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of Irreproducible Research!

Author's title

Author*Unverified author*
R Software Modulerwasp_variability.wasp
Title produced by softwareVariability
Date of computationTue, 29 Nov 2011 03:27:13 -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/29/t1322555296uufhx3w8y2bu1rf.htm/, Retrieved Fri, 29 Mar 2024 04:41:44 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=148100, Retrieved Fri, 29 Mar 2024 04:41:44 +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)
-       [Variability] [Gemiddelde consum...] [2011-11-29 08:27:13] [08802a004a000ae20ac4145e9a22f7e4] [Current]
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Dataseries X:
15.14
14.2
13.83
14.31
14.04
14.9
14.92
15.36
15.5
15.65
16.18
15.44
15.58
15.24
15.33
16.07
15.82
15.87
15.72
17.07
16.83
17.52
17.76
17.36
17.95
16.71
17.14
16.72
17.26
17.24
17.69
18.13
18.08
18.18
18.18
17.64
17.89
16.82
16.61
16.66
17.02
16.91
17.18
18.06
17.58
17.48
17.54
17.44
17.79
16.79
16.19
16.62
16.39
16.54
17.26
18
17.29
18.16
17.82
17.48
18.31
17.04
17.03
16.97
17.11
17.12
17.69
18.5
18.27
18.45
18.35
18.03
18.49
18.07
17.8
17.88
18.12
18.68
18.8
19.64
19.56
19.3
20.07
19.82
20.29
19.36
18.74
18.87
18.87
18.91
19.31
20.06
20.72
20.42
20.58
20.58
21.18
19.87
19.83
19.48
19.49
19.4
19.89
20.44
20.07
19.75
19.54
19.07
19.55
18.01
17.5
17.41
17.47
17.6
17.64
18.3
18.27
17.99
18.04
17.62
18.22
17.67
17.73
17.99
18.15
18.41
18.36
19.52
19.96
19.6
19.48
19.13




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'George Udny Yule' @ yule.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 & 'George Udny Yule' @ yule.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=148100&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]'George Udny Yule' @ yule.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=148100&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=148100&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'George Udny Yule' @ yule.wessa.net







Variability - Ungrouped Data
Absolute range7.35
Relative range (unbiased)4.80805875366224
Relative range (biased)4.82637523429016
Variance (unbiased)2.33687318991441
Variance (biased)2.31916960514233
Standard Deviation (unbiased)1.52868348258049
Standard Deviation (biased)1.52288200630986
Coefficient of Variation (unbiased)0.0857380518120197
Coefficient of Variation (biased)0.0854126690373997
Mean Squared Error (MSE versus 0)320.217263636364
Mean Squared Error (MSE versus Mean)2.31916960514233
Mean Absolute Deviation from Mean (MAD Mean)1.18045454545455
Mean Absolute Deviation from Median (MAD Median)1.18045454545455
Median Absolute Deviation from Mean0.915
Median Absolute Deviation from Median0.915
Mean Squared Deviation from Mean2.31916960514233
Mean Squared Deviation from Median2.31958181818182
Interquartile Difference (Weighted Average at Xnp)1.85
Interquartile Difference (Weighted Average at X(n+1)p)1.8475
Interquartile Difference (Empirical Distribution Function)1.85
Interquartile Difference (Empirical Distribution Function - Averaging)1.845
Interquartile Difference (Empirical Distribution Function - Interpolation)1.8425
Interquartile Difference (Closest Observation)1.85
Interquartile Difference (True Basic - Statistics Graphics Toolkit)1.8425
Interquartile Difference (MS Excel (old versions))1.85
Semi Interquartile Difference (Weighted Average at Xnp)0.925
Semi Interquartile Difference (Weighted Average at X(n+1)p)0.92375
Semi Interquartile Difference (Empirical Distribution Function)0.925
Semi Interquartile Difference (Empirical Distribution Function - Averaging)0.922500000000001
Semi Interquartile Difference (Empirical Distribution Function - Interpolation)0.92125
Semi Interquartile Difference (Closest Observation)0.925
Semi Interquartile Difference (True Basic - Statistics Graphics Toolkit)0.92125
Semi Interquartile Difference (MS Excel (old versions))0.925
Coefficient of Quartile Variation (Weighted Average at Xnp)0.0515463917525774
