Central Tendancy - Niet werkende werkzoekende Vlaams Gewest

*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: Fri, 17 Dec 2010 13:39:14 +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/Dec/17/t12925930552ex6q3y5b813hm2.htm/, Retrieved Fri, 17 Dec 2010 14:37:35 +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/Dec/17/t12925930552ex6q3y5b813hm2.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}, }

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Dataseries X:

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211868 229527 229139 198563 195722 202196 205816 212588 214320 220375 204442 206903 214126 226899 223532 195309 186005 188906 191563 189226 186413 178037 166827 169362 174330 187069 186530 158114 151001 159612 161914 164182 169701 171297 166444 173476 182516 202388 202300 168053 167302 172608 178106 185686 194581 194596 197922 208795 230580 240636 240048 211457 211142 214771 212610 219313 219277 231805 229245 241114 248624 265845 256446 219452 217142 221678 227184 230354 235243 237217 233575 244460 243324 260307 241476 203666 200237 204045 209465 213586 216234 213188 208679 217859 227247 243477 232571 191531 186029 189733 190420 194163 198770 195198 193111 195411 202108 215706 206348 166972 166070 169292 175041 177876 181140 179566 175335 184128 189917 194690 179612 150605 150569 153745 155511 159044 163095 159585 158644 166618 176512 200765 182698 153730 156145 161570 165688 173666 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 3 seconds R Server 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 Central Tendency - Ungrouped Data Measure Value S.E. Value/S.E. Arithmetic Mean 197420.674418605 2409.00617521001 81.9510869047043 Geometric Mean 195552.562514208 Harmonic Mean 193703.875252113 Quadratic Mean 199293.116951334 Winsorized Mean ( 1 / 43 ) 197378.023255814 2399.80243432088 82.2476135672685 Winsorized Mean ( 2 / 43 ) 197324.302325581 2386.94535829459 82.6681271273694 Winsorized Mean ( 3 / 43 ) 197205.860465116 2344.33152862447 84.1202952983473 Winsorized Mean ( 4 / 43 ) 197077.209302326 2322.91031112927 84.8406450985693 Winsorized Mean ( 5 / 43 ) 197107.558139535 2307.07370484066 85.4361773210657 Winsorized Mean ( 6 / 43 ) 197129.930232558 2301.82926703665 85.640552518624 Winsorized Mean ( 7 / 43 ) 197136.496124031 2271.71893864154 86.778559077346 Winsorized Mean ( 8 / 43 ) 197146.914728682 2263.91516014924 87.0822892125012 Winsorized Mean ( 9 / 43 ) 197141.472868217 2255.17718398948 87.4172877713616 Winsorized Mean ( 10 / 43 ) 197137.829457364 2242.82609965423 87.8970641048614 Winsorized Mean ( 11 / 43 ) 196898.728682171 2207.25103340908 89.2054078588705 Winsorized Mean ( 12 / 43 ) 196897.240310078 2157.72544814905 91.2522213977598 Winsorized Mean ( 13 / 43 ) 196763.813953488 2130.27573635618 92.3654203986058 Winsorized Mean ( 14 / 43 ) 196783.023255814 2099.43916737838 93.7312337092109 Winsorized Mean ( 15 / 43 ) 196820.348837209 2071.93201316003 94.9936327963903 Winsorized Mean ( 16 / 43 ) 196855.201550388 2029.34262684718 97.0044185472143 Winsorized Mean ( 17 / 43 ) 196875.759689922 2019.46067415516 97.489276324871 Winsorized Mean ( 18 / 43 ) 196812.550387597 1998.40085895979 98.4850209131925 Winsorized Mean ( 19 / 43 ) 196796.643410853 1990.05994666068 98.8898066819934 Winsorized Mean ( 20 / 43 ) 196812.612403101 1984.13495805403 99.1931580078242 Winsorized Mean ( 21 / 43 ) 196528.217054264 1942.70659178470 101.162068366546 Winsorized Mean ( 22 / 43 ) 196573.751937984 1934.70812062053 101.603828423967 Winsorized Mean ( 23 / 43 ) 196656.837209302 1912.69316311822 102.816719901219 Winsorized Mean ( 24 / 43 ) 196260.930232558 1810.20770877493 108.419011410231 Winsorized Mean ( 25 / 43 ) 195915.193798450 1767.00616148295 110.874086389167 Winsorized Mean ( 26 / 43 ) 195720.899224806 1729.39475524183 113.173061634177 Winsorized Mean ( 27 / 43 ) 195861.759689922 1669.12550484304 117.343937961298 Winsorized Mean ( 28 / 43 ) 196116.147286822 1633.42600259310 120.064298581927 Winsorized Mean ( 29 / 43 ) 196303.186046512 1610.75280409567 121.870460537067 Winsorized Mean ( 30 / 43 ) 196017.604651163 1569.54481657972 124.888185785173 Winsorized Mean ( 31 / 43 ) 196004.868217054 1533.21011186955 127.83953529895 Winsorized Mean ( 32 / 43 ) 195956 1489.68808162900 131.541631041123 Winsorized Mean ( 33 / 43 ) 195896.139534884 1467.13950214949 133.522503652773 Winsorized Mean ( 34 / 43 ) 195959.92248062 1407.54322485039 139.221246652265 Winsorized Mean ( 35 / 43 ) 196207.635658915 1355.23088791589 144.778013406002 Winsorized Mean ( 36 / 43 ) 196198.426356589 1344.84103957555 145.889678097950 Winsorized Mean ( 37 / 43 ) 196063.333333333 1326.69405089928 147.783381707663 Winsorized Mean ( 38 / 43 ) 196376.170542636 1269.58679488204 154.677231469536 Winsorized Mean ( 39 / 43 ) 196215.333333333 1250.15485805940 156.952822339079 Winsorized Mean ( 40 / 43 ) 196373.472868217 1232.41051557895 159.340958540885 Winsorized Mean ( 41 / 43 ) 196461.193798450 1176.55219578796 166.980431893951 Winsorized Mean ( 42 / 43 ) 196775.379844961 1117.71551545879 176.051398699776 Winsorized Mean ( 43 / 43 ) 196731.046511628 1100.91486520917 178.697783751198 Trimmed Mean ( 1 / 43 ) 197250.811023622 2357.60098464333 83.6659011887304 Trimmed Mean ( 2 / 43 ) 197119.528 2311.11711503964 85.2918818857082 Trimmed Mean ( 3 / 43 ) 197012.146341463 2267.31492377488 86.8922725624085 Trimmed Mean ( 4 / 43 ) 196943.305785124 2236.12800100821 88.0733597076409 Trimmed Mean ( 5 / 43 ) 196907.016806723 2208.34434076456 89.1649971301806 Trimmed Mean ( 6 / 43 ) 196862.794871795 2181.64902191877 90.2357771089379 Trimmed Mean ( 7 / 43 ) 196812.852173913 2153.17904069142 91.405706842991 Trimmed Mean ( 8 / 43 ) 196760.07079646 2127.56142230391 92.4814995862214 Trimmed Mean ( 9 / 43 ) 196703.873873874 2100.41044271476 93.6502075373593 Trimmed Mean ( 10 / 43 ) 196646.330275229 2071.57213609086 94.9261321144766 Trimmed Mean ( 11 / 43 ) 196587.074766355 2041.29620932269 96.3050212255003 Trimmed Mean ( 12 / 43 ) 196552.266666667 2012.84325474705 97.64906740906 Trimmed Mean ( 13 / 43 ) 196516.262135922 1988.01686295516 98.8504000131081 Trimmed Mean ( 14 / 43 ) 196491.940594059 1963.8112803213 100.056427296777 Trimmed Mean ( 15 / 43 ) 196464.848484848 1940.52136798995 