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*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: Sat, 13 Dec 2008 07:48:04 -0700

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2008/Dec/13/t12291797278v5x0qao87ten1i.htm/, Retrieved Sat, 13 Dec 2008 15:48:49 +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/2008/Dec/13/t12291797278v5x0qao87ten1i.htm/},
    year = {2008},
}
@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 = {2008},
    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:

Dataseries X:

» Textbox « » Textfile « » CSV «

1593 1477.9 1733.7 1569.7 1843.7 1950.3 1657.5 1772.1 1568.3 1809.8 1646.7 1808.5 1763.9 1625.5 1538.8 1342.4 1645.1 1619.9 1338.1 1505.5 1529.1 1511.9 1656.7 1694.4 1662.3 1588.7 1483.3 1585.6 1658.9 1584.4 1470.6 1618.7 1407.6 1473.9 1515.3 1485.4 1496.1 1493.5 1298.4 1375.3 1507.9 1455.3 1363.3 1392.8 1348.8 1880.3 1669.2 1543.6 1701.2 1516.5 1466.8 1484.1 1577.2 1684.5 1414.7 1674.5 1598.7 1739.1 1674.6 1671.8 1802 1526.8 1580.9 1634.8 1610.3 1712 1678.8 1708.1 1680.6 2056 1624 2021.4 1861.1 1750.8 1767.5 1710.3 2151.5 2047.9 1915.4 1984.7 1896.5 2170.8 2139.9 2330.5 2121.8 2226.8 1857.9 2155.9 2341.7 2290.2 2006.5 2111.9 1731.3 1762.2 1863.2 1943.5 1975.2

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	1 seconds
R Server	'Gwilym Jenkins' @ 72.249.127.135

