Free Statistics

of Irreproducible Research!

Author's title

Author*Unverified author*
R Software Modulerwasp_variability.wasp
Title produced by softwareVariability
Date of computationMon, 28 Nov 2011 09:29:59 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2011/Nov/28/t1322490675stnujhxuo7verot.htm/, Retrieved Fri, 29 Mar 2024 14:42:29 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=147753, Retrieved Fri, 29 Mar 2024 14:42:29 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsKDGP2W83
Estimated Impact101
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Bootstrap Plot - Central Tendency] [Bootstrap Plot ma...] [2011-11-23 17:58:33] [8970471211ece064523ec252a60bb336]
- RMPD  [Standard Deviation Plot] [Standard Deviatio...] [2011-11-28 12:07:09] [8970471211ece064523ec252a60bb336]
- RMPD      [Variability] [spreidingsmaten p...] [2011-11-28 14:29:59] [6e376bb9389cce432e10fa4d58960065] [Current]
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Dataseries X:
2,2
2,28
2,28
2,28
2,28
2,27
2,28
2,27
2,28
2,28
2,28
2,28
2,27
2,28
2,28
2,28
2,27
2,28
2,27
2,27
2,27
2,27
2,27
2,27
2,27
2,35
2,54
2,54
2,54
2,54
2,54
2,54
2,54
2,54
2,54
2,54
2,54
2,54
2,54
2,54
2,54
2,54
2,54
2,54
2,54
2,54
2,54
2,54
2,54
2,66
2,66
2,66
2,66
2,66
2,66
2,66
2,66
2,66
2,66
2,66
2,66
2,66
2,66
2,66
2,66
2,66
2,66
2,66
2,66
2,66
2,66
2,66
2,66
2,93
2,93
2,93
2,93
2,93
2,93
2,93
2,93
2,93
2,93
2,93




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'AstonUniversity' @ aston.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 & 'AstonUniversity' @ aston.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=147753&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]'AstonUniversity' @ aston.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=147753&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=147753&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 computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'AstonUniversity' @ aston.wessa.net







Variability - Ungrouped Data
Absolute range0.73
Relative range (unbiased)3.38942453287305
Relative range (biased)3.40978162000715
Variance (unbiased)0.0463867326448652
Variance (biased)0.0458345096371882
Standard Deviation (unbiased)0.21537579400867
Standard Deviation (biased)0.214089956880719
Coefficient of Variation (unbiased)0.0846785242065449
Coefficient of Variation (biased)0.084172976260147
Mean Squared Error (MSE versus 0)6.51498452380952
Mean Squared Error (MSE versus Mean)0.0458345096371882
Mean Absolute Deviation from Mean (MAD Mean)0.167837301587302
Mean Absolute Deviation from Median (MAD Median)0.167261904761905
Median Absolute Deviation from Mean0.116547619047619
Median Absolute Deviation from Median0.12
Mean Squared Deviation from Mean0.0458345096371882
Mean Squared Deviation from Median0.0458464285714286
Interquartile Difference (Weighted Average at Xnp)0.38
Interquartile Difference (Weighted Average at X(n+1)p)0.38
Interquartile Difference (Empirical Distribution Function)0.38
Interquartile Difference (Empirical Distribution Function - Averaging)0.38
Interquartile Difference (Empirical Distribution Function - Interpolation)0.38
Interquartile Difference (Closest Observation)0.38
Interquartile Difference (True Basic - Statistics Graphics Toolkit)0.38
Interquartile Difference (MS Excel (old versions))0.38
Semi Interquartile Difference (Weighted Average at Xnp)0.19
