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TIJDREEKS A - STAP 14

*Unverified author*

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 12:15:37 +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/t1280837832zjhzccssoh9wze1.htm/, Retrieved Tue, 03 Aug 2010 14:17:14 +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/t1280837832zjhzccssoh9wze1.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:

Lisa Bruggeman

Dataseries X:

» Textbox « » Textfile « » CSV «

95 94 93 91 111 110 95 85 86 86 87 89 93 96 99 92 109 110 97 88 93 93 89 89 91 97 99 85 101 105 88 80 87 84 87 87 85 96 102 93 111 117 101 88 98 89 93 93 95 105 109 94 113 125 106 95 109 100 94 94 94 103 103 80 106 117 99 95 116 118 100 100 105 121 131 108 136 149 131 137 164 169 154 160 166 186 197 166 191 207 187 191 222 230 210 224 234 251 258 227 254 281 261 264 286 293 276 292 299 319 329 293 318 346 327 329 353 355 332 346

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	151.35	7.47415387789656	20.2497837845686
Geometric Mean	134.353962885916
Harmonic Mean	122.454194052220
Quadratic Mean	171.914271271081
Winsorized Mean ( 1 / 40 )	151.333333333333	7.47035535636203	20.2578493410561
Winsorized Mean ( 2 / 40 )	151.283333333333	7.43908204305639	20.3362904801595
Winsorized Mean ( 3 / 40 )	151.308333333333	7.43719545037869	20.3448106672562
Winsorized Mean ( 4 / 40 )	150.841666666667	7.33743515123003	20.5578193957026
Winsorized Mean ( 5 / 40 )	150.716666666667	7.31166122181517	20.613190640861
Winsorized Mean ( 6 / 40 )	150.766666666667	7.30791111690774	20.6306103419690
Winsorized Mean ( 7 / 40 )	150.65	7.28408773791677	20.6820682864379
Winsorized Mean ( 8 / 40 )	150.183333333333	7.17212335421177	20.9398703725779
Winsorized Mean ( 9 / 40 )	150.108333333333	7.15731390072953	20.9727190137676
Winsorized Mean ( 10 / 40 )	148.525	6.85501066508925	21.6666329574655
Winsorized Mean ( 11 / 40 )	147.975	6.7546587564411	21.9071022438986
Winsorized Mean ( 12 / 40 )	148.075	6.74712473775984	21.9463854241953
Winsorized Mean ( 13 / 40 )	147.966666666667	6.72760246452144	21.9939670108305
Winsorized Mean ( 14 / 40 )	147.266666666667	6.60282527311617	22.3035837804572
Winsorized Mean ( 15 / 40 )	146.766666666667	6.48388147287166	22.6356183839469
Winsorized Mean ( 16 / 40 )	146.1	6.36875030066	22.9401363066251
Winsorized Mean ( 17 / 40 )	144.4	6.08249082842474	23.7402741858958
Winsorized Mean ( 18 / 40 )	143.95	6.00847732124271	23.9578169815289
Winsorized Mean ( 19 / 40 )	143.791666666667	5.90694525262878	24.3428135046071
Winsorized Mean ( 20 / 40 )	143.125	5.79922677280903	24.6800143548574
Winsorized Mean ( 21 / 40 )	142.775	5.7020250776364	25.0393497145374
Winsorized Mean ( 22 / 40 )	139.841666666667	5.20213266751078	26.8816032970533
Winsorized Mean ( 23 / 40 )	139.075	5.08623344512059	27.343416597093
Winsorized Mean ( 24 / 40 )	138.475	4.99649684702161	27.7144175688901
Winsorized Mean ( 25 / 40 )	137.85	4.90383217779842	28.110668351193
Winsorized Mean ( 26 / 40 )	137.416666666667	4.84002603375949	28.3917205626946
Winsorized Mean ( 27 / 40 )	134.716666666667	4.44956459855494	30.2763705712730
Winsorized Mean ( 28 / 40 )	134.016666666667	4.35045609723489	30.8051991955157
Winsorized Mean ( 29 / 40 )	131.841666666667	3.99511248730009	33.000739550081
Winsorized Mean ( 30 / 40 )	130.341666666667	3.79143764506727	34.3779006457468
Winsorized Mean ( 31 / 40 )	130.341666666667	3.79143764506727	34.3779006457468
Winsorized Mean ( 32 / 40 )	129.275	3.64881628670418	35.4292981181491
Winsorized Mean ( 33 / 40 )	129	3.61230390413076	35.7112810615091
Winsorized Mean ( 34 / 40 )	124.466666666667	2.96404535940726	41.9921598944616
Winsorized Mean ( 35 / 40 )	123.591666666667	2.85417027029562	43.3021351083814
Winsorized Mean ( 36 / 40 )	123.591666666667	2.85417027029562	43.3021351083814
Winsorized Mean ( 37 / 40 )	122.975	2.77739632068037	44.277080330356
Winsorized Mean ( 38 / 40 )	121.708333333333	2.62100425066032	46.4357634302466
Winsorized Mean ( 39 / 40 )	120.083333333333	2.35535575804706	50.9830979558265
