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Omzet product X

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

Title produced by software: Central Tendency

Date of computation: Tue, 03 Aug 2010 13:12:06 +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/Aug/03/t1280841148m33xtkedtyck67c.htm/, Retrieved Tue, 03 Aug 2010 15:12:30 +0200

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/Aug/03/t1280841148m33xtkedtyck67c.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:

Phiilppe De Vocht

Dataseries X:

» Textbox « » Textfile « » CSV «

73 72 71 69 89 88 73 63 64 64 65 67 69 71 70 72 88 83 76 70 75 71 75 81 87 90 80 85 105 104 98 94 107 112 121 118 120 122 109 112 132 127 116 113 123 125 137 127 123 128 114 120 143 135 119 117 132 139 158 141 139 150 142 149 166 150 139 140 158 169 186 177 175 187 176 185 204 188 171 171 182 185 200 192 185 195 190 195 213 194 171 171 186 182 193 185 172 185 179 182 193 173 155 164 188 186 200 185 173 190 190 193 195 178 163 165 188 182 200 177

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	139.075	4.11271790053874	33.8158374494351
Geometric Mean	130.848489987346
Harmonic Mean	121.984202980677
Quadratic Mean	146.132388607044
Winsorized Mean ( 1 / 40 )	139.008333333333	4.10077016462077	33.8981039543796
Winsorized Mean ( 2 / 40 )	138.941666666667	4.09215098652839	33.953211189927
Winsorized Mean ( 3 / 40 )	138.966666666667	4.08832685009895	33.9910852928267
Winsorized Mean ( 4 / 40 )	139.033333333333	4.07831138048005	34.090906839234
Winsorized Mean ( 5 / 40 )	138.908333333333	4.04082797616526	34.3762056075342
Winsorized Mean ( 6 / 40 )	138.908333333333	4.04082797616526	34.3762056075342
Winsorized Mean ( 7 / 40 )	138.966666666667	4.03239565922885	34.4625573506451
Winsorized Mean ( 8 / 40 )	138.9	4.02466833193405	34.5121606413842
Winsorized Mean ( 9 / 40 )	138.9	4.00536055371624	34.6785259746781
Winsorized Mean ( 10 / 40 )	138.9	4.00536055371624	34.6785259746781
Winsorized Mean ( 11 / 40 )	138.9	4.00536055371624	34.6785259746781
Winsorized Mean ( 12 / 40 )	138.9	3.97989344338869	34.9004318773251
Winsorized Mean ( 13 / 40 )	138.683333333333	3.95593698656125	35.0570127391957
Winsorized Mean ( 14 / 40 )	138.8	3.93948623816968	35.2330206551217
Winsorized Mean ( 15 / 40 )	138.8	3.93948623816968	35.2330206551217
Winsorized Mean ( 16 / 40 )	138.8	3.87351851141353	35.8330545190421
Winsorized Mean ( 17 / 40 )	138.8	3.87351851141353	35.8330545190421
Winsorized Mean ( 18 / 40 )	138.95	3.85284008890848	36.0643049785554
Winsorized Mean ( 19 / 40 )	139.425	3.75026913133217	37.1773318440411
Winsorized Mean ( 20 / 40 )	139.425	3.710471639821	37.5760856123202
Winsorized Mean ( 21 / 40 )	139.775	3.66452947327542	38.1426868085923
Winsorized Mean ( 22 / 40 )	140.141666666667	3.61717223679809	38.7434320215615
Winsorized Mean ( 23 / 40 )	140.333333333333	3.54805610828319	39.5521742189237
Winsorized Mean ( 24 / 40 )	140.533333333333	3.52289298399161	39.8914568145928
Winsorized Mean ( 25 / 40 )	140.533333333333	3.52289298399161	39.8914568145928
Winsorized Mean ( 26 / 40 )	140.75	3.49584086613572	40.2621301682946
Winsorized Mean ( 27 / 40 )	140.975	3.46794974302801	40.6508197771369
Winsorized Mean ( 28 / 40 )	141.908333333333	3.3542689016554	42.3067850234961
Winsorized Mean ( 29 / 40 )	142.15	3.16195986629787	44.9562948331897
Winsorized Mean ( 30 / 40 )	143.65	2.99026548571695	48.0392128010528
Winsorized Mean ( 31 / 40 )	143.908333333333	2.96161237771201	48.5912114685682
Winsorized Mean ( 32 / 40 )	144.441666666667	2.90326764213488	49.7514127083556
Winsorized Mean ( 33 / 40 )	144.166666666667	2.75526827513653	52.3240034255911
Winsorized Mean ( 34 / 40 )	144.733333333333	2.63521543916830	54.9227707086493
Winsorized Mean ( 35 / 40 )	144.441666666667	2.60442404890549	55.4601186113944
Winsorized Mean ( 36 / 40 )	144.741666666667	2.57317273105173	56.2502722495069
Winsorized Mean ( 37 / 40 )	144.741666666667	2.50893350162831	57.6905153415698
Winsorized Mean ( 38 / 40 )	145.058333333333	2.41114638033729	60.1615623656334
Winsorized Mean ( 39 / 40 )	144.733333333333	2.31096925514511	62.628844157533
Winsorized Mean ( 40 / 40 )	145.066666666667	2.27751564158531	63.6951351805822