Semi Interquartile Difference (Weighted Average at X(n+1)p)0.19
Semi Interquartile Difference (Empirical Distribution Function)0.19
Semi Interquartile Difference (Empirical Distribution Function - Averaging)0.19
Semi Interquartile Difference (Empirical Distribution Function - Interpolation)0.19
Semi Interquartile Difference (Closest Observation)0.19
Semi Interquartile Difference (True Basic - Statistics Graphics Toolkit)0.19
Semi Interquartile Difference (MS Excel (old versions))0.19
Coefficient of Quartile Variation (Weighted Average at Xnp)0.076923076923077
Coefficient of Quartile Variation (Weighted Average at X(n+1)p)0.076923076923077
Coefficient of Quartile Variation (Empirical Distribution Function)0.076923076923077
Coefficient of Quartile Variation (Empirical Distribution Function - Averaging)0.076923076923077
Coefficient of Quartile Variation (Empirical Distribution Function - Interpolation)0.076923076923077
Coefficient of Quartile Variation (Closest Observation)0.076923076923077
Coefficient of Quartile Variation (True Basic - Statistics Graphics Toolkit)0.076923076923077
Coefficient of Quartile Variation (MS Excel (old versions))0.076923076923077
Number of all Pairs of Observations3486
Squared Differences between all Pairs of Observations0.0927734652897355
Mean Absolute Differences between all Pairs of Observations0.237185886402749
Gini Mean Difference0.237185886402756
Leik Measure of Dispersion0.504268043388156
Index of Diversity0.988010891786518
Index of Qualitative Variation0.999914637470693
Coefficient of Dispersion0.0660776777902762
Observations84

\begin{tabular}{lllllllll}
\hline
Variability - Ungrouped Data \tabularnewline
Absolute range & 0.73 \tabularnewline
Relative range (unbiased) & 3.38942453287305 \tabularnewline
Relative range (biased) & 3.40978162000715 \tabularnewline
Variance (unbiased) & 0.0463867326448652 \tabularnewline
Variance (biased) & 0.0458345096371882 \tabularnewline
Standard Deviation (unbiased) & 0.21537579400867 \tabularnewline
Standard Deviation (biased) & 0.214089956880719 \tabularnewline
Coefficient of Variation (unbiased) & 0.0846785242065449 \tabularnewline
Coefficient of Variation (biased) & 0.084172976260147 \tabularnewline
Mean Squared Error (MSE versus 0) & 6.51498452380952 \tabularnewline
Mean Squared Error (MSE versus Mean) & 0.0458345096371882 \tabularnewline
Mean Absolute Deviation from Mean (MAD Mean) & 0.167837301587302 \tabularnewline
Mean Absolute Deviation from Median (MAD Median) & 0.167261904761905 \tabularnewline
Median Absolute Deviation from Mean & 0.116547619047619 \tabularnewline
Median Absolute Deviation from Median & 0.12 \tabularnewline
Mean Squared Deviation from Mean & 0.0458345096371882 \tabularnewline
Mean Squared Deviation from Median & 0.0458464285714286 \tabularnewline
Interquartile Difference (Weighted Average at Xnp) & 0.38 \tabularnewline
Interquartile Difference (Weighted Average at X(n+1)p) & 0.38 \tabularnewline
Interquartile Difference (Empirical Distribution Function) & 0.38 \tabularnewline
Interquartile Difference (Empirical Distribution Function - Averaging) & 0.38 \tabularnewline
Interquartile Difference (Empirical Distribution Function - Interpolation) & 0.38 \tabularnewline
Interquartile Difference (Closest Observation) & 0.38 \tabularnewline
Interquartile Difference (True Basic - Statistics Graphics Toolkit) & 0.38 \tabularnewline
