed Mean ( 31 / 48 ) 250743.902439024 3227.57199926221 77.688089528705 Trimmed Mean ( 32 / 48 ) 250796.25 3218.28116900204 77.9286323443795 Trimmed Mean ( 33 / 48 ) 250848.717948718 3211.56840816531 78.1078545021625 Trimmed Mean ( 34 / 48 ) 250905.263157895 3202.96786425145 78.3352421228654 Trimmed Mean ( 35 / 48 ) 250963.513513514 3191.71953363015 78.6295634278606 Trimmed Mean ( 36 / 48 ) 251023.611111111 3177.38394786868 79.0032351235023 Trimmed Mean ( 37 / 48 ) 251085.714285714 3161.581152838 79.417766664103 Trimmed Mean ( 38 / 48 ) 251148.529411765 3141.54277585044 79.9443290546242 Trimmed Mean ( 39 / 48 ) 251209.090909091 3118.94035504599 80.5430890984085 Trimmed Mean ( 40 / 48 ) 251271.875 3091.6822846079 81.2735112695667 Trimmed Mean ( 41 / 48 ) 251324.193548387 3060.37579001628 82.1220042219227 Trimmed Mean ( 42 / 48 ) 251396.666666667 3027.89569735303 83.0268581861775 Trimmed Mean ( 43 / 48 ) 251472.413793103 2988.52391915923 84.1460267996954 Trimmed Mean ( 44 / 48 ) 251551.785714286 2941.60261015118 85.5152170610012 Trimmed Mean ( 45 / 48 ) 251681.481481481 2893.043385169 86.9954051749484 Trimmed Mean ( 46 / 48 ) 251821.153846154 2832.95934432436 88.88978740576 Trimmed Mean ( 47 / 48 ) 251906 2776.01742334119 90.743666765898 Trimmed Mean ( 48 / 48 ) 252016.666666667 2709.36014359606 93.0170421464058 Median 258200 Midrange 252650 Midmean - Weighted Average at Xnp 250427.397260274 Midmean - Weighted Average at X(n+1)p 251023.611111111 Midmean - Empirical Distribution Function 250427.397260274 Midmean - Empirical Distribution Function - Averaging 251023.611111111 Midmean - Empirical Distribution Function - Interpolation 251023.611111111 Midmean - Closest Observation 250427.397260274 Midmean - True Basic - Statistics Graphics Toolkit 251023.611111111 Midmean - MS Excel (old versions) 250963.513513514 Number of observations 144

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Mar/12/t126840958185b7jdvois3ik09/1nx6x1268409392.png (open in new window) http://www.freestatistics.org/blog/date/2010/Mar/12/t126840958185b7jdvois3ik09/1nx6x1268409392.ps (open in new window) http://www.freestatistics.org/blog/date/2010/Mar/12/t126840958185b7jdvois3ik09/2otk21268409392.png (open in new window) http://www.freestatistics.org/blog/date/2010/Mar/12/t126840958185b7jdvois3ik09/2otk21268409392.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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