Free Statistics

of Irreproducible Research!

Author's title

Author*Unverified author*
R Software Modulerwasp_centraltendency.wasp
Title produced by softwareCentral Tendency
Date of computationWed, 17 Oct 2007 11:13:29 -0700
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2007/Oct/17/vfkkce2b4rrw9u91192644721.htm/, Retrieved Sat, 04 May 2024 02:12:48 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=877, Retrieved Sat, 04 May 2024 02:12:48 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsDescriptive statistics, Central Tendency, voorbeeld theorie 20
Estimated Impact267
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Central Tendency] [Descriptive stati...] [2007-10-17 18:13:29] [181c187d2008ac66a37ecc12859b08c5] [Current]
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Dataseries X:
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20




Summary of compuational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time5 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135

\begin{tabular}{lllllllll}
\hline
Summary of compuational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 5 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=877&T=0

[TABLE]
[ROW][C]Summary of compuational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]5 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=877&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=877&T=0

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Summary of compuational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time5 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean10.51.322875655532307.93725393319377
Geometric Mean8.30436120373934
Harmonic Mean5.55904593048803
Quadratic Mean11.9791485507109
Winsorized Mean ( 1 / 6 )10.51.286570308181698.16123295651026
Winsorized Mean ( 2 / 6 )10.51.21936135138988.61106511866425
Winsorized Mean ( 3 / 6 )10.51.125073097040469.33272693802792
Winsorized Mean ( 4 / 6 )10.51.0065574473108010.4315953630392
Winsorized Mean ( 5 / 6 )10.50.86602540378443912.1243556529821
Winsorized Mean ( 6 / 6 )10.50.70524351897244114.8884742894182
Trimmed Mean ( 1 / 6 )10.51.258305739211798.34455384950978
Trimmed Mean ( 2 / 6 )10.51.190238071423818.82176452937646
Trimmed Mean ( 3 / 6 )10.51.118033988749899.39148550549912
Trimmed Mean ( 4 / 6 )10.51.0408329997330710.0880736897205
Trimmed Mean ( 5 / 6 )10.50.95742710775633810.9668923252090
Trimmed Mean ( 6 / 6 )10.50.86602540378443812.1243556529821
Median10.5
Midrange10.5
Midmean - Weighted Average at Xnp10
Midmean - Weighted Average at X(n+1)p10.5
Midmean - Empirical Distribution Function10
Midmean - Empirical Distribution Function - Averaging10.5
Midmean - Empirical Distribution Function - Interpolation10.5
Midmean - Closest Observation10
Midmean - True Basic - Statistics Graphics Toolkit10.5
Midmean - MS Excel (old versions)10.5
Number of observations20

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & 10.5 & 1.32287565553230 & 7.93725393319377 \tabularnewline
Geometric Mean & 8.30436120373934 &  &  \tabularnewline
Harmonic Mean & 5.55904593048803 &  &  \tabularnewline
Quadratic Mean & 11.9791485507109 &  &  \tabularnewline
Winsorized Mean ( 1 / 6 ) & 10.5 & 1.28657030818169 & 8.16123295651026 \tabularnewline
Winsorized Mean ( 2 / 6 ) & 10.5 & 1.2193613513898 & 8.61106511866425 \tabularnewline
Winsorized Mean ( 3 / 6 ) & 10.5 & 1.12507309704046 & 9.33272693802792 \tabularnewline
Winsorized Mean ( 4 / 6 ) & 10.5 & 1.00655744731080 & 10.4315953630392 \tabularnewline
Winsorized Mean ( 5 / 6 ) & 10.5 & 0.866025403784439 & 12.1243556529821 \tabularnewline
Winsorized Mean ( 6 / 6 ) & 10.5 & 0.705243518972441 & 14.8884742894182 \tabularnewline
Trimmed Mean ( 1 / 6 ) & 10.5 & 1.25830573921179 & 8.34455384950978 \tabularnewline
Trimmed Mean ( 2 / 6 ) & 10.5 & 1.19023807142381 & 8.82176452937646 \tabularnewline
Trimmed Mean ( 3 / 6 ) & 10.5 & 1.11803398874989 & 9.39148550549912 \tabularnewline
Trimmed Mean ( 4 / 6 ) & 10.5 & 1.04083299973307 & 10.0880736897205 \tabularnewline
Trimmed Mean ( 5 / 6 ) & 10.5 & 0.957427107756338 & 10.9668923252090 \tabularnewline
Trimmed Mean ( 6 / 6 ) & 10.5 & 0.866025403784438 & 12.1243556529821 \tabularnewline
Median & 10.5 &  &  \tabularnewline
Midrange & 10.5 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & 10 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & 10.5 &  &  \tabularnewline
Midmean - Empirical Distribution Function & 10 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & 10.5 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & 10.5 &  &  \tabularnewline
Midmean - Closest Observation & 10 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & 10.5 &  &  \tabularnewline
Midmean - MS Excel (old versions) & 10.5 &  &  \tabularnewline
Number of observations & 20 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=877&T=1