Central Tendency - Ungrouped Data
Measure	Value	S.E.	Value/S.E.
Arithmetic Mean	1706.35154639175	24.4866378682815	69.685007618055
Geometric Mean	1690.32657469611
Harmonic Mean	1675.10774399296
Quadratic Mean	1723.13573509065
Winsorized Mean ( 1 / 32 )	1706.64536082474	24.3879166155785	69.9791371163938
Winsorized Mean ( 2 / 32 )	1705.90309278350	24.158585379484	70.6127062486115
Winsorized Mean ( 3 / 32 )	1704.14020618557	23.6547082097676	72.0423262495322
Winsorized Mean ( 4 / 32 )	1702.42886597938	23.0516913136547	73.8526662887831
Winsorized Mean ( 5 / 32 )	1702.2793814433	22.7971973665828	74.6705550717643
Winsorized Mean ( 6 / 32 )	1703.08969072165	22.5824976933819	75.4163562350662
Winsorized Mean ( 7 / 32 )	1703.3206185567	22.2600545324604	76.519157492308
Winsorized Mean ( 8 / 32 )	1702.41340206186	21.8778691112489	77.814406577034
Winsorized Mean ( 9 / 32 )	1705.26185567010	21.2046998171863	80.4190519258374
Winsorized Mean ( 10 / 32 )	1700.68453608247	19.9480282283247	85.2557714785882
Winsorized Mean ( 11 / 32 )	1700.19690721649	19.7260398537318	86.190483230462
Winsorized Mean ( 12 / 32 )	1697.32680412371	19.0853167636704	88.9336459615192
Winsorized Mean ( 13 / 32 )	1695.86597938144	18.6703474728361	90.8320523680019
Winsorized Mean ( 14 / 32 )	1693.49896907216	18.0383120395073	93.883450145617
Winsorized Mean ( 15 / 32 )	1692.15360824742	17.7779105174520	95.182929770419
Winsorized Mean ( 16 / 32 )	1688.26082474227	17.0826104882296	98.8292056360783
Winsorized Mean ( 17 / 32 )	1688.48865979381	16.7186638764387	100.994234483856
Winsorized Mean ( 18 / 32 )	1683.75670103093	15.8479338704525	106.244556217526
Winsorized Mean ( 19 / 32 )	1681.89587628866	15.0653887569073	111.639726224624
Winsorized Mean ( 20 / 32 )	1679.05051546392	14.5156925041126	115.671402861986
Winsorized Mean ( 21 / 32 )	1676.21443298969	13.881918570864	120.748038135579
Winsorized Mean ( 22 / 32 )	1676.50927835052	13.7203983205315	122.191006353056
Winsorized Mean ( 23 / 32 )	1676.03505154639	13.5794803034555	123.424093860197
Winsorized Mean ( 24 / 32 )	1675.07010309278	12.7829488156293	131.039412521524
Winsorized Mean ( 25 / 32 )	1666.92577319588	11.5449859021565	144.385258442325
Winsorized Mean ( 26 / 32 )	1669.17731958763	11.1802758697993	149.296612983986
Winsorized Mean ( 27 / 32 )	1668.70412371134	10.7844773898416	154.732034144108
Winsorized Mean ( 28 / 32 )	1667.20309278350	8.8460810305849	188.467987916822
Winsorized Mean ( 29 / 32 )	1666.24639175258	8.62831191229638	193.113833701118
Winsorized Mean ( 30 / 32 )	1667.45257731959	8.2244353064469	202.743716156721
Winsorized Mean ( 31 / 32 )	1668.09175257732	8.02354362475405	207.899630212137
Winsorized Mean ( 32 / 32 )	1665.48556701031	7.43803526037347	223.914717893752
Trimmed Mean ( 1 / 32 )	1703.95789473684	23.6926859017378	71.919152678754
Trimmed Mean ( 2 / 32 )	1701.15483870968	22.8969542836045	74.2961189352508
Trimmed Mean ( 3 / 32 )	1698.62417582418	22.1257271751618	76.771450826305
Trimmed Mean ( 4 / 32 )	1696.6202247191	21.4624063911652	79.0507920592492
Trimmed Mean ( 5 / 32 )	1695.00114942529	20.9105589801535	81.0595810008732
Trimmed Mean ( 6 / 32 )	1693.34	20.3493453875814	83.2134875961854
Trimmed Mean ( 7 / 32 )	1693.34	19.7550018243348	85.7170257465676
Trimmed Mean ( 8 / 32 )	1689.40864197531	19.1408621138525	88.2618887240538
Trimmed Mean ( 9 / 32 )	1687.41265822785	18.5105591388678	91.1594644747752
Trimmed Mean ( 10 / 32 )	1684.91428571429	17.9084317172016	94.0849713878562
Trimmed Mean ( 11 / 32 )	1682.87466666667	17.4563328649832	96.404822231733
Trimmed Mean ( 12 / 32 )	1680.78219178082	16.9641941329873	99.0782219659051
Trimmed Mean ( 13 / 32 )	1678.89859154930	16.5026639509108	101.735004514628
Trimmed Mean ( 14 / 32 )	1678.89859154930	16.0293584512065	104.738976089397
Trimmed Mean ( 15 / 32 )	1675.36417910448	15.5785897652851	107.542736816770
Trimmed Mean ( 16 / 32 )	1673.69384615385	15.0840688815607	110.957716999014
Trimmed Mean ( 17 / 32 )	1672.29206349206	14.6160264747585	114.414958564838
Trimmed Mean ( 18 / 32 )	1670.77704918033	14.1109141562417	118.403175774497
Trimmed Mean ( 19 / 32 )	1669.59152542373	13.6579245462615	122.243428697279
Trimmed Mean ( 20 / 32 )	1668.48947368421	13.2435899007771	125.984682868072
Trimmed Mean ( 21 / 32 )	1667.55818181818	12.8334715172697	129.938199463348
Trimmed Mean ( 22 / 32 )	1666.80377358491	12.4417026524935	133.969105366045
Trimmed Mean ( 23 / 32 )	1665.96470588235	11.9783686812093	139.081101126549
Trimmed Mean ( 24 / 32 )	1665.09795918367	11.4185538275156	145.823891916264
Trimmed Mean ( 25 / 32 )	1665.09795918367	10.8731248596887	153.138861244655
Trimmed Mean ( 26 / 32 )	1664.00888888889	10.4482654411877	159.261735668512
Trimmed Mean ( 27 / 32 )	1663.56046511628	9.97187581115395	166.825228935916
Trimmed Mean ( 28 / 32 )	1663.56046511628	9.43595989202363	176.300078015647
Trimmed Mean ( 29 / 32 )	1662.74615384615	9.18942642267648	180.941233692567
Trimmed Mean ( 30 / 32 )	1662.42972972973	8.90025041391552	186.784601827666
Trimmed Mean ( 31 / 32 )	1662.42972972973	8.59674546866785	193.378963677442
Trimmed Mean ( 32 / 32 )	1661.38484848485	8.2179187086357	202.166133225314
Median	1662.3
Midrange	1820.05
Midmean - Weighted Average at Xnp	1661.37708333333
Midmean - Weighted Average at X(n+1)p	1665.09795918367
Midmean - Empirical Distribution Function	1665.09795918367
Midmean - Empirical Distribution Function - Averaging	1665.09795918367
Midmean - Empirical Distribution Function - Interpolation	1665.09795918367
Midmean - Closest Observation	1662.126
Midmean - True Basic - Statistics Graphics Toolkit	1665.09795918367
Midmean - MS Excel (old versions)	1665.09795918367
Number of observations	97

Charts produced by software:

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/13/t12291797278v5x0qao87ten1i/10aiw1229179682.png (open in new window)

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/13/t12291797278v5x0qao87ten1i/10aiw1229179682.ps (open in new window)

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/13/t12291797278v5x0qao87ten1i/2rp7r1229179682.png (open in new window)

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/13/t12291797278v5x0qao87ten1i/2rp7r1229179682.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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