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Author's title

Author*Unverified author*
R Software Modulerwasp_variability.wasp
Title produced by softwareVariability
Date of computationWed, 04 Dec 2013 07:48:02 -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/2013/Dec/04/t13861614041ptvk2685ncuuee.htm/, Retrieved Thu, 18 Apr 2024 18:18:05 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=230578, Retrieved Thu, 18 Apr 2024 18:18:05 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact80
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Variability] [] [2013-12-04 12:48:02] [51fe0640a383c3aded7defd919b1cd8b] [Current]
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Dataseries X:
1,38
1,96
1,36
1,24
1,35
1,23
1,09
1,08
1,33
1,35
1,38
1,5
1,47
2,09
1,52
1,29
1,52
1,27
1,35
1,29
1,41
1,39
1,45
1,53
1,45
2,11
1,53
1,38
1,54
1,35
1,29
1,33
1,47
1,47
1,54
1,59
1,5
2
1,51
1,4
1,62
1,44
1,29
1,28
1,4
1,39
1,46
1,49
1,45
2,05
1,59
1,42
1,73
1,39
1,23
1,37
1,51
1,47
1,5
1,54
1,54
2,15
1,62
1,4
1,65
1,49
1,45
1,45
1,51
1,48
1,56
1,57
1,57
2,28
1,7
1,56
1,8
1,56
1,51
1,46
1,51
1,55
1,57
1,64




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ jenkins.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 & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=230578&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]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=230578&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=230578&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'Gwilym Jenkins' @ jenkins.wessa.net







Variability - Ungrouped Data
Absolute range1.2
Relative range (unbiased)5.47499860320731
Relative range (biased)5.50788177335716
Variance (unbiased)0.0480390562248996
Variance (biased)0.0474671626984127
Standard Deviation (unbiased)0.219178138108935
Standard Deviation (biased)0.217869600216305
Coefficient of Variation (unbiased)0.145552720382248
Coefficient of Variation (biased)0.144683741150839
Mean Squared Error (MSE versus 0)2.31500119047619
Mean Squared Error (MSE versus Mean)0.0474671626984127
Mean Absolute Deviation from Mean (MAD Mean)0.145714285714286
Mean Absolute Deviation from Median (MAD Median)0.143928571428571
Median Absolute Deviation from Mean0.100833333333333
Median Absolute Deviation from Median0.0850000000000002
Mean Squared Deviation from Mean0.0474671626984127
Mean Squared Deviation from Median0.0484178571428571
Interquartile Difference (Weighted Average at Xnp)0.18
Interquartile Difference (Weighted Average at X(n+1)p)0.18
Interquartile Difference (Empirical Distribution Function)0.18
Interquartile Difference (Empirical Distribution Function - Averaging)0.18
Interquartile Difference (Empirical Distribution Function - Interpolation)0.18
Interquartile Difference (Closest Observation)0.18
Interquartile Difference (True Basic - Statistics Graphics Toolkit)0.18
Interquartile Difference (MS Excel (old versions))0.18
Semi Interquartile Difference (Weighted Average at Xnp)0.0900000000000001
Semi Interquartile Difference (Weighted Average at X(n+1)p)0.0900000000000001
Semi Interquartile Difference (Empirical Distribution Function)0.0900000000000001
Semi Interquartile Difference (Empirical Distribution Function - Averaging)0.0900000000000001
Semi Interquartile Difference (Empirical Distribution Function - Interpolation)0.0900000000000001
Semi Interquartile Difference (Closest Observation)0.0900000000000001
Semi Interquartile Difference (True Basic - Statistics Graphics Toolkit)0.0900000000000001
Semi Interquartile Difference (MS Excel (old versions))0.0900000000000001
Coefficient of Quartile Variation (Weighted Average at Xnp)0.0612244897959184
Coefficient of Quartile Variation (Weighted Average at X(n+1)p)0.0612244897959184
Coefficient of Quartile Variation (Empirical Distribution Function)0.0612244897959184
Coefficient of Quartile Variation (Empirical Distribution Function - Averaging)0.0612244897959184
Coefficient of Quartile Variation (Empirical Distribution Function - Interpolation)0.0612244897959184
Coefficient of Quartile Variation (Closest Observation)0.0612244897959184