[TABLE]
[ROW][C]Central Tendency - Ungrouped Data[/C][/ROW]
[ROW][C]Measure[/C][C]Value[/C][C]S.E.[/C][C]Value/S.E.[/C][/ROW]
[ROW][C]Arithmetic Mean[/C][C]10.5[/C][C]1.32287565553230[/C][C]7.93725393319377[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]8.30436120373934[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]5.55904593048803[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]11.9791485507109[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 6 )[/C][C]10.5[/C][C]1.28657030818169[/C][C]8.16123295651026[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 6 )[/C][C]10.5[/C][C]1.2193613513898[/C][C]8.61106511866425[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 6 )[/C][C]10.5[/C][C]1.12507309704046[/C][C]9.33272693802792[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 6 )[/C][C]10.5[/C][C]1.00655744731080[/C][C]10.4315953630392[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 6 )[/C][C]10.5[/C][C]0.866025403784439[/C][C]12.1243556529821[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 6 )[/C][C]10.5[/C][C]0.705243518972441[/C][C]14.8884742894182[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 6 )[/C][C]10.5[/C][C]1.25830573921179[/C][C]8.34455384950978[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 6 )[/C][C]10.5[/C][C]1.19023807142381[/C][C]8.82176452937646[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 6 )[/C][C]10.5[/C][C]1.11803398874989[/C][C]9.39148550549912[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 6 )[/C][C]10.5[/C][C]1.04083299973307[/C][C]10.0880736897205[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 6 )[/C][C]10.5[/C][C]0.957427107756338[/C][C]10.9668923252090[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 6 )[/C][C]10.5[/C][C]0.866025403784438[/C][C]12.1243556529821[/C][/ROW]
[ROW][C]Median[/C][C]10.5[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]10.5[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]10[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]10.5[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]10[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]10.5[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]10.5[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]10[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]10.5[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]10.5[/C][C][/C][C][/C][/ROW]
[ROW][C]Number of observations[/C][C]20[/C][C][/C][C][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=877&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=877&T=1

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean10.51.322875655532307.93725393319377
Geometric Mean8.30436120373934
Harmonic Mean5.55904593048803
Quadratic Mean11.9791485507109
Winsorized Mean ( 1 / 6 )10.51.286570308181698.16123295651026
Winsorized Mean ( 2 / 6 )10.51.21936135138988.61106511866425
Winsorized Mean ( 3 / 6 )10.51.125073097040469.33272693802792
Winsorized Mean ( 4 / 6 )10.51.0065574473108010.4315953630392
Winsorized Mean ( 5 / 6 )10.50.86602540378443912.1243556529821
Winsorized Mean ( 6 / 6 )10.50.70524351897244114.8884742894182
Trimmed Mean ( 1 / 6 )10.51.258305739211798.34455384950978
Trimmed Mean ( 2 / 6 )10.51.190238071423818.82176452937646
Trimmed Mean ( 3 / 6 )10.51.118033988749899.39148550549912
Trimmed Mean ( 4 / 6 )10.51.0408329997330710.0880736897205
Trimmed Mean ( 5 / 6 )10.50.95742710775633810.9668923252090
Trimmed Mean ( 6 / 6 )10.50.86602540378443812.1243556529821
Median10.5
Midrange10.5
Midmean - Weighted Average at Xnp10
Midmean - Weighted Average at X(n+1)p10.5
Midmean - Empirical Distribution Function10
Midmean - Empirical Distribution Function - Averaging10.5
Midmean - Empirical Distribution Function - Interpolation10.5
Midmean - Closest Observation10
Midmean - True Basic - Statistics Graphics Toolkit10.5
Midmean - MS Excel (old versions)10.5
Number of observations20



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('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('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('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('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('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('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('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('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('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('midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('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('midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('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('midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('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('midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('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('midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('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('midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('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('midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('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('midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('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')