Interquartile Difference (MS Excel (old versions)) & 0.38 \tabularnewline
Semi Interquartile Difference (Weighted Average at Xnp) & 0.19 \tabularnewline
Semi Interquartile Difference (Weighted Average at X(n+1)p) & 0.19 \tabularnewline
Semi Interquartile Difference (Empirical Distribution Function) & 0.19 \tabularnewline
Semi Interquartile Difference (Empirical Distribution Function - Averaging) & 0.19 \tabularnewline
Semi Interquartile Difference (Empirical Distribution Function - Interpolation) & 0.19 \tabularnewline
Semi Interquartile Difference (Closest Observation) & 0.19 \tabularnewline
Semi Interquartile Difference (True Basic - Statistics Graphics Toolkit) & 0.19 \tabularnewline
Semi Interquartile Difference (MS Excel (old versions)) & 0.19 \tabularnewline
Coefficient of Quartile Variation (Weighted Average at Xnp) & 0.076923076923077 \tabularnewline
Coefficient of Quartile Variation (Weighted Average at X(n+1)p) & 0.076923076923077 \tabularnewline
Coefficient of Quartile Variation (Empirical Distribution Function) & 0.076923076923077 \tabularnewline
Coefficient of Quartile Variation (Empirical Distribution Function - Averaging) & 0.076923076923077 \tabularnewline
Coefficient of Quartile Variation (Empirical Distribution Function - Interpolation) & 0.076923076923077 \tabularnewline
Coefficient of Quartile Variation (Closest Observation) & 0.076923076923077 \tabularnewline
Coefficient of Quartile Variation (True Basic - Statistics Graphics Toolkit) & 0.076923076923077 \tabularnewline
Coefficient of Quartile Variation (MS Excel (old versions)) & 0.076923076923077 \tabularnewline
Number of all Pairs of Observations & 3486 \tabularnewline
Squared Differences between all Pairs of Observations & 0.0927734652897355 \tabularnewline
Mean Absolute Differences between all Pairs of Observations & 0.237185886402749 \tabularnewline
Gini Mean Difference & 0.237185886402756 \tabularnewline
Leik Measure of Dispersion & 0.504268043388156 \tabularnewline
Index of Diversity & 0.988010891786518 \tabularnewline
Index of Qualitative Variation & 0.999914637470693 \tabularnewline
Coefficient of Dispersion & 0.0660776777902762 \tabularnewline
Observations & 84 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=147753&T=1

[TABLE]
[ROW][C]Variability - Ungrouped Data[/C][/ROW]
[ROW][C]Absolute range[/C][C]0.73[/C][/ROW]
[ROW][C]Relative range (unbiased)[/C][C]3.38942453287305[/C][/ROW]
[ROW][C]Relative range (biased)[/C][C]3.40978162000715[/C][/ROW]
[ROW][C]Variance (unbiased)[/C][C]0.0463867326448652[/C][/ROW]
[ROW][C]Variance (biased)[/C][C]0.0458345096371882[/C][/ROW]
[ROW][C]Standard Deviation (unbiased)[/C][C]0.21537579400867[/C][/ROW]
[ROW][C]Standard Deviation (biased)[/C][C]0.214089956880719[/C][/ROW]
[ROW][C]Coefficient of Variation (unbiased)[/C][C]0.0846785242065449[/C][/ROW]
[ROW][C]Coefficient of Variation (biased)[/C][C]0.084172976260147[/C][/ROW]
[ROW][C]Mean Squared Error (MSE versus 0)[/C][C]6.51498452380952[/C][/ROW]
[ROW][C]Mean Squared Error (MSE versus Mean)[/C][C]0.0458345096371882[/C][/ROW]
[ROW][C]Mean Absolute Deviation from Mean (MAD Mean)[/C][C]0.167837301587302[/C][/ROW]
[ROW][C]Mean Absolute Deviation from Median (MAD Median)[/C][C]0.167261904761905[/C][/ROW]
[ROW][C]Median Absolute Deviation from Mean[/C][C]0.116547619047619[/C][/ROW]
[ROW][C]Median Absolute Deviation from Median[/C][C]0.12[/C][/ROW]