Coefficient of Quartile Variation (True Basic - Statistics Graphics Toolkit)0.0612244897959184
Coefficient of Quartile Variation (MS Excel (old versions))0.0612244897959184
Number of all Pairs of Observations3486
Squared Differences between all Pairs of Observations0.0960781124497995
Mean Absolute Differences between all Pairs of Observations0.221632243258748
Gini Mean Difference0.221632243258744
Leik Measure of Dispersion0.505643095744509
Index of Diversity0.987846031131507
Index of Qualitative Variation0.99974779054273
Coefficient of Dispersion0.0987893462469734
Observations84

\begin{tabular}{lllllllll}
\hline
Variability - Ungrouped Data \tabularnewline
Absolute range & 1.2 \tabularnewline
Relative range (unbiased) & 5.47499860320731 \tabularnewline
Relative range (biased) & 5.50788177335716 \tabularnewline
Variance (unbiased) & 0.0480390562248996 \tabularnewline
Variance (biased) & 0.0474671626984127 \tabularnewline
Standard Deviation (unbiased) & 0.219178138108935 \tabularnewline
Standard Deviation (biased) & 0.217869600216305 \tabularnewline
Coefficient of Variation (unbiased) & 0.145552720382248 \tabularnewline
Coefficient of Variation (biased) & 0.144683741150839 \tabularnewline
Mean Squared Error (MSE versus 0) & 2.31500119047619 \tabularnewline
Mean Squared Error (MSE versus Mean) & 0.0474671626984127 \tabularnewline
Mean Absolute Deviation from Mean (MAD Mean) & 0.145714285714286 \tabularnewline
Mean Absolute Deviation from Median (MAD Median) & 0.143928571428571 \tabularnewline
Median Absolute Deviation from Mean & 0.100833333333333 \tabularnewline
Median Absolute Deviation from Median & 0.0850000000000002 \tabularnewline
Mean Squared Deviation from Mean & 0.0474671626984127 \tabularnewline
Mean Squared Deviation from Median & 0.0484178571428571 \tabularnewline
Interquartile Difference (Weighted Average at Xnp) & 0.18 \tabularnewline
Interquartile Difference (Weighted Average at X(n+1)p) & 0.18 \tabularnewline
Interquartile Difference (Empirical Distribution Function) & 0.18 \tabularnewline
Interquartile Difference (Empirical Distribution Function - Averaging) & 0.18 \tabularnewline
Interquartile Difference (Empirical Distribution Function - Interpolation) & 0.18 \tabularnewline
Interquartile Difference (Closest Observation) & 0.18 \tabularnewline
Interquartile Difference (True Basic - Statistics Graphics Toolkit) & 0.18 \tabularnewline
Interquartile Difference (MS Excel (old versions)) & 0.18 \tabularnewline
Semi Interquartile Difference (Weighted Average at Xnp) & 0.0900000000000001 \tabularnewline
Semi Interquartile Difference (Weighted Average at X(n+1)p) & 0.0900000000000001 \tabularnewline
Semi Interquartile Difference (Empirical Distribution Function) & 0.0900000000000001 \tabularnewline
Semi Interquartile Difference (Empirical Distribution Function - Averaging) & 0.0900000000000001 \tabularnewline
Semi Interquartile Difference (Empirical Distribution Function - Interpolation) & 0.0900000000000001 \tabularnewline
Semi Interquartile Difference (Closest Observation) & 0.0900000000000001 \tabularnewline
Semi Interquartile Difference (True Basic - Statistics Graphics Toolkit) & 0.0900000000000001 \tabularnewline
Semi Interquartile Difference (MS Excel (old versions)) & 0.0900000000000001 \tabularnewline
Coefficient of Quartile Variation (Weighted Average at Xnp) & 0.0612244897959184 \tabularnewline
Coefficient of Quartile Variation (Weighted Average at X(n+1)p) & 0.0612244897959184 \tabularnewline
Coefficient of Quartile Variation (Empirical Distribution Function) & 0.0612244897959184 \tabularnewline
Coefficient of Quartile Variation (Empirical Distribution Function - Averaging) & 0.0612244897959184 \tabularnewline
Coefficient of Quartile Variation (Empirical Distribution Function - Interpolation) & 0.0612244897959184 \tabularnewline
Coefficient of Quartile Variation (Closest Observation) & 0.0612244897959184 \tabularnewline
Coefficient of Quartile Variation (True Basic - Statistics Graphics Toolkit) & 0.0612244897959184 \tabularnewline
Coefficient of Quartile Variation (MS Excel (old versions)) & 0.0612244897959184 \tabularnewline