Coefficient of Quartile Variation (Weighted Average at X(n+1)p)0.0514731489865571
Coefficient of Quartile Variation (Empirical Distribution Function)0.0515463917525774
Coefficient of Quartile Variation (Empirical Distribution Function - Averaging)0.0513999164229002
Coefficient of Quartile Variation (Empirical Distribution Function - Interpolation)0.0513266940594749
Coefficient of Quartile Variation (Closest Observation)0.0515463917525774
Coefficient of Quartile Variation (True Basic - Statistics Graphics Toolkit)0.0513266940594749
Coefficient of Quartile Variation (MS Excel (old versions))0.0515463917525774
Number of all Pairs of Observations8646
Squared Differences between all Pairs of Observations4.6737463798288
Mean Absolute Differences between all Pairs of Observations1.72243812167477
Gini Mean Difference1.72243812167476
Leik Measure of Dispersion0.49494283566548
Index of Diversity0.992368974817939
Index of Qualitative Variation0.999944310503572
Coefficient of Dispersion0.0661319073083779
Observations132

\begin{tabular}{lllllllll}
\hline
Variability - Ungrouped Data \tabularnewline
Absolute range & 7.35 \tabularnewline
Relative range (unbiased) & 4.80805875366224 \tabularnewline
Relative range (biased) & 4.82637523429016 \tabularnewline
Variance (unbiased) & 2.33687318991441 \tabularnewline
Variance (biased) & 2.31916960514233 \tabularnewline
Standard Deviation (unbiased) & 1.52868348258049 \tabularnewline
Standard Deviation (biased) & 1.52288200630986 \tabularnewline
Coefficient of Variation (unbiased) & 0.0857380518120197 \tabularnewline
Coefficient of Variation (biased) & 0.0854126690373997 \tabularnewline
Mean Squared Error (MSE versus 0) & 320.217263636364 \tabularnewline
Mean Squared Error (MSE versus Mean) & 2.31916960514233 \tabularnewline
Mean Absolute Deviation from Mean (MAD Mean) & 1.18045454545455 \tabularnewline
Mean Absolute Deviation from Median (MAD Median) & 1.18045454545455 \tabularnewline
Median Absolute Deviation from Mean & 0.915 \tabularnewline
Median Absolute Deviation from Median & 0.915 \tabularnewline
Mean Squared Deviation from Mean & 2.31916960514233 \tabularnewline
Mean Squared Deviation from Median & 2.31958181818182 \tabularnewline
Interquartile Difference (Weighted Average at Xnp) & 1.85 \tabularnewline
Interquartile Difference (Weighted Average at X(n+1)p) & 1.8475 \tabularnewline
Interquartile Difference (Empirical Distribution Function) & 1.85 \tabularnewline
Interquartile Difference (Empirical Distribution Function - Averaging) & 1.845 \tabularnewline
Interquartile Difference (Empirical Distribution Function - Interpolation) & 1.8425 \tabularnewline
Interquartile Difference (Closest Observation) & 1.85 \tabularnewline
Interquartile Difference (True Basic - Statistics Graphics Toolkit) & 1.8425 \tabularnewline
Interquartile Difference (MS Excel (old versions)) & 1.85 \tabularnewline
Semi Interquartile Difference (Weighted Average at Xnp) & 0.925 \tabularnewline
Semi Interquartile Difference (Weighted Average at X(n+1)p) & 0.92375 \tabularnewline
Semi Interquartile Difference (Empirical Distribution Function) & 0.925 \tabularnewline
Semi Interquartile Difference (Empirical Distribution Function - Averaging) & 0.922500000000001 \tabularnewline
Semi Interquartile Difference (Empirical Distribution Function - Interpolation) & 0.92125 \tabularnewline
Semi Interquartile Difference (Closest Observation) & 0.925 \tabularnewline
Semi Interquartile Difference (True Basic - Statistics Graphics Toolkit) & 0.92125 \tabularnewline
Semi Interquartile Difference (MS Excel (old versions)) & 0.925 \tabularnewline
Coefficient of Quartile Variation (Weighted Average at Xnp) & 0.0515463917525774 \tabularnewline
Coefficient of Quartile Variation (Weighted Average at X(n+1)p) & 0.0514731489865571 \tabularnewline
Coefficient of Quartile Variation (Empirical Distribution Function) & 0.0515463917525774 \tabularnewline
Coefficient of Quartile Variation (Empirical Distribution Function - Averaging) & 0.0513999164229002 \tabularnewline