Winsorized Mean ( 40 / 40 )	118.416666666667	2.15507294596439	54.9478693463322
Trimmed Mean ( 1 / 40 )	150.228813559322	7.37546086742694	20.3687357657600
Trimmed Mean ( 2 / 40 )	149.086206896552	7.26872878402818	20.5106300326054
Trimmed Mean ( 3 / 40 )	147.929824561404	7.16674035084046	20.6411586466999
Trimmed Mean ( 4 / 40 )	146.723214285714	7.05222987706502	20.8052228647398
Trimmed Mean ( 5 / 40 )	145.6	6.95521477097763	20.9339329976628
Trimmed Mean ( 6 / 40 )	144.462962962963	6.85209952495967	21.0830216982018
Trimmed Mean ( 7 / 40 )	143.273584905660	6.73558536106037	21.2711408475276
Trimmed Mean ( 8 / 40 )	142.057692307692	6.6080781311649	21.4975806108772
Trimmed Mean ( 9 / 40 )	140.862745098039	6.48514332216975	21.7208376284443
Trimmed Mean ( 10 / 40 )	139.63	6.34720418846763	21.9986620650548
Trimmed Mean ( 11 / 40 )	138.540816326531	6.24350145412052	22.1896026363697
Trimmed Mean ( 12 / 40 )	137.46875	6.14099599622552	22.3854159951404
Trimmed Mean ( 13 / 40 )	136.340425531915	6.02343386095907	22.6350000147933
Trimmed Mean ( 14 / 40 )	135.173913043478	5.89041526922109	22.9481126313447
Trimmed Mean ( 15 / 40 )	134.022222222222	5.75606888710976	23.2836376441487
Trimmed Mean ( 16 / 40 )	132.863636363636	5.61804967837218	23.6494235490871
Trimmed Mean ( 17 / 40 )	131.709302325581	5.47492396436829	24.056827671538
Trimmed Mean ( 18 / 40 )	130.642857142857	5.35186582702759	24.4107123319674
Trimmed Mean ( 19 / 40 )	129.560975609756	5.21838922820055	24.8277715486609
Trimmed Mean ( 20 / 40 )	128.4375	5.07518920736029	25.3069382740911
Trimmed Mean ( 21 / 40 )	127.307692307692	4.92231720744866	25.8633661632056
Trimmed Mean ( 22 / 40 )	126.144736842105	4.75489420796101	26.5294518290026
Trimmed Mean ( 23 / 40 )	125.135135135135	4.63524496250126	26.9964448799293
Trimmed Mean ( 24 / 40 )	124.125	4.50963745857965	27.5243855276770
Trimmed Mean ( 25 / 40 )	123.1	4.37232734099491	28.1543421613966
Trimmed Mean ( 26 / 40 )	122.058823529412	4.22105816413327	28.9166409898251
Trimmed Mean ( 27 / 40 )	120.984848484848	4.04712867937657	29.8939959832177
Trimmed Mean ( 28 / 40 )	120.03125	3.90556740067691	30.7333705159451
Trimmed Mean ( 29 / 40 )	119.064516129032	3.74877882233324	31.7608804818543
Trimmed Mean ( 30 / 40 )	118.183333333333	3.62044505697105	32.6433163529923
Trimmed Mean ( 31 / 40 )	117.344827586207	3.49890240538811	33.5376109392199
Trimmed Mean ( 32 / 40 )	116.446428571429	3.34478850717044	34.8142874569782
Trimmed Mean ( 33 / 40 )	115.555555555556	3.17954093380351	36.3434715769873
Trimmed Mean ( 34 / 40 )	114.615384615385	2.97426795512682	38.5356619997264
Trimmed Mean ( 35 / 40 )	113.92	2.86382646834900	39.7789465454850
Trimmed Mean ( 36 / 40 )	113.229166666667	2.74511810118980	41.247466408673
Trimmed Mean ( 37 / 40 )	112.478260869565	2.5873604198969	43.4722043379048
Trimmed Mean ( 38 / 40 )	111.704545454545	2.39705147134859	46.6008122018757
Trimmed Mean ( 39 / 40 )	110.952380952381	2.18695116053701	50.7338174507455
Trimmed Mean ( 40 / 40 )	110.25	1.98382885428076	55.5743504597684
Median	107
Midrange	217.5
Midmean - Weighted Average at Xnp	117.786885245902
Midmean - Weighted Average at X(n+1)p	117.786885245902
Midmean - Empirical Distribution Function	117.786885245902
Midmean - Empirical Distribution Function - Averaging	117.786885245902
Midmean - Empirical Distribution Function - Interpolation	117.786885245902
Midmean - Closest Observation	117.786885245902
Midmean - True Basic - Statistics Graphics Toolkit	117.786885245902
Midmean - MS Excel (old versions)	119.064516129032
Number of observations	120

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Aug/03/t1280837832zjhzccssoh9wze1/146kx1280837735.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Aug/03/t1280837832zjhzccssoh9wze1/146kx1280837735.ps (open in new window)

http://www.freestatistics.org/blog/date/2010/Aug/03/t1280837832zjhzccssoh9wze1/246kx1280837735.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Aug/03/t1280837832zjhzccssoh9wze1/246kx1280837735.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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