Number of all Pairs of Observations & 3486 \tabularnewline
Squared Differences between all Pairs of Observations & 0.0960781124497995 \tabularnewline
Mean Absolute Differences between all Pairs of Observations & 0.221632243258748 \tabularnewline
Gini Mean Difference & 0.221632243258744 \tabularnewline
Leik Measure of Dispersion & 0.505643095744509 \tabularnewline
Index of Diversity & 0.987846031131507 \tabularnewline
Index of Qualitative Variation & 0.99974779054273 \tabularnewline
Coefficient of Dispersion & 0.0987893462469734 \tabularnewline
Observations & 84 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=230578&T=1

[TABLE]
[ROW][C]Variability - Ungrouped Data[/C][/ROW]
[ROW][C]Absolute range[/C][C]1.2[/C][/ROW]
[ROW][C]Relative range (unbiased)[/C][C]5.47499860320731[/C][/ROW]
[ROW][C]Relative range (biased)[/C][C]5.50788177335716[/C][/ROW]
[ROW][C]Variance (unbiased)[/C][C]0.0480390562248996[/C][/ROW]
[ROW][C]Variance (biased)[/C][C]0.0474671626984127[/C][/ROW]
[ROW][C]Standard Deviation (unbiased)[/C][C]0.219178138108935[/C][/ROW]
[ROW][C]Standard Deviation (biased)[/C][C]0.217869600216305[/C][/ROW]
[ROW][C]Coefficient of Variation (unbiased)[/C][C]0.145552720382248[/C][/ROW]
[ROW][C]Coefficient of Variation (biased)[/C][C]0.144683741150839[/C][/ROW]
[ROW][C]Mean Squared Error (MSE versus 0)[/C][C]2.31500119047619[/C][/ROW]
[ROW][C]Mean Squared Error (MSE versus Mean)[/C][C]0.0474671626984127[/C][/ROW]
[ROW][C]Mean Absolute Deviation from Mean (MAD Mean)[/C][C]0.145714285714286[/C][/ROW]
[ROW][C]Mean Absolute Deviation from Median (MAD Median)[/C][C]0.143928571428571[/C][/ROW]
[ROW][C]Median Absolute Deviation from Mean[/C][C]0.100833333333333[/C][/ROW]
[ROW][C]Median Absolute Deviation from Median[/C][C]0.0850000000000002[/C][/ROW]
[ROW][C]Mean Squared Deviation from Mean[/C][C]0.0474671626984127[/C][/ROW]
[ROW][C]Mean Squared Deviation from Median[/C][C]0.0484178571428571[/C][/ROW]
[ROW][C]Interquartile Difference (Weighted Average at Xnp)[/C][C]0.18[/C][/ROW]
[ROW][C]Interquartile Difference (Weighted Average at X(n+1)p)[/C][C]0.18[/C][/ROW]
[ROW][C]Interquartile Difference (Empirical Distribution Function)[/C][C]0.18[/C][/ROW]
[ROW][C]Interquartile Difference (Empirical Distribution Function - Averaging)[/C][C]0.18[/C][/ROW]
[ROW][C]Interquartile Difference (Empirical Distribution Function - Interpolation)[/C][C]0.18[/C][/ROW]
[ROW][C]Interquartile Difference (Closest Observation)[/C][C]0.18[/C][/ROW]
[ROW][C]Interquartile Difference (True Basic - Statistics Graphics Toolkit)[/C][C]0.18[/C][/ROW]
[ROW][C]Interquartile Difference (MS Excel (old versions))[/C][C]0.18[/C][/ROW]
[ROW][C]Semi Interquartile Difference (Weighted Average at Xnp)[/C][C]0.0900000000000001[/C][/ROW]
[ROW][C]Semi Interquartile Difference (Weighted Average at X(n+1)p)[/C][C]0.0900000000000001[/C][/ROW]
[ROW][C]Semi Interquartile Difference (Empirical Distribution Function)[/C][C]0.0900000000000001[/C][/ROW]
[ROW][C]Semi Interquartile Difference (Empirical Distribution Function - Averaging)[/C][C]0.0900000000000001[/C][/ROW]
[ROW][C]Semi Interquartile Difference (Empirical Distribution Function - Interpolation)[/C][C]0.0900000000000001[/C][/ROW]
[ROW][C]Semi Interquartile Difference (Closest Observation)[/C][C]0.0900000000000001[/C][/ROW]
[ROW][C]Semi Interquartile Difference (True Basic - Statistics Graphics Toolkit)[/C][C]0.0900000000000001[/C][/ROW]
[ROW][C]Semi Interquartile Difference (MS Excel (old versions))[/C][C]0.0900000000000001[/C][/ROW]
[ROW][C]Coefficient of Quartile Variation (Weighted Average at Xnp)[/C][C]0.0612244897959184[/C][/ROW]
[ROW][C]Coefficient of Quartile Variation (Weighted Average at X(n+1)p)[/C][C]0.0612244897959184[/C][/ROW]
[ROW][C]Coefficient of Quartile Variation (Empirical Distribution Function)[/C][C]0.0612244897959184[/C][/ROW]
[ROW][C]Coefficient of Quartile Variation (Empirical Distribution Function - Averaging)[/C][C]0.0612244897959184[/C][/ROW]
[ROW][C]Coefficient of Quartile Variation (Empirical Distribution Function - Interpolation)[/C][C]0.0612244897959184[/C][/ROW]