Trimmed Mean ( 1 / 40 )	139.093220338983	4.08413237156572	34.0569814307119
Trimmed Mean ( 2 / 40 )	139.181034482759	4.06500033909116	34.2388740154143
Trimmed Mean ( 3 / 40 )	139.307017543860	4.04792220143708	34.4144503306915
Trimmed Mean ( 4 / 40 )	139.428571428571	4.02966625775937	34.6005258276893
Trimmed Mean ( 5 / 40 )	139.536363636364	4.01163190454573	34.7829429410634
Trimmed Mean ( 6 / 40 )	139.675925925926	4.00008282848874	34.9182584248378
Trimmed Mean ( 7 / 40 )	139.820754716981	3.98611239607064	35.0769724543671
Trimmed Mean ( 8 / 40 )	139.961538461538	3.97109428497830	35.2450806798971
Trimmed Mean ( 9 / 40 )	140.117647058824	3.95453913306349	35.4321053210258
Trimmed Mean ( 10 / 40 )	140.28	3.93803211892653	35.621852682664
Trimmed Mean ( 11 / 40 )	140.448979591837	3.91832570635003	35.8441309164844
Trimmed Mean ( 12 / 40 )	140.625	3.89501058485601	36.103881346756
Trimmed Mean ( 13 / 40 )	140.808510638298	3.87118943777963	36.3734487556002
Trimmed Mean ( 14 / 40 )	141.021739130435	3.84621289345813	36.6650892804954
Trimmed Mean ( 15 / 40 )	141.233333333333	3.8189373060206	36.9823649921347
Trimmed Mean ( 16 / 40 )	141.454545454545	3.78672918814293	37.3553371330251
Trimmed Mean ( 17 / 40 )	141.686046511628	3.75724604547168	37.7100793498449
Trimmed Mean ( 18 / 40 )	141.928571428571	3.72224036766073	38.1298780867738
Trimmed Mean ( 19 / 40 )	142.170731707317	3.683577856237	38.5958264643694
Trimmed Mean ( 20 / 40 )	142.3875	3.65101398045023	38.9994398165633
Trimmed Mean ( 21 / 40 )	142.615384615385	3.61690405293654	39.4302371663954
Trimmed Mean ( 22 / 40 )	142.828947368421	3.58189345977181	39.8752640112083
Trimmed Mean ( 23 / 40 )	143.027027027027	3.54585829665651	40.3363628946739
Trimmed Mean ( 24 / 40 )	143.222222222222	3.51100562429444	40.7923647946317
Trimmed Mean ( 25 / 40 )	143.414285714286	3.47183240244989	41.3079518507534
Trimmed Mean ( 26 / 40 )	143.617647058824	3.42408126214904	41.9434108198372
Trimmed Mean ( 27 / 40 )	143.818181818182	3.36988646311958	42.6774561671867
Trimmed Mean ( 28 / 40 )	144.015625	3.30805085961981	43.5348884014896
Trimmed Mean ( 29 / 40 )	144.161290322581	3.2497157300229	44.3612002707587
Trimmed Mean ( 30 / 40 )	144.3	3.20560067790963	45.0149642762423
Trimmed Mean ( 31 / 40 )	144.344827586207	3.17521707334764	45.4598297539461
Trimmed Mean ( 32 / 40 )	144.375	3.13987369462242	45.9811489383371
Trimmed Mean ( 33 / 40 )	144.370370370370	3.1027474014113	46.5298497404922
Trimmed Mean ( 34 / 40 )	144.384615384615	3.07659311956323	46.9300325956372
Trimmed Mean ( 35 / 40 )	144.36	3.05884598754337	47.1942688804475
Trimmed Mean ( 36 / 40 )	144.354166666667	3.0372232067992	47.5283365224893
Trimmed Mean ( 37 / 40 )	144.326086956522	3.01061798073401	47.9390237752231
Trimmed Mean ( 38 / 40 )	144.295454545455	2.98331858747091	48.3674305357311
Trimmed Mean ( 39 / 40 )	144.238095238095	2.96079875978527	48.7159401703329
Trimmed Mean ( 40 / 40 )	144.2	2.94461699220276	48.9707151666368
Median	140.5
Midrange	138
Midmean - Weighted Average at Xnp	144.161290322581
Midmean - Weighted Average at X(n+1)p	144.918032786885
Midmean - Empirical Distribution Function	144.161290322581
Midmean - Empirical Distribution Function - Averaging	144.918032786885
Midmean - Empirical Distribution Function - Interpolation	144.918032786885
Midmean - Closest Observation	144.161290322581
Midmean - True Basic - Statistics Graphics Toolkit	144.918032786885
Midmean - MS Excel (old versions)	144.161290322581
Number of observations	120

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Aug/03/t1280841148m33xtkedtyck67c/1x9vp1280841124.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Aug/03/t1280841148m33xtkedtyck67c/1x9vp1280841124.ps (open in new window)

http://www.freestatistics.org/blog/date/2010/Aug/03/t1280841148m33xtkedtyck67c/2x9vp1280841124.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Aug/03/t1280841148m33xtkedtyck67c/2x9vp1280841124.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')

This work is licensed under a Creative Commons Attribution-Noncommercial-Share Alike 3.0 License.

Software written by Ed van Stee & Patrick Wessa

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