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Centrummaten omzet product xc

*Unverified author*

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

Title produced by software: Central Tendency

Date of computation: Fri, 30 Jul 2010 11:59:49 +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/Jul/30/t1280491198r2c3wh297ivwsfn.htm/, Retrieved Fri, 30 Jul 2010 13:59:58 +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/Jul/30/t1280491198r2c3wh297ivwsfn.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:

Dataseries X:

» Textbox « » Textfile « » CSV «

56 55 54 52 72 71 56 46 47 47 48 50 44 38 33 33 52 54 39 22 31 31 38 42 41 31 36 34 51 47 31 19 30 33 36 40 32 25 28 29 55 55 40 38 44 41 49 59 61 47 43 39 66 68 63 68 67 59 68 78 82 70 62 68 94 102 100 104 103 93 110 114 120 102 95 103 122 139 135 135 137 130 148 148 145 128 131 133 146 163 151 157 152 149 172 167 160 150 160 165 171 179 171 176 170 169 194 196 188 174 186 191 197 206 197 204 201 190 213 213

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	96.6083333333333	5.35392073190742	18.0444086064971
Geometric Mean	78.827774696675
Harmonic Mean	63.8608783500262
Quadratic Mean	112.890396698154
Winsorized Mean ( 1 / 40 )	96.6333333333333	5.35093297099961	18.0591560120554
Winsorized Mean ( 2 / 40 )	96.5666666666667	5.32444199326864	18.1364858117996
Winsorized Mean ( 3 / 40 )	96.5916666666667	5.30756417876142	18.198869276642
Winsorized Mean ( 4 / 40 )	96.525	5.28715957509786	18.2564945560988
Winsorized Mean ( 5 / 40 )	96.4	5.25546800747479	18.3428002725716
Winsorized Mean ( 6 / 40 )	96.45	5.25019474095268	18.3707471358479
Winsorized Mean ( 7 / 40 )	96.3916666666667	5.24084229755693	18.3923997697089
Winsorized Mean ( 8 / 40 )	96.2583333333333	5.21970377892104	18.4413402388959
Winsorized Mean ( 9 / 40 )	96.0333333333333	5.18468350469768	18.5225063875781
Winsorized Mean ( 10 / 40 )	96.0333333333333	5.1631631746686	18.5997091481613
Winsorized Mean ( 11 / 40 )	95.9416666666667	5.12580246956996	18.7173944443310
Winsorized Mean ( 12 / 40 )	95.7416666666667	5.09582538861205	18.7882549666294
Winsorized Mean ( 13 / 40 )	94.9833333333333	4.98566549327479	19.0512848207440
Winsorized Mean ( 14 / 40 )	94.75	4.92447511741839	19.2406292530262
Winsorized Mean ( 15 / 40 )	94.75	4.86438278592004	19.4783190735429
Winsorized Mean ( 16 / 40 )	94.4833333333333	4.82813856838025	19.5693085430708
Winsorized Mean ( 17 / 40 )	94.625	4.78054915361029	19.7937510858013
Winsorized Mean ( 18 / 40 )	94.625	4.78054915361029	19.7937510858013
Winsorized Mean ( 19 / 40 )	94.4666666666667	4.75936248663393	19.8485967252892
Winsorized Mean ( 20 / 40 )	94.4666666666667	4.72065509230095	20.0113469041056
Winsorized Mean ( 21 / 40 )	94.1166666666667	4.67450597059136	20.1340349672845
Winsorized Mean ( 22 / 40 )	93.9333333333333	4.6086286951811	20.3820571250516
Winsorized Mean ( 23 / 40 )	93.55	4.55925583023043	20.5186994289092
Winsorized Mean ( 24 / 40 )	93.15	4.46340002418676	20.8697404434352
Winsorized Mean ( 25 / 40 )	93.15	4.46340002418676	20.8697404434352
Winsorized Mean ( 26 / 40 )	92.7166666666667	4.36100596375114	21.2603852040863
Winsorized Mean ( 27 / 40 )	91.8166666666667	4.20160672437262	21.8527512663329
Winsorized Mean ( 28 / 40 )	91.8166666666667	4.15089986081675	22.1197016900814
Winsorized Mean ( 29 / 40 )	91.575	4.12202974293984	22.2159969022175
Winsorized Mean ( 30 / 40 )	91.825	4.04423479585862	22.7051604654682
Winsorized Mean ( 31 / 40 )	91.825	3.98910741158677	23.0189339432889
Winsorized Mean ( 32 / 40 )	91.825	3.98910741158677	23.0189339432889
Winsorized Mean ( 33 / 40 )	91.275	3.92433623890288	23.2587103763356
Winsorized Mean ( 34 / 40 )	90.9916666666667	3.8912113829857	23.3838919840046
Winsorized Mean ( 35 / 40 )	89.5333333333333	3.66199600662913	24.4493257696774
Winsorized Mean ( 36 / 40 )	89.2333333333333	3.56564555136175	25.0258563415689
Winsorized Mean ( 37 / 40 )	88.925	3.46733784374830	25.6464769247491
Winsorized Mean ( 38 / 40 )	89.2416666666667	3.43759890783773	25.9604651558376