[ROW][C]Coefficient of Quartile Variation (Closest Observation)[/C][C]0.0612244897959184[/C][/ROW]
[ROW][C]Coefficient of Quartile Variation (True Basic - Statistics Graphics Toolkit)[/C][C]0.0612244897959184[/C][/ROW]
[ROW][C]Coefficient of Quartile Variation (MS Excel (old versions))[/C][C]0.0612244897959184[/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]0.0960781124497995[/C][/ROW]
[ROW][C]Mean Absolute Differences between all Pairs of Observations[/C][C]0.221632243258748[/C][/ROW]
[ROW][C]Gini Mean Difference[/C][C]0.221632243258744[/C][/ROW]
[ROW][C]Leik Measure of Dispersion[/C][C]0.505643095744509[/C][/ROW]
[ROW][C]Index of Diversity[/C][C]0.987846031131507[/C][/ROW]
[ROW][C]Index of Qualitative Variation[/C][C]0.99974779054273[/C][/ROW]
[ROW][C]Coefficient of Dispersion[/C][C]0.0987893462469734[/C][/ROW]
[ROW][C]Observations[/C][C]84[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=230578&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=230578&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 range1.2
Relative range (unbiased)5.47499860320731
Relative range (biased)5.50788177335716
Variance (unbiased)0.0480390562248996
Variance (biased)0.0474671626984127
Standard Deviation (unbiased)0.219178138108935
Standard Deviation (biased)0.217869600216305
Coefficient of Variation (unbiased)0.145552720382248
Coefficient of Variation (biased)0.144683741150839
Mean Squared Error (MSE versus 0)2.31500119047619
Mean Squared Error (MSE versus Mean)0.0474671626984127
Mean Absolute Deviation from Mean (MAD Mean)0.145714285714286
Mean Absolute Deviation from Median (MAD Median)0.143928571428571
Median Absolute Deviation from Mean0.100833333333333
Median Absolute Deviation from Median0.0850000000000002
Mean Squared Deviation from Mean0.0474671626984127
Mean Squared Deviation from Median0.0484178571428571
Interquartile Difference (Weighted Average at Xnp)0.18
Interquartile Difference (Weighted Average at X(n+1)p)0.18
Interquartile Difference (Empirical Distribution Function)0.18
Interquartile Difference (Empirical Distribution Function - Averaging)0.18
Interquartile Difference (Empirical Distribution Function - Interpolation)0.18
Interquartile Difference (Closest Observation)0.18
Interquartile Difference (True Basic - Statistics Graphics Toolkit)0.18
Interquartile Difference (MS Excel (old versions))0.18
Semi Interquartile Difference (Weighted Average at Xnp)0.0900000000000001
Semi Interquartile Difference (Weighted Average at X(n+1)p)0.0900000000000001
Semi Interquartile Difference (Empirical Distribution Function)0.0900000000000001
Semi Interquartile Difference (Empirical Distribution Function - Averaging)0.0900000000000001
Semi Interquartile Difference (Empirical Distribution Function - Interpolation)0.0900000000000001
Semi Interquartile Difference (Closest Observation)0.0900000000000001
Semi Interquartile Difference (True Basic - Statistics Graphics Toolkit)0.0900000000000001
Semi Interquartile Difference (MS Excel (old versions))0.0900000000000001
Coefficient of Quartile Variation (Weighted Average at Xnp)0.0612244897959184
Coefficient of Quartile Variation (Weighted Average at X(n+1)p)0.0612244897959184
Coefficient of Quartile Variation (Empirical Distribution Function)0.0612244897959184
Coefficient of Quartile Variation (Empirical Distribution Function - Averaging)0.0612244897959184
Coefficient of Quartile Variation (Empirical Distribution Function - Interpolation)0.0612244897959184
Coefficient of Quartile Variation (Closest Observation)0.0612244897959184
Coefficient of Quartile Variation (True Basic - Statistics Graphics Toolkit)0.0612244897959184
Coefficient of Quartile Variation (MS Excel (old versions))0.0612244897959184
Number of all Pairs of Observations3486
Squared Differences between all Pairs of Observations0.0960781124497995
Mean Absolute Differences between all Pairs of Observations0.221632243258748
Gini Mean Difference0.221632243258744
Leik Measure of Dispersion0.505643095744509
Index of Diversity0.987846031131507
Index of Qualitative Variation0.99974779054273
Coefficient of Dispersion0.0987893462469734
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')