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*Unverified author*
R Software Module: /rwasp_centraltendency.wasp (opens new window with default values)
Title produced by software: Central Tendency
Date of computation: Tue, 09 Mar 2010 05:31:02 -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/09/t1268138031wog9d7q4r2ys0se.htm/, Retrieved Tue, 09 Mar 2010 13:33:54 +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/09/t1268138031wog9d7q4r2ys0se.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 «
40801 49081 52431 59650 75428 78705 68870 70641 80074 76464 69976 92917 92559 73981 71107 96942 86270 69610 57768 80077 71454 70382 69881 84530 79322 80181 82137 88439 91575 82909 73282 94089 108112 95653 85273 105093 102275 99308 79687 93263 114918 103374 65124 104045 101183 95492 85035 90692 107486 98179 82551 106804 110898 89950 65184 95357 98280 92146 77874 100039 104777 102341 71316 88838 85457 70784 70522 88629 88452 98886 79601 108135 113835 101617 68698 79182 86003 84165 68550 90385 100368 99081 81288 103491 111695 82504 62237 78249 92341 84412 75102 90461 106451 98379 72615 98367 116949 95832 68060 83923 87653 78054 57566 78784 88916 84662 63442 77773 88102 87972 61790 95276 104418 95420 82141 104064 96287 78426 59111 76837 76615 65860 57703 68656 77955 65856 60947 69885 80550 73694 67538 76326 84727
 
Output produced by software:


Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135


Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean84133.77443609021321.9302307346363.6446406020497
Geometric Mean82688.6538048968
Harmonic Mean81150.6940789484
Quadratic Mean85493.6368361628
Winsorized Mean ( 1 / 44 )84180.75939849621305.0501613692764.5038496529308
Winsorized Mean ( 2 / 44 )84214.84962406021292.3560058044865.1638165070753
Winsorized Mean ( 3 / 44 )84282.40601503761264.1183650859466.6728752171144
Winsorized Mean ( 4 / 44 )84262.55639097751259.5704276740066.897852267445
Winsorized Mean ( 5 / 44 )84161.12781954891243.2668226401367.6935363245913
Winsorized Mean ( 6 / 44 )84220.67669172931233.5708152363568.273888820556
Winsorized Mean ( 7 / 44 )84216.09774436091224.4384509433868.779363862247
Winsorized Mean ( 8 / 44 )84253.0902255641206.9448635132569.8069089753733
Winsorized Mean ( 9 / 44 )84286.24812030071195.3367946640970.5125521916075
Winsorized Mean ( 10 / 44 )84217.75187969931176.5258562334071.5817263458356
Winsorized Mean ( 11 / 44 )84291.27819548871159.1749722280372.7166132939138
Winsorized Mean ( 12 / 44 )84410.64661654141134.7273709783474.3884820049452
Winsorized Mean ( 13 / 44 )84381.90977443611129.3770269780174.7154473296002
Winsorized Mean ( 14 / 44 )84450.64661654141120.1093254788975.3950035907748
Winsorized Mean ( 15 / 44 )84388.61654135341111.8458612382575.8995643940884
Winsorized Mean ( 16 / 44 )84576.40601503761085.2502387285977.9326306475838
Winsorized Mean ( 17 / 44 )84511.09022556391060.2840512626379.7060845392562
Winsorized Mean ( 18 / 44 )84568.47368421051051.420509494380.4325889789665
Winsorized Mean ( 19 / 44 )84489.61654135341037.7981952514681.4123756698973
Winsorized Mean ( 20 / 44 )84430.66917293231028.9625889883982.0541680295096
Winsorized Mean ( 21 / 44 )84329.14285714291010.1381437745083.4827824064116
Winsorized Mean ( 22 / 44 )84397.1278195489989.58061622805785.285752808338
Winsorized Mean ( 23 / 44 )84317.5789473684969.30824094379586.9873744860254
Winsorized Mean ( 24 / 44 )84277.3383458647964.44548109140587.3842430683516
Winsorized Mean ( 25 / 44 )84257.7894736842958.2622886314887.927690021085
Winsorized Mean ( 26 / 44 )84238.045112782937.9480565741689.8109916880259
Winsorized Mean ( 27 / 44 )84264.030075188934.49619551534690.1705437427907
Winsorized Mean ( 28 / 44 )84270.7669172932929.61682260747990.6510778074373
Winsorized Mean ( 29 / 44 )84279.92481203923.64699601852891.2468997087925
Winsorized Mean ( 30 / 44 )84073.7593984962884.27190399752395.0768185876137
Winsorized Mean ( 31 / 44 )83969.8045112782862.17892775797197.392550209543
Winsorized Mean ( 32 / 44 )83893.5338345865846.71378796342599.0813366065209
Winsorized Mean ( 33 / 44 )84137.1879699248810.395128018912103.822425704367
Winsorized Mean ( 34 / 44 )84266.5413533835787.766697382282106.968905430247
Winsorized Mean ( 35 / 44 )84356.015037594774.336529518084108.939733335445
Winsorized Mean ( 36 / 44 )84416.6466165414764.420086100049110.432271667823
Winsorized Mean ( 37 / 44 )84705.969924812730.288527450953115.989731100494
Winsorized Mean ( 38 / 44 )84459.969924812684.305909934227123.424288317092
Winsorized Mean ( 39 / 44 )84481.0827067669632.618221880623133.541968575652
Winsorized Mean ( 40 / 44 )84418.5263157895617.671324006357136.672244662795
Winsorized Mean ( 41 / 44 )84354.7142857143601.67995442095140.198644920614
Winsorized Mean ( 42 / 44 )84355.977443609587.768356851024143.519086150788
Winsorized Mean ( 43 / 44 )84595.5488721805552.424668329837153.134995089812
Winsorized Mean ( 44 / 44 )84440.060150376529.875440269587159.358320339239
Trimmed Mean ( 1 / 44 )84214.06106870231275.9045482237366.0034178778828
Trimmed Mean ( 2 / 44 )84248.39534883721243.8431982445067.7323278912817
Trimmed Mean ( 3 / 44 )84265.96062992131215.9297665369369.301667702336
Trimmed Mean ( 4 / 44 )84260.1281196.5939773818870.416640558696
Trimmed Mean ( 5 / 44 )84259.47154471541176.727391951171.6049206647659
Trimmed Mean ( 6 / 44 )84281.0909090911159.0678241907972.7145462500713
Trimmed Mean ( 7 / 44 )84292.34453781511141.7564996494773.8269014134746
Trimmed Mean ( 8 / 44 )84304.72649572651124.4428642792774.9746644973043
Trimmed Mean ( 9 / 44 )84312.19130434781108.4670442032976.0619738270591
Trimmed Mean ( 10 / 44 )84315.58407079651092.6887926949077.1634015416672
Trimmed Mean ( 11 / 44 )84327.30630630631078.100407391778.2184161402215
Trimmed Mean ( 12 / 44 )84331.30275229361064.4097727726279.2282304329314
Trimmed Mean ( 13 / 44 )84323.08411214951052.5304386586080.1146275822822
Trimmed Mean ( 14 / 44 )84317.35238095241039.9037698489081.0818797139312
Trimmed Mean ( 15 / 44 )84305.05825242721026.9020457195582.0964946012496
Trimmed Mean ( 16 / 44 )84297.72277227721013.3047208274883.1908911896105
Trimmed Mean ( 17 / 44 )84274.32323232321001.2204648625684.1715947584952
Trimmed Mean ( 18 / 44 )84255.2268041237990.52382371170485.061282512521
Trimmed Mean ( 19 / 44 )84230.8631578947979.3460078278186.007256357453
Trimmed Mean ( 20 / 44 )84211.3870967742968.17278801855586.979708724431
Trimmed Mean ( 21 / 44 )84195.3626373626956.39455364962688.034130177834
Trimmed Mean ( 22 / 44 )84185.8426966292945.04828363483389.0809963410914
Trimmed Mean ( 23 / 44 )84171.1609195402934.29490856783190.0905700626852
Trimmed Mean ( 24 / 44 )84161.2924.13552348684791.0701924783199
Trimmed Mean ( 25 / 44 )84153.4457831325912.84412931422992.1881875346588
Trimmed Mean ( 26 / 44 )84146.5925925926900.3841540872593.4563232933557
Trimmed Mean ( 27 / 44 )84140.670886076888.20515361668494.7311221326103
Trimmed Mean ( 28 / 44 )84132.7792207792874.31176890699296.2274353529022
Trimmed Mean ( 29 / 44 )84124.04858.57774778256897.9806898295064
Trimmed Mean ( 30 / 44 )84114.2465753425840.800883603183100.040625807715
Trimmed Mean ( 31 / 44 )84116.7746478873824.910050872857101.970844650130
Trimmed Mean ( 32 / 44 )84125.9130434783808.889849401698104.001692079215
Trimmed Mean ( 33 / 44 )84140.328358209791.800601697493106.264542080198
Trimmed Mean ( 34 / 44 )84140.5230769231776.300104324901108.386592515139
Trimmed Mean ( 35 / 44 )84132.6984126984760.693133824597110.600049706901
Trimmed Mean ( 36 / 44 )84118.7868852459743.614214905253113.121542325497
Trimmed Mean ( 37 / 44 )84100.1355932203724.205485149759116.127449070383
Trimmed Mean ( 38 / 44 )84061.9298245614705.509782032567119.150622663771
Trimmed Mean ( 39 / 44 )84036.6689.917002571839121.806825584429
Trimmed Mean ( 40 / 44 )84008678.578961589406123.799888819470
Trimmed Mean ( 41 / 44 )83981.2352941177666.490643970774126.005122583237
Trimmed Mean ( 42 / 44 )83956.5102040816653.63501845374128.445551162011
Trimmed Mean ( 43 / 44 )83929.5957446808639.38148351451131.266853840280
Trimmed Mean ( 44 / 44 )83883.8222222222626.976516958219133.791011231466
Median84165
Midrange78875
Midmean - Weighted Average at Xnp83965.893939394
Midmean - Weighted Average at X(n+1)p84140.328358209
Midmean - Empirical Distribution Function84140.328358209
Midmean - Empirical Distribution Function - Averaging84140.328358209
Midmean - Empirical Distribution Function - Interpolation84140.328358209
Midmean - Closest Observation83953.7647058823
Midmean - True Basic - Statistics Graphics Toolkit84140.328358209
Midmean - MS Excel (old versions)84140.328358209
Number of observations133
 
Charts produced by software:
http://www.freestatistics.org/blog/date/2010/Mar/09/t1268138031wog9d7q4r2ys0se/1mk511268137860.png (open in new window)
http://www.freestatistics.org/blog/date/2010/Mar/09/t1268138031wog9d7q4r2ys0se/1mk511268137860.ps (open in new window)


http://www.freestatistics.org/blog/date/2010/Mar/09/t1268138031wog9d7q4r2ys0se/2lmbp1268137860.png (open in new window)
http://www.freestatistics.org/blog/date/2010/Mar/09/t1268138031wog9d7q4r2ys0se/2lmbp1268137860.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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