Winsorized Mean ( 39 / 40 )	88.9166666666667	3.33482984614024	26.663029530451
Winsorized Mean ( 40 / 40 )	88.25	3.26107786652521	27.0616046632561
Trimmed Mean ( 1 / 40 )	96.2796610169491	5.31320743045816	18.1208172797889
Trimmed Mean ( 2 / 40 )	95.9137931034483	5.27070158491533	18.1975381376081
Trimmed Mean ( 3 / 40 )	95.5701754385965	5.2379191600771	18.2458286426073
Trimmed Mean ( 4 / 40 )	95.2053571428571	5.20718025938004	18.2834763538976
Trimmed Mean ( 5 / 40 )	94.8454545454545	5.17822776274938	18.3161998450019
Trimmed Mean ( 6 / 40 )	94.5	5.15296478123914	18.3389570881708
Trimmed Mean ( 7 / 40 )	94.1320754716981	5.12462959407757	18.3685618138108
Trimmed Mean ( 8 / 40 )	93.7596153846154	5.0935698600687	18.4074466357375
Trimmed Mean ( 9 / 40 )	93.3921568627451	5.06141963457753	18.4517711641075
Trimmed Mean ( 10 / 40 )	93.04	5.03004950073038	18.4968358634423
Trimmed Mean ( 11 / 40 )	92.6734693877551	4.99677521739318	18.5466556640711
Trimmed Mean ( 12 / 40 )	92.3020833333333	4.96348773350239	18.5962146557381
Trimmed Mean ( 13 / 40 )	91.936170212766	4.92884182135985	18.6526923656481
Trimmed Mean ( 14 / 40 )	91.6304347826087	4.90365166620494	18.6861630923152
Trimmed Mean ( 15 / 40 )	91.3333333333333	4.8814152385948	18.71042082452
Trimmed Mean ( 16 / 40 )	91.0227272727273	4.86172373744637	18.7223158263075
Trimmed Mean ( 17 / 40 )	90.7209302325581	4.84178266914824	18.7370926024067
Trimmed Mean ( 18 / 40 )	90.3928571428571	4.82234644160415	18.7445796849029
Trimmed Mean ( 19 / 40 )	90.0487804878049	4.79764892860066	18.7693559549530
Trimmed Mean ( 20 / 40 )	89.7	4.76954340621799	18.8068316734594
Trimmed Mean ( 21 / 40 )	89.3333333333333	4.73931371203621	18.8494239379971
Trimmed Mean ( 22 / 40 )	88.9736842105263	4.70770080896615	18.8996046734894
Trimmed Mean ( 23 / 40 )	88.6081081081081	4.67645593599217	18.9477051256143
Trimmed Mean ( 24 / 40 )	88.25	4.64362815830612	19.0045363219159
Trimmed Mean ( 25 / 40 )	87.9	4.61436904205924	19.0491916010197
Trimmed Mean ( 26 / 40 )	87.5294117647059	4.57679907910138	19.1245912813572
Trimmed Mean ( 27 / 40 )	87.1666666666667	4.54265376027088	19.1884900911904
Trimmed Mean ( 28 / 40 )	86.84375	4.51975484996364	19.2142611453138
Trimmed Mean ( 29 / 40 )	86.5	4.49476750845361	19.2445993785694
Trimmed Mean ( 30 / 40 )	86.15	4.46460182900171	19.2962336395546
Trimmed Mean ( 31 / 40 )	85.7586206896552	4.43377773051357	19.3421109270901
Trimmed Mean ( 32 / 40 )	85.3392857142857	4.39910533892192	19.3992366946138
Trimmed Mean ( 33 / 40 )	84.8888888888889	4.35165186807253	19.5072794107697
Trimmed Mean ( 34 / 40 )	84.4423076923077	4.29918206306928	19.6414821362607
Trimmed Mean ( 35 / 40 )	83.98	4.23479175692144	19.8309633201541
Trimmed Mean ( 36 / 40 )	83.5833333333333	4.19005845239841	19.9480112945655
Trimmed Mean ( 37 / 40 )	83.1739130434783	4.14417749370715	20.0700653313658
Trimmed Mean ( 38 / 40 )	82.75	4.09688751554281	20.1982601880238
Trimmed Mean ( 39 / 40 )	82.2619047619048	4.03297377820805	20.3973319158191
Trimmed Mean ( 40 / 40 )	81.75	3.96357615007406	20.6253133293459
Median	70.5
Midrange	116
Midmean - Weighted Average at Xnp	84.7903225806452
Midmean - Weighted Average at X(n+1)p	86.15
Midmean - Empirical Distribution Function	84.7903225806452
Midmean - Empirical Distribution Function - Averaging	86.15
Midmean - Empirical Distribution Function - Interpolation	86.15
Midmean - Closest Observation	84.7903225806452
Midmean - True Basic - Statistics Graphics Toolkit	86.15
Midmean - MS Excel (old versions)	85.8253968253968
Number of observations	120

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Jul/30/t1280491198r2c3wh297ivwsfn/19ult1280491185.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Jul/30/t1280491198r2c3wh297ivwsfn/19ult1280491185.ps (open in new window)

http://www.freestatistics.org/blog/date/2010/Jul/30/t1280491198r2c3wh297ivwsfn/223ke1280491185.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Jul/30/t1280491198r2c3wh297ivwsfn/223ke1280491185.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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