101.243331676555 Trimmed Mean ( 16 / 43 ) 196433.329896907 1917.62464232200 102.435755966847 Trimmed Mean ( 17 / 43 ) 196397.526315789 1896.87899916643 103.537192621193 Trimmed Mean ( 18 / 43 ) 196358.505376344 1874.34066260662 104.761375183138 Trimmed Mean ( 19 / 43 ) 196322.747252747 1851.09258418159 106.057767682942 Trimmed Mean ( 20 / 43 ) 196286.595505618 1825.40487279448 107.530443481903 Trimmed Mean ( 21 / 43 ) 196247.597701149 1796.58374245884 109.233760198988 Trimmed Mean ( 22 / 43 ) 196227.317647059 1768.52702713800 110.955226940813 Trimmed Mean ( 23 / 43 ) 196202.843373494 1737.07608958771 112.950057023733 Trimmed Mean ( 24 / 43 ) 196171.407407407 1703.38730977189 115.165474277062 Trimmed Mean ( 25 / 43 ) 196165.316455696 1677.05925963261 116.969818048451 Trimmed Mean ( 26 / 43 ) 196182.077922078 1651.52116294739 118.788715714645 Trimmed Mean ( 27 / 43 ) 196212.586666667 1626.07385757963 120.666466502773 Trimmed Mean ( 28 / 43 ) 196235.547945205 1603.47970988111 122.381060849067 Trimmed Mean ( 29 / 43 ) 196243.295774648 1581.01891990842 124.124571378320 Trimmed Mean ( 30 / 43 ) 196239.434782609 1556.97514689445 126.038899961909 Trimmed Mean ( 31 / 43 ) 196253.671641791 1533.37910527735 127.987704388533 Trimmed Mean ( 32 / 43 ) 196269.6 1509.60450083534 130.013920792760 Trimmed Mean ( 33 / 43 ) 196289.666666667 1486.49767092076 132.048418579144 Trimmed Mean ( 34 / 43 ) 196314.885245902 1461.23506524472 134.348599972191 Trimmed Mean ( 35 / 43 ) 196337.711864407 1438.59790681524 136.478519073518 Trimmed Mean ( 36 / 43 ) 196346.122807018 1417.95749868925 138.471091685412 Trimmed Mean ( 37 / 43 ) 196355.745454545 1393.40596766316 140.917830130904 Trimmed Mean ( 38 / 43 ) 196374.981132075 1365.19809816581 143.843579474592 Trimmed Mean ( 39 / 43 ) 196374.901960784 1338.90784062613 146.667975197570 Trimmed Mean ( 40 / 43 ) 196385.673469388 1308.45306583759 150.08996394049 Trimmed Mean ( 41 / 43 ) 196386.510638298 1272.42745745268 154.340044682351 Trimmed Mean ( 42 / 43 ) 196381.288888889 1236.70690272787 158.793719397636 Trimmed Mean ( 43 / 43 ) 196353.139534884 1201.86770331872 163.373338839785 Median 195309 Midrange 208207 Midmean - Weighted Average at Xnp 195957.65625 Midmean - Weighted Average at X(n+1)p 196269.6 Midmean - Empirical Distribution Function 196269.6 Midmean - Empirical Distribution Function - Averaging 196269.6 Midmean - Empirical Distribution Function - Interpolation 196269.6 Midmean - Closest Observation 195937.181818182 Midmean - True Basic - Statistics Graphics Toolkit 196269.6 Midmean - MS Excel (old versions) 196269.6 Number of observations 129

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Dec/17/t12925930552ex6q3y5b813hm2/1lvis1292593150.png (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/17/t12925930552ex6q3y5b813hm2/1lvis1292593150.ps (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/17/t12925930552ex6q3y5b813hm2/2emzd1292593150.png (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/17/t12925930552ex6q3y5b813hm2/2emzd1292593150.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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