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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_centraltendency.wasp
Title produced by softwareCentral Tendency
Date of computationWed, 31 Aug 2016 10:01:47 +0100
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2016/Aug/31/t1472634120yeusx8pxgyea56t.htm/, Retrieved Sun, 05 May 2024 15:43:55 +0200
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=, Retrieved Sun, 05 May 2024 15:43:55 +0200
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact0

Tree of Dependent Computations

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
0.7923
-2.468
-2.996
3.119
0.04315
0.731
2.45
2.119
-1.429
-1.644
-3.065
-1.461
1.141
1.329
0.3396
0.8429
2.225
-1.924
0.4999
-0.6433

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 1 seconds \tabularnewline
R Server & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=&T=0

[TABLE]
[ROW][C]Summary of computational 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]1 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=&T=0

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

As an alternative you can also use a QR Code:  
QR Code


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

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net






Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean7.75000000000403e-050.4165504125754480.000186051910309903
Geometric MeanNaN
Harmonic Mean0.664815215020978
Quadratic Mean1.81570115496053
Winsorized Mean ( 1 / 6 )-0.02992250.403190031473912-0.0742143844445124
Winsorized Mean ( 2 / 6 )0.0003775000000000530.3766815171313230.00100217287770041
Winsorized Mean ( 3 / 6 )0.06607750000000010.345197689212760.191419299910996
Winsorized Mean ( 4 / 6 )-0.03592250.283079982943147-0.126898764181481
Winsorized Mean ( 5 / 6 )-0.03717250000000010.257959211317639-0.144102239304134
Winsorized Mean ( 6 / 6 )-0.11700250.234727632992923-0.498460698930694
Trimmed Mean ( 1 / 6 )-0.002913888888888860.391130734078279-0.00744991031133259
Trimmed Mean ( 2 / 6 )0.0308468750.364115865301050.0847171956500602
Trimmed Mean ( 3 / 6 )0.05261071428571430.3376885900516330.155796541060715
Trimmed Mean ( 4 / 6 )0.04512916666666670.3086687690012630.146205807645159
Trimmed Mean ( 5 / 6 )0.0856550.299231996436990.286249468706254
Trimmed Mean ( 6 / 6 )0.147068750.2841815612008680.517516862735678
Median0.41975
Midrange0.0270000000000001
Midmean - Weighted Average at Xnp-0.0715863636363636
Midmean - Weighted Average at X(n+1)p0.0856549999999999
Midmean - Empirical Distribution Function-0.0715863636363636
Midmean - Empirical Distribution Function - Averaging0.0856549999999999
Midmean - Empirical Distribution Function - Interpolation0.0856549999999999
Midmean - Closest Observation-0.0715863636363636
Midmean - True Basic - Statistics Graphics Toolkit0.0856549999999999
Midmean - MS Excel (old versions)0.0451291666666667
Number of observations20