[ROW][C]Mean Squared Deviation from Mean[/C][C]0.0458345096371882[/C][/ROW]
[ROW][C]Mean Squared Deviation from Median[/C][C]0.0458464285714286[/C][/ROW]
[ROW][C]Interquartile Difference (Weighted Average at Xnp)[/C][C]0.38[/C][/ROW]
[ROW][C]Interquartile Difference (Weighted Average at X(n+1)p)[/C][C]0.38[/C][/ROW]
[ROW][C]Interquartile Difference (Empirical Distribution Function)[/C][C]0.38[/C][/ROW]
[ROW][C]Interquartile Difference (Empirical Distribution Function - Averaging)[/C][C]0.38[/C][/ROW]
[ROW][C]Interquartile Difference (Empirical Distribution Function - Interpolation)[/C][C]0.38[/C][/ROW]
[ROW][C]Interquartile Difference (Closest Observation)[/C][C]0.38[/C][/ROW]
[ROW][C]Interquartile Difference (True Basic - Statistics Graphics Toolkit)[/C][C]0.38[/C][/ROW]
[ROW][C]Interquartile Difference (MS Excel (old versions))[/C][C]0.38[/C][/ROW]
[ROW][C]Semi Interquartile Difference (Weighted Average at Xnp)[/C][C]0.19[/C][/ROW]
[ROW][C]Semi Interquartile Difference (Weighted Average at X(n+1)p)[/C][C]0.19[/C][/ROW]
[ROW][C]Semi Interquartile Difference (Empirical Distribution Function)[/C][C]0.19[/C][/ROW]
[ROW][C]Semi Interquartile Difference (Empirical Distribution Function - Averaging)[/C][C]0.19[/C][/ROW]
[ROW][C]Semi Interquartile Difference (Empirical Distribution Function - Interpolation)[/C][C]0.19[/C][/ROW]
[ROW][C]Semi Interquartile Difference (Closest Observation)[/C][C]0.19[/C][/ROW]
[ROW][C]Semi Interquartile Difference (True Basic - Statistics Graphics Toolkit)[/C][C]0.19[/C][/ROW]
[ROW][C]Semi Interquartile Difference (MS Excel (old versions))[/C][C]0.19[/C][/ROW]
[ROW][C]Coefficient of Quartile Variation (Weighted Average at Xnp)[/C][C]0.076923076923077[/C][/ROW]
[ROW][C]Coefficient of Quartile Variation (Weighted Average at X(n+1)p)[/C][C]0.076923076923077[/C][/ROW]
[ROW][C]Coefficient of Quartile Variation (Empirical Distribution Function)[/C][C]0.076923076923077[/C][/ROW]
[ROW][C]Coefficient of Quartile Variation (Empirical Distribution Function - Averaging)[/C][C]0.076923076923077[/C][/ROW]
[ROW][C]Coefficient of Quartile Variation (Empirical Distribution Function - Interpolation)[/C][C]0.076923076923077[/C][/ROW]
[ROW][C]Coefficient of Quartile Variation (Closest Observation)[/C][C]0.076923076923077[/C][/ROW]
[ROW][C]Coefficient of Quartile Variation (True Basic - Statistics Graphics Toolkit)[/C][C]0.076923076923077[/C][/ROW]
[ROW][C]Coefficient of Quartile Variation (MS Excel (old versions))[/C][C]0.076923076923077[/C][/ROW]
[ROW][C]Number of all Pairs of Observations[/C][C]3486[/C][/ROW]
[ROW][C]Squared Differences between all Pairs of Observations[/C][C]0.0927734652897355[/C][/ROW]
[ROW][C]Mean Absolute Differences between all Pairs of Observations[/C][C]0.237185886402749[/C][/ROW]
[ROW][C]Gini Mean Difference[/C][C]0.237185886402756[/C][/ROW]
[ROW][C]Leik Measure of Dispersion[/C][C]0.504268043388156[/C][/ROW]
[ROW][C]Index of Diversity[/C][C]0.988010891786518[/C][/ROW]
[ROW][C]Index of Qualitative Variation[/C][C]0.999914637470693[/C][/ROW]
[ROW][C]Coefficient of Dispersion[/C][C]0.0660776777902762[/C][/ROW]
[ROW][C]Observations[/C][C]84[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=147753&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=147753&T=1

As an alternative you can also use a QR Code:  

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

