FreeStatistics.org

Free Statistics

of Irreproducible Research!

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 computationThu, 31 Jan 2019 10:47:52 +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/2019/Jan/31/t15489280787zx1s0epwkn7k7f.htm/, Retrieved Sun, 05 May 2024 20:05:15 +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 20:05:15 +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 Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R ServerBig Analytics Cloud Computing Center

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input view raw input (R code)  \tabularnewline
Raw Outputview raw output of R engine  \tabularnewline
Computing time1 seconds \tabularnewline
R ServerBig Analytics Cloud Computing Center \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=&T=0

[TABLE]
[ROW]
Summary of computational transaction[/C][/ROW] [ROW]Raw Input[/C] view raw input (R code) [/C][/ROW] [ROW]Raw Output[/C]view raw output of R engine [/C][/ROW] [ROW]Computing time[/C]1 seconds[/C][/ROW] [ROW]R Server[/C]Big Analytics Cloud Computing Center[/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 Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R ServerBig Analytics Cloud Computing Center






Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean7.75e-050.416550.000186052
Geometric MeanNaN
Harmonic Mean0.664815
Quadratic Mean1.8157
Winsorized Mean ( 1 / 6 )-0.02992250.40319-0.0742144
Winsorized Mean ( 2 / 6 )0.00037750.3766820.00100217
Winsorized Mean ( 3 / 6 )0.06607750.3451980.191419
Winsorized Mean ( 4 / 6 )-0.03592250.28308-0.126899
Winsorized Mean ( 5 / 6 )-0.03717250.257959-0.144102
Winsorized Mean ( 6 / 6 )-0.1170030.234728-0.498461
Trimmed Mean ( 1 / 6 )-0.002913890.391131-0.00744991
Trimmed Mean ( 2 / 6 )0.03084690.3641160.0847172
Trimmed Mean ( 3 / 6 )0.05261070.3376890.155797
Trimmed Mean ( 4 / 6 )0.04512920.3086690.146206
Trimmed Mean ( 5 / 6 )0.0856550.2992320.286249
Trimmed Mean ( 6 / 6 )0.1470690.2841820.517517
Median0.41975
Midrange0.027
Midmean - Weighted Average at Xnp-0.0715864
Midmean - Weighted Average at X(n+1)p0.085655
Midmean - Empirical Distribution Function-0.0715864
Midmean - Empirical Distribution Function - Averaging0.085655
Midmean - Empirical Distribution Function - Interpolation0.085655
Midmean - Closest Observation-0.0715864
Midmean - True Basic - Statistics Graphics Toolkit0.085655
Midmean - MS Excel (old versions)0.0451292
Number of observations20