Coefficient of Quartile Variation (Empirical Distribution Function - Interpolation) & 0.0513266940594749 \tabularnewline
Coefficient of Quartile Variation (Closest Observation) & 0.0515463917525774 \tabularnewline
Coefficient of Quartile Variation (True Basic - Statistics Graphics Toolkit) & 0.0513266940594749 \tabularnewline
Coefficient of Quartile Variation (MS Excel (old versions)) & 0.0515463917525774 \tabularnewline
Number of all Pairs of Observations & 8646 \tabularnewline
Squared Differences between all Pairs of Observations & 4.6737463798288 \tabularnewline
Mean Absolute Differences between all Pairs of Observations & 1.72243812167477 \tabularnewline
Gini Mean Difference & 1.72243812167476 \tabularnewline
Leik Measure of Dispersion & 0.49494283566548 \tabularnewline
Index of Diversity & 0.992368974817939 \tabularnewline
Index of Qualitative Variation & 0.999944310503572 \tabularnewline
Coefficient of Dispersion & 0.0661319073083779 \tabularnewline
Observations & 132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=148100&T=1

[TABLE]
[ROW][C]Variability - Ungrouped Data[/C][/ROW]
[ROW][C]Absolute range[/C][C]7.35[/C][/ROW]
[ROW][C]Relative range (unbiased)[/C][C]4.80805875366224[/C][/ROW]
[ROW][C]Relative range (biased)[/C][C]4.82637523429016[/C][/ROW]
[ROW][C]Variance (unbiased)[/C][C]2.33687318991441[/C][/ROW]
[ROW][C]Variance (biased)[/C][C]2.31916960514233[/C][/ROW]
[ROW][C]Standard Deviation (unbiased)[/C][C]1.52868348258049[/C][/ROW]
[ROW][C]Standard Deviation (biased)[/C][C]1.52288200630986[/C][/ROW]
[ROW][C]Coefficient of Variation (unbiased)[/C][C]0.0857380518120197[/C][/ROW]
[ROW][C]Coefficient of Variation (biased)[/C][C]0.0854126690373997[/C][/ROW]
[ROW][C]Mean Squared Error (MSE versus 0)[/C][C]320.217263636364[/C][/ROW]
[ROW][C]Mean Squared Error (MSE versus Mean)[/C][C]2.31916960514233[/C][/ROW]
[ROW][C]Mean Absolute Deviation from Mean (MAD Mean)[/C][C]1.18045454545455[/C][/ROW]
[ROW][C]Mean Absolute Deviation from Median (MAD Median)[/C][C]1.18045454545455[/C][/ROW]
[ROW][C]Median Absolute Deviation from Mean[/C][C]0.915[/C][/ROW]
[ROW][C]Median Absolute Deviation from Median[/C][C]0.915[/C][/ROW]
[ROW][C]Mean Squared Deviation from Mean[/C][C]2.31916960514233[/C][/ROW]
[ROW][C]Mean Squared Deviation from Median[/C][C]2.31958181818182[/C][/ROW]
[ROW][C]Interquartile Difference (Weighted Average at Xnp)[/C][C]1.85[/C][/ROW]
[ROW][C]Interquartile Difference (Weighted Average at X(n+1)p)[/C][C]1.8475[/C][/ROW]
[ROW][C]Interquartile Difference (Empirical Distribution Function)[/C][C]1.85[/C][/ROW]
[ROW][C]Interquartile Difference (Empirical Distribution Function - Averaging)[/C][C]1.845[/C][/ROW]
[ROW][C]Interquartile Difference (Empirical Distribution Function - Interpolation)[/C][C]1.8425[/C][/ROW]
[ROW][C]Interquartile Difference (Closest Observation)[/C][C]1.85[/C][/ROW]
[ROW][C]Interquartile Difference (True Basic - Statistics Graphics Toolkit)[/C][C]1.8425[/C][/ROW]
[ROW][C]Interquartile Difference (MS Excel (old versions))[/C][C]1.85[/C][/ROW]
[ROW][C]Semi Interquartile Difference (Weighted Average at Xnp)[/C][C]0.925[/C][/ROW]
[ROW][C]Semi Interquartile Difference (Weighted Average at X(n+1)p)[/C][C]0.92375[/C][/ROW]
[ROW][C]Semi Interquartile Difference (Empirical Distribution Function)[/C][C]0.925[/C][/ROW]
[ROW][C]Semi Interquartile Difference (Empirical Distribution Function - Averaging)[/C][C]0.922500000000001[/C][/ROW]
[ROW][C]Semi Interquartile Difference (Empirical Distribution Function - Interpolation)[/C][C]0.92125[/C][/ROW]
[ROW][C]Semi Interquartile Difference (Closest Observation)[/C][C]0.925[/C][/ROW]
[ROW][C]Semi Interquartile Difference (True Basic - Statistics Graphics Toolkit)[/C][C]0.92125[/C][/ROW]
[ROW][C]Semi Interquartile Difference (MS Excel (old versions))[/C][C]0.925[/C][/ROW]
[ROW][C]Coefficient of Quartile Variation (Weighted Average at Xnp)[/C][C]0.0515463917525774[/C][/ROW]