Variability - Ungrouped Data
Absolute range0.73
Relative range (unbiased)3.38942453287305
Relative range (biased)3.40978162000715
Variance (unbiased)0.0463867326448652
Variance (biased)0.0458345096371882
Standard Deviation (unbiased)0.21537579400867
Standard Deviation (biased)0.214089956880719
Coefficient of Variation (unbiased)0.0846785242065449
Coefficient of Variation (biased)0.084172976260147
Mean Squared Error (MSE versus 0)6.51498452380952
Mean Squared Error (MSE versus Mean)0.0458345096371882
Mean Absolute Deviation from Mean (MAD Mean)0.167837301587302
Mean Absolute Deviation from Median (MAD Median)0.167261904761905
Median Absolute Deviation from Mean0.116547619047619
Median Absolute Deviation from Median0.12
Mean Squared Deviation from Mean0.0458345096371882
Mean Squared Deviation from Median0.0458464285714286
Interquartile Difference (Weighted Average at Xnp)0.38
Interquartile Difference (Weighted Average at X(n+1)p)0.38
Interquartile Difference (Empirical Distribution Function)0.38
Interquartile Difference (Empirical Distribution Function - Averaging)0.38
Interquartile Difference (Empirical Distribution Function - Interpolation)0.38
Interquartile Difference (Closest Observation)0.38
Interquartile Difference (True Basic - Statistics Graphics Toolkit)0.38
Interquartile Difference (MS Excel (old versions))0.38
Semi Interquartile Difference (Weighted Average at Xnp)0.19
Semi Interquartile Difference (Weighted Average at X(n+1)p)0.19
Semi Interquartile Difference (Empirical Distribution Function)0.19
Semi Interquartile Difference (Empirical Distribution Function - Averaging)0.19
Semi Interquartile Difference (Empirical Distribution Function - Interpolation)0.19
Semi Interquartile Difference (Closest Observation)0.19
Semi Interquartile Difference (True Basic - Statistics Graphics Toolkit)0.19
Semi Interquartile Difference (MS Excel (old versions))0.19
Coefficient of Quartile Variation (Weighted Average at Xnp)0.076923076923077
Coefficient of Quartile Variation (Weighted Average at X(n+1)p)0.076923076923077
Coefficient of Quartile Variation (Empirical Distribution Function)0.076923076923077
Coefficient of Quartile Variation (Empirical Distribution Function - Averaging)0.076923076923077
Coefficient of Quartile Variation (Empirical Distribution Function - Interpolation)0.076923076923077
Coefficient of Quartile Variation (Closest Observation)0.076923076923077
Coefficient of Quartile Variation (True Basic - Statistics Graphics Toolkit)0.076923076923077
Coefficient of Quartile Variation (MS Excel (old versions))0.076923076923077
Number of all Pairs of Observations3486
Squared Differences between all Pairs of Observations0.0927734652897355
Mean Absolute Differences between all Pairs of Observations0.237185886402749
Gini Mean Difference0.237185886402756
Leik Measure of Dispersion0.504268043388156
Index of Diversity0.988010891786518
Index of Qualitative Variation0.999914637470693
Coefficient of Dispersion0.0660776777902762
Observations84



Parameters (Session):
Parameters (R input):
R code (references can be found in the software module):
num <- 50
res <- array(NA,dim=c(num,3))
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]
}
}
}
}
iqd <- 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)
}
iqdiff <- qvalue3 - qvalue1
return(c(iqdiff,iqdiff/2,iqdiff/(qvalue3 + qvalue1)))
}
range <- max(x) - min(x)
lx <- length(x)