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & 7.75e-05 & 0.41655 & 0.000186052 \tabularnewline
Geometric Mean & NaN &  &  \tabularnewline
Harmonic Mean & 0.664815 &  &  \tabularnewline
Quadratic Mean & 1.8157 &  &  \tabularnewline
Winsorized Mean ( 1 / 6 ) & -0.0299225 & 0.40319 & -0.0742144 \tabularnewline
Winsorized Mean ( 2 / 6 ) & 0.0003775 & 0.376682 & 0.00100217 \tabularnewline
Winsorized Mean ( 3 / 6 ) & 0.0660775 & 0.345198 & 0.191419 \tabularnewline
Winsorized Mean ( 4 / 6 ) & -0.0359225 & 0.28308 & -0.126899 \tabularnewline
Winsorized Mean ( 5 / 6 ) & -0.0371725 & 0.257959 & -0.144102 \tabularnewline
Winsorized Mean ( 6 / 6 ) & -0.117003 & 0.234728 & -0.498461 \tabularnewline
Trimmed Mean ( 1 / 6 ) & -0.00291389 & 0.391131 & -0.00744991 \tabularnewline
Trimmed Mean ( 2 / 6 ) & 0.0308469 & 0.364116 & 0.0847172 \tabularnewline
Trimmed Mean ( 3 / 6 ) & 0.0526107 & 0.337689 & 0.155797 \tabularnewline
Trimmed Mean ( 4 / 6 ) & 0.0451292 & 0.308669 & 0.146206 \tabularnewline
Trimmed Mean ( 5 / 6 ) & 0.085655 & 0.299232 & 0.286249 \tabularnewline
Trimmed Mean ( 6 / 6 ) & 0.147069 & 0.284182 & 0.517517 \tabularnewline
Median & 0.41975 &  &  \tabularnewline
Midrange & 0.027 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & -0.0715864 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & 0.085655 &  &  \tabularnewline
Midmean - Empirical Distribution Function & -0.0715864 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & 0.085655 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & 0.085655 &  &  \tabularnewline
Midmean - Closest Observation & -0.0715864 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & 0.085655 &  &  \tabularnewline
Midmean - MS Excel (old versions) & 0.0451292 &  &  \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]7.75e-05[/C][C]0.41655[/C][C]0.000186052[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]NaN[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]0.664815[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]1.8157[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 6 )[/C][C]-0.0299225[/C][C]0.40319[/C][C]-0.0742144[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 6 )[/C][C]0.0003775[/C][C]0.376682[/C][C]0.00100217[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 6 )[/C][C]0.0660775[/C][C]0.345198[/C][C]0.191419[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 6 )[/C][C]-0.0359225[/C][C]0.28308[/C][C]-0.126899[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 6 )[/C][C]-0.0371725[/C][C]0.257959[/C][C]-0.144102[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 6 )[/C][C]-0.117003[/C][C]0.234728[/C][C]-0.498461[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 6 )[/C][C]-0.00291389[/C][C]0.391131[/C][C]-0.00744991[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 6 )[/C][C]0.0308469[/C][C]0.364116[/C][C]0.0847172[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 6 )[/C][C]0.0526107[/C][C]0.337689[/C][C]0.155797[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 6 )[/C][C]0.0451292[/C][C]0.308669[/C][C]0.146206[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 6 )[/C][C]0.085655[/C][C]0.299232[/C][C]0.286249[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 6 )[/C][C]0.147069[/C][C]0.284182[/C][C]0.517517[/C][/ROW]
[ROW][C]Median[/C][C]0.41975[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]0.027[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]-0.0715864[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]0.085655[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]-0.0715864[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]0.085655[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]0.085655[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]-0.0715864[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]0.085655[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]0.0451292[/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 Mean7.75e-050.416550.000186052
Geometric MeanNaN
Harmonic Mean0.664815
Quadratic Mean1.8157
Winsorized Mean ( 1 / 6 )-0.02992250.40319-0.0742144
Winsorized Mean ( 2 / 6 )0.00037750.3766820.00100217
Winsorized Mean ( 3 / 6 )0.06607750.3451980.191419
Winsorized Mean ( 4 / 6 )-0.03592250.28308-0.126899
Winsorized Mean ( 5 / 6 )-0.03717250.257959-0.144102
Winsorized Mean ( 6 / 6 )-0.1170030.234728-0.498461
Trimmed Mean ( 1 / 6 )-0.002913890.391131-0.00744991
Trimmed Mean ( 2 / 6 )0.03084690.3641160.0847172
Trimmed Mean ( 3 / 6 )0.05261070.3376890.155797
Trimmed Mean ( 4 / 6 )0.04512920.3086690.146206
Trimmed Mean ( 5 / 6 )0.0856550.2992320.286249
Trimmed Mean ( 6 / 6 )0.1470690.2841820.517517
Median0.41975
Midrange0.027
Midmean - Weighted Average at Xnp-0.0715864
Midmean - Weighted Average at X(n+1)p0.085655
Midmean - Empirical Distribution Function-0.0715864
Midmean - Empirical Distribution Function - Averaging0.085655
Midmean - Empirical Distribution Function - Interpolation0.085655
Midmean - Closest Observation-0.0715864
Midmean - True Basic - Statistics Graphics Toolkit0.085655
Midmean - MS Excel (old versions)0.0451292
Number of observations20