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & 7.75000000000403e-05 & 0.416550412575448 & 0.000186051910309903 \tabularnewline
Geometric Mean & NaN &  &  \tabularnewline
Harmonic Mean & 0.664815215020978 &  &  \tabularnewline
Quadratic Mean & 1.81570115496053 &  &  \tabularnewline
Winsorized Mean ( 1 / 6 ) & -0.0299225 & 0.403190031473912 & -0.0742143844445124 \tabularnewline
Winsorized Mean ( 2 / 6 ) & 0.000377500000000053 & 0.376681517131323 & 0.00100217287770041 \tabularnewline
Winsorized Mean ( 3 / 6 ) & 0.0660775000000001 & 0.34519768921276 & 0.191419299910996 \tabularnewline
Winsorized Mean ( 4 / 6 ) & -0.0359225 & 0.283079982943147 & -0.126898764181481 \tabularnewline
Winsorized Mean ( 5 / 6 ) & -0.0371725000000001 & 0.257959211317639 & -0.144102239304134 \tabularnewline
Winsorized Mean ( 6 / 6 ) & -0.1170025 & 0.234727632992923 & -0.498460698930694 \tabularnewline
Trimmed Mean ( 1 / 6 ) & -0.00291388888888886 & 0.391130734078279 & -0.00744991031133259 \tabularnewline
Trimmed Mean ( 2 / 6 ) & 0.030846875 & 0.36411586530105 & 0.0847171956500602 \tabularnewline
Trimmed Mean ( 3 / 6 ) & 0.0526107142857143 & 0.337688590051633 & 0.155796541060715 \tabularnewline
Trimmed Mean ( 4 / 6 ) & 0.0451291666666667 & 0.308668769001263 & 0.146205807645159 \tabularnewline
Trimmed Mean ( 5 / 6 ) & 0.085655 & 0.29923199643699 & 0.286249468706254 \tabularnewline
Trimmed Mean ( 6 / 6 ) & 0.14706875 & 0.284181561200868 & 0.517516862735678 \tabularnewline
Median & 0.41975 &  &  \tabularnewline
Midrange & 0.0270000000000001 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & -0.0715863636363636 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & 0.0856549999999999 &  &  \tabularnewline
Midmean - Empirical Distribution Function & -0.0715863636363636 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & 0.0856549999999999 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & 0.0856549999999999 &  &  \tabularnewline
Midmean - Closest Observation & -0.0715863636363636 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & 0.0856549999999999 &  &  \tabularnewline
Midmean - MS Excel (old versions) & 0.0451291666666667 &  &  \tabularnewline
Number of observations & 20 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=&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]7.75000000000403e-05[/C][C]0.416550412575448[/C][C]0.000186051910309903[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]NaN[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]0.664815215020978[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]1.81570115496053[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 6 )[/C][C]-0.0299225[/C][C]0.403190031473912[/C][C]-0.0742143844445124[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 6 )[/C][C]0.000377500000000053[/C][C]0.376681517131323[/C][C]0.00100217287770041[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 6 )[/C][C]0.0660775000000001[/C][C]0.34519768921276[/C][C]0.191419299910996[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 6 )[/C][C]-0.0359225[/C][C]0.283079982943147[/C][C]-0.126898764181481[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 6 )[/C][C]-0.0371725000000001[/C][C]0.257959211317639[/C][C]-0.144102239304134[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 6 )[/C][C]-0.1170025[/C][C]0.234727632992923[/C][C]-0.498460698930694[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 6 )[/C][C]-0.00291388888888886[/C][C]0.391130734078279[/C][C]-0.00744991031133259[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 6 )[/C][C]0.030846875[/C][C]0.36411586530105[/C][C]0.0847171956500602[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 6 )[/C][C]0.0526107142857143[/C][C]0.337688590051633[/C][C]0.155796541060715[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 6 )[/C][C]0.0451291666666667[/C][C]0.308668769001263[/C][C]0.146205807645159[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 6 )[/C][C]0.085655[/C][C]0.29923199643699[/C][C]0.286249468706254[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 6 )[/C][C]0.14706875[/C][C]0.284181561200868[/C][C]0.517516862735678[/C][/ROW]
[ROW][C]Median[/C][C]0.41975[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]0.0270000000000001[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]-0.0715863636363636[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]0.0856549999999999[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]-0.0715863636363636[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]0.0856549999999999[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]0.0856549999999999[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]-0.0715863636363636[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]0.0856549999999999[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]0.0451291666666667[/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=&T=1

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

As an alternative you can also use a QR Code:  
QR Code


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

Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean7.75000000000403e-050.4165504125754480.000186051910309903
Geometric MeanNaN
Harmonic Mean0.664815215020978
Quadratic Mean1.81570115496053
Winsorized Mean ( 1 / 6 )-0.02992250.403190031473912-0.0742143844445124
Winsorized Mean ( 2 / 6 )0.0003775000000000530.3766815171313230.00100217287770041
Winsorized Mean ( 3 / 6 )0.06607750000000010.345197689212760.191419299910996
Winsorized Mean ( 4 / 6 )-0.03592250.283079982943147-0.126898764181481
Winsorized Mean ( 5 / 6 )-0.03717250000000010.257959211317639-0.144102239304134
Winsorized Mean ( 6 / 6 )-0.11700250.234727632992923-0.498460698930694
Trimmed Mean ( 1 / 6 )-0.002913888888888860.391130734078279-0.00744991031133259
Trimmed Mean ( 2 / 6 )0.0308468750.364115865301050.0847171956500602
Trimmed Mean ( 3 / 6 )0.05261071428571430.3376885900516330.155796541060715
Trimmed Mean ( 4 / 6 )0.04512916666666670.3086687690012630.146205807645159
Trimmed Mean ( 5 / 6 )0.0856550.299231996436990.286249468706254
Trimmed Mean ( 6 / 6 )0.147068750.2841815612008680.517516862735678
Median0.41975
Midrange0.0270000000000001
Midmean - Weighted Average at Xnp-0.0715863636363636
Midmean - Weighted Average at X(n+1)p0.0856549999999999
Midmean - Empirical Distribution Function-0.0715863636363636
Midmean - Empirical Distribution Function - Averaging0.0856549999999999
Midmean - Empirical Distribution Function - Interpolation0.0856549999999999
Midmean - Closest Observation-0.0715863636363636
Midmean - True Basic - Statistics Graphics Toolkit0.0856549999999999
Midmean - MS Excel (old versions)0.0451291666666667
Number of observations20


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = grey ; par2 = no ;
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')