biasf <- (lx-1)/lx
varx <- var(x)
bvarx <- varx*biasf
sdx <- sqrt(varx)
mx <- mean(x)
bsdx <- sqrt(bvarx)
x2 <- x*x
mse0 <- sum(x2)/lx
xmm <- x-mx
xmm2 <- xmm*xmm
msem <- sum(xmm2)/lx
axmm <- abs(x - mx)
medx <- median(x)
axmmed <- abs(x - medx)
xmmed <- x - medx
xmmed2 <- xmmed*xmmed
msemed <- sum(xmmed2)/lx
qarr <- array(NA,dim=c(8,3))
for (j in 1:8) {
qarr[j,] <- iqd(x,j)
}
sdpo <- 0
adpo <- 0
for (i in 1:(lx-1)) {
for (j in (i+1):lx) {
ldi <- x[i]-x[j]
aldi <- abs(ldi)
sdpo = sdpo + ldi * ldi
adpo = adpo + aldi
}
}
denom <- (lx*(lx-1)/2)
sdpo = sdpo / denom
adpo = adpo / denom
gmd <- 0
for (i in 1:lx) {
for (j in 1:lx) {
ldi <- abs(x[i]-x[j])
gmd = gmd + ldi
}
}
gmd <- gmd / (lx*(lx-1))
sumx <- sum(x)
pk <- x / sumx
ck <- cumsum(pk)
dk <- array(NA,dim=lx)
for (i in 1:lx) {
if (ck[i] <= 0.5) dk[i] <- ck[i] else dk[i] <- 1 - ck[i]
}
bigd <- sum(dk) * 2 / (lx-1)
iod <- 1 - sum(pk*pk)
res[1,] <- c('Absolute range','absolute.htm', range)
res[2,] <- c('Relative range (unbiased)','relative.htm', range/sd(x))
res[3,] <- c('Relative range (biased)','relative.htm', range/sqrt(varx*biasf))
res[4,] <- c('Variance (unbiased)','unbiased.htm', varx)
res[5,] <- c('Variance (biased)','biased.htm', bvarx)
res[6,] <- c('Standard Deviation (unbiased)','unbiased1.htm', sdx)
res[7,] <- c('Standard Deviation (biased)','biased1.htm', bsdx)
res[8,] <- c('Coefficient of Variation (unbiased)','variation.htm', sdx/mx)
res[9,] <- c('Coefficient of Variation (biased)','variation.htm', bsdx/mx)
res[10,] <- c('Mean Squared Error (MSE versus 0)','mse.htm', mse0)
res[11,] <- c('Mean Squared Error (MSE versus Mean)','mse.htm', msem)
res[12,] <- c('Mean Absolute Deviation from Mean (MAD Mean)', 'mean2.htm', sum(axmm)/lx)
res[13,] <- c('Mean Absolute Deviation from Median (MAD Median)', 'median1.htm', sum(axmmed)/lx)
res[14,] <- c('Median Absolute Deviation from Mean', 'mean3.htm', median(axmm))
res[15,] <- c('Median Absolute Deviation from Median', 'median2.htm', median(axmmed))
res[16,] <- c('Mean Squared Deviation from Mean', 'mean1.htm', msem)
res[17,] <- c('Mean Squared Deviation from Median', 'median.htm', msemed)
load(file='createtable')
mylink1 <- hyperlink('difference.htm','Interquartile Difference','')
mylink2 <- paste(mylink1,hyperlink('method_1.htm','(Weighted Average at Xnp)',''),sep=' ')
res[18,] <- c('', mylink2, qarr[1,1])
mylink2 <- paste(mylink1,hyperlink('method_2.htm','(Weighted Average at X(n+1)p)',''),sep=' ')
res[19,] <- c('', mylink2, qarr[2,1])
mylink2 <- paste(mylink1,hyperlink('method_3.htm','(Empirical Distribution Function)',''),sep=' ')
res[20,] <- c('', mylink2, qarr[3,1])
mylink2 <- paste(mylink1,hyperlink('method_4.htm','(Empirical Distribution Function - Averaging)',''),sep=' ')
res[21,] <- c('', mylink2, qarr[4,1])
mylink2 <- paste(mylink1,hyperlink('method_5.htm','(Empirical Distribution Function - Interpolation)',''),sep=' ')
res[22,] <- c('', mylink2, qarr[5,1])
mylink2 <- paste(mylink1,hyperlink('method_6.htm','(Closest Observation)',''),sep=' ')
res[23,] <- c('', mylink2, qarr[6,1])
mylink2 <- paste(mylink1,hyperlink('method_7.htm','(True Basic - Statistics Graphics Toolkit)',''),sep=' ')
res[24,] <- c('', mylink2, qarr[7,1])
mylink2 <- paste(mylink1,hyperlink('method_8.htm','(MS Excel (old versions))',''),sep=' ')
res[25,] <- c('', mylink2, qarr[8,1])
mylink1 <- hyperlink('deviation.htm','Semi Interquartile Difference','')