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 500121222pearson11111111212120000FALSEFALSE0two.sidedtwo.sided20011two.sided0.010.0250.02520031111111111two.sidedtwo.sided0.850.0251Default124additive1Default11pearson11111111111pearson11110.025200Default1111additive12121212Defaultpearson0 ; par2 = 122111Do not include Seasonal DummiesDo not include Seasonal DummiesDo not include Seasonal DummiesDo not include Seasonal DummiesDo not include Seasonal DummiesDo not include Seasonal DummiesDo not include Seasonal DummiesDoubleTriple11111110.970.975220.850.990.9750.97551Do not include Seasonal DummiesDo not include Seasonal DummiesDo not include Seasonal DummiesDo not include Seasonal DummiesDo not include Seasonal DummiesDo not include Seasonal DummiesDo not include Seasonal DummiesDo not include Seasonal DummiesDo not include Seasonal DummiesDo not include Seasonal DummiesDo not include Seasonal DummiesDo not include Seasonal Dummies0.850.8500.975011201022222Do not include Seasonal DummiesDo not include Seasonal DummiesDo not include Seasonal DummiesDo not include Seasonal DummiesInclude Seasonal DummiesDo not include Seasonal DummiesDo not include Seasonal Dummies22Do not include Seasonal DummiesDo not include Seasonal Dummies0.97551000012SingleTripleDoubleTriple1no ; par3 = 5Pearson Chi-SquaredTRUE33No Linear TrendNo Linear TrendNo Linear TrendNo Linear TrendNo Linear TrendNo Linear TrendNo Linear Trendadditiveadditive0000000201503Pearson Chi-Squared00.010.050.0502No Linear TrendNo Linear TrendNo Linear TrendNo Linear TrendNo Linear TrendNo Linear TrendNo Linear TrendNo Linear TrendNo Linear TrendNo Linear TrendNo Linear TrendNo Linear Trend000.0500000Exact Pearson Chi-Squared by Simulation0.990.990.990.95No Linear TrendNo Linear TrendNo Linear TrendNo Linear TrendNo Linear TrendNo Linear TrendNo Linear Trend33No Linear TrendNo Linear Trend0.05000000additiveadditiveadditiveadditive0512 ; par4 = P1 P5 Q1 Q3 P95 P9912TRUE1212121212121111111P0.5 P2.5 Q1 Q3 P97.5 P99.5TRUEP0.5 P2.5 Q1 Q3 P97.5 P99.5TRUE12121212121212012401212two.sided12two.sided1TRUETRUEP0.5 P2.5 Q1 Q3 P97.5 P99.501111121212120 ; par5 = 121212121212121212unpairedunpairedunpairedunpaired11212 ; par6 = 12121212121212333333312121212121212121212112White NoiseWhite Noise000121212121212121212White NoiseWhite Noise ; par7 = 11221110.950.950.950.95 ; par8 = 1021211 ; par9 = 1111110 ; par10 = FALSEFALSEFALSEFALSEFALSE ;
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,'Arithmetic Mean',header=TRUE)
a<-table.element(a,signif(arm,6))
a<-table.element(a, signif(armse,6))
a<-table.element(a,signif(armose,6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Geometric Mean',header=TRUE)
a<-table.element(a,signif(geo,6))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Harmonic Mean',header=TRUE)
a<-table.element(a,signif(har,6))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Quadratic Mean',header=TRUE)
a<-table.element(a,signif(qua,6))
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, mylabel,header=TRUE)
a<-table.element(a,signif(win[j,1],6))
a<-table.element(a,signif(win[j,2],6))
a<-table.element(a,signif(win[j,1]/win[j,2],6))
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, mylabel,header=TRUE)
a<-table.element(a,signif(tri[j,1],6))
a<-table.element(a,signif(tri[j,2],6))
a<-table.element(a,signif(tri[j,1]/tri[j,2],6))
a<-table.row.end(a)
}
a<-table.row.start(a)
a<-table.element(a, 'Median',header=TRUE)
a<-table.element(a,signif(median(x),6))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Midrange',header=TRUE)
a<-table.element(a,signif(midr,6))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <-  'Midmean'
mylabel <- paste(mymid,'Weighted Average at Xnp',sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,signif(midm[1],6))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <-  'Midmean'
mylabel <- paste(mymid,'Weighted Average at X(n+1)p',sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,signif(midm[2],6))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <-  'Midmean'
mylabel <- paste(mymid,'Empirical Distribution Function',sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,signif(midm[3],6))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <-  'Midmean'
mylabel <- paste(mymid,'Empirical Distribution Function - Averaging',sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,signif(midm[4],6))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <-  'Midmean'
mylabel <- paste(mymid,'Empirical Distribution Function - Interpolation',sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,signif(midm[5],6))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <-  'Midmean'
mylabel <- paste(mymid,'Closest Observation',sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,signif(midm[6],6))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <-  'Midmean'
mylabel <- paste(mymid,'True Basic - Statistics Graphics Toolkit',sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,signif(midm[7],6))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <-  'Midmean'
mylabel <- paste(mymid,'MS Excel (old versions)',sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,signif(midm[8],6))
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,signif(length(x),6))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable.tab')