mylink2 <- paste(mylink1,hyperlink('method_1.htm','(Weighted Average at Xnp)',''),sep=' ')
res[26,] <- c('', mylink2, qarr[1,2])
mylink2 <- paste(mylink1,hyperlink('method_2.htm','(Weighted Average at X(n+1)p)',''),sep=' ')
res[27,] <- c('', mylink2, qarr[2,2])
mylink2 <- paste(mylink1,hyperlink('method_3.htm','(Empirical Distribution Function)',''),sep=' ')
res[28,] <- c('', mylink2, qarr[3,2])
mylink2 <- paste(mylink1,hyperlink('method_4.htm','(Empirical Distribution Function - Averaging)',''),sep=' ')
res[29,] <- c('', mylink2, qarr[4,2])
mylink2 <- paste(mylink1,hyperlink('method_5.htm','(Empirical Distribution Function - Interpolation)',''),sep=' ')
res[30,] <- c('', mylink2, qarr[5,2])
mylink2 <- paste(mylink1,hyperlink('method_6.htm','(Closest Observation)',''),sep=' ')
res[31,] <- c('', mylink2, qarr[6,2])
mylink2 <- paste(mylink1,hyperlink('method_7.htm','(True Basic - Statistics Graphics Toolkit)',''),sep=' ')
res[32,] <- c('', mylink2, qarr[7,2])
mylink2 <- paste(mylink1,hyperlink('method_8.htm','(MS Excel (old versions))',''),sep=' ')
res[33,] <- c('', mylink2, qarr[8,2])
mylink1 <- hyperlink('variation1.htm','Coefficient of Quartile Variation','')
mylink2 <- paste(mylink1,hyperlink('method_1.htm','(Weighted Average at Xnp)',''),sep=' ')
res[34,] <- c('', mylink2, qarr[1,3])
mylink2 <- paste(mylink1,hyperlink('method_2.htm','(Weighted Average at X(n+1)p)',''),sep=' ')
res[35,] <- c('', mylink2, qarr[2,3])
mylink2 <- paste(mylink1,hyperlink('method_3.htm','(Empirical Distribution Function)',''),sep=' ')
res[36,] <- c('', mylink2, qarr[3,3])
mylink2 <- paste(mylink1,hyperlink('method_4.htm','(Empirical Distribution Function - Averaging)',''),sep=' ')
res[37,] <- c('', mylink2, qarr[4,3])
mylink2 <- paste(mylink1,hyperlink('method_5.htm','(Empirical Distribution Function - Interpolation)',''),sep=' ')
res[38,] <- c('', mylink2, qarr[5,3])
mylink2 <- paste(mylink1,hyperlink('method_6.htm','(Closest Observation)',''),sep=' ')
res[39,] <- c('', mylink2, qarr[6,3])
mylink2 <- paste(mylink1,hyperlink('method_7.htm','(True Basic - Statistics Graphics Toolkit)',''),sep=' ')
res[40,] <- c('', mylink2, qarr[7,3])
mylink2 <- paste(mylink1,hyperlink('method_8.htm','(MS Excel (old versions))',''),sep=' ')
res[41,] <- c('', mylink2, qarr[8,3])
res[42,] <- c('Number of all Pairs of Observations', 'pair_numbers.htm', lx*(lx-1)/2)
res[43,] <- c('Squared Differences between all Pairs of Observations', 'squared_differences.htm', sdpo)
res[44,] <- c('Mean Absolute Differences between all Pairs of Observations', 'mean_abs_differences.htm', adpo)
res[45,] <- c('Gini Mean Difference', 'gini_mean_difference.htm', gmd)
res[46,] <- c('Leik Measure of Dispersion', 'leiks_d.htm', bigd)
res[47,] <- c('Index of Diversity', 'diversity.htm', iod)
res[48,] <- c('Index of Qualitative Variation', 'qualitative_variation.htm', iod*lx/(lx-1))
res[49,] <- c('Coefficient of Dispersion', 'dispersion.htm', sum(axmm)/lx/medx)
res[50,] <- c('Observations', '', lx)
res
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Variability - Ungrouped Data',2,TRUE)
a<-table.row.end(a)
for (i in 1:num) {
a<-table.row.start(a)
if (res[i,1] != '') {
a<-table.element(a,hyperlink(res[i,2],res[i,1],''),header=TRUE)
} else {
a<-table.element(a,res[i,2],header=TRUE)
}
a<-table.element(a,res[i,3])
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable.tab')