[ROW][C]Coefficient of Quartile Variation (Weighted Average at X(n+1)p)[/C][C]0.0514731489865571[/C][/ROW]
[ROW][C]Coefficient of Quartile Variation (Empirical Distribution Function)[/C][C]0.0515463917525774[/C][/ROW]
[ROW][C]Coefficient of Quartile Variation (Empirical Distribution Function - Averaging)[/C][C]0.0513999164229002[/C][/ROW]
[ROW][C]Coefficient of Quartile Variation (Empirical Distribution Function - Interpolation)[/C][C]0.0513266940594749[/C][/ROW]
[ROW][C]Coefficient of Quartile Variation (Closest Observation)[/C][C]0.0515463917525774[/C][/ROW]
[ROW][C]Coefficient of Quartile Variation (True Basic - Statistics Graphics Toolkit)[/C][C]0.0513266940594749[/C][/ROW]
[ROW][C]Coefficient of Quartile Variation (MS Excel (old versions))[/C][C]0.0515463917525774[/C][/ROW]
[ROW][C]Number of all Pairs of Observations[/C][C]8646[/C][/ROW]
[ROW][C]Squared Differences between all Pairs of Observations[/C][C]4.6737463798288[/C][/ROW]
[ROW][C]Mean Absolute Differences between all Pairs of Observations[/C][C]1.72243812167477[/C][/ROW]
[ROW][C]Gini Mean Difference[/C][C]1.72243812167476[/C][/ROW]
[ROW][C]Leik Measure of Dispersion[/C][C]0.49494283566548[/C][/ROW]
[ROW][C]Index of Diversity[/C][C]0.992368974817939[/C][/ROW]
[ROW][C]Index of Qualitative Variation[/C][C]0.999944310503572[/C][/ROW]
[ROW][C]Coefficient of Dispersion[/C][C]0.0661319073083779[/C][/ROW]
[ROW][C]Observations[/C][C]132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=148100&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=148100&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 range7.35
Relative range (unbiased)4.80805875366224
Relative range (biased)4.82637523429016
Variance (unbiased)2.33687318991441
Variance (biased)2.31916960514233
Standard Deviation (unbiased)1.52868348258049
Standard Deviation (biased)1.52288200630986
Coefficient of Variation (unbiased)0.0857380518120197
Coefficient of Variation (biased)0.0854126690373997
Mean Squared Error (MSE versus 0)320.217263636364
Mean Squared Error (MSE versus Mean)2.31916960514233
Mean Absolute Deviation from Mean (MAD Mean)1.18045454545455
Mean Absolute Deviation from Median (MAD Median)1.18045454545455
Median Absolute Deviation from Mean0.915
Median Absolute Deviation from Median0.915
Mean Squared Deviation from Mean2.31916960514233
Mean Squared Deviation from Median2.31958181818182
Interquartile Difference (Weighted Average at Xnp)1.85
Interquartile Difference (Weighted Average at X(n+1)p)1.8475
Interquartile Difference (Empirical Distribution Function)1.85
Interquartile Difference (Empirical Distribution Function - Averaging)1.845
Interquartile Difference (Empirical Distribution Function - Interpolation)1.8425
Interquartile Difference (Closest Observation)1.85
Interquartile Difference (True Basic - Statistics Graphics Toolkit)1.8425
Interquartile Difference (MS Excel (old versions))1.85
Semi Interquartile Difference (Weighted Average at Xnp)0.925
Semi Interquartile Difference (Weighted Average at X(n+1)p)0.92375
Semi Interquartile Difference (Empirical Distribution Function)0.925
Semi Interquartile Difference (Empirical Distribution Function - Averaging)0.922500000000001
Semi Interquartile Difference (Empirical Distribution Function - Interpolation)0.92125
Semi Interquartile Difference (Closest Observation)0.925
Semi Interquartile Difference (True Basic - Statistics Graphics Toolkit)0.92125
Semi Interquartile Difference (MS Excel (old versions))0.925
Coefficient of Quartile Variation (Weighted Average at Xnp)0.0515463917525774
Coefficient of Quartile Variation (Weighted Average at X(n+1)p)0.0514731489865571
Coefficient of Quartile Variation (Empirical Distribution Function)0.0515463917525774
Coefficient of Quartile Variation (Empirical Distribution Function - Averaging)0.0513999164229002
Coefficient of Quartile Variation (Empirical Distribution Function - Interpolation)0.0513266940594749
Coefficient of Quartile Variation (Closest Observation)0.0515463917525774
Coefficient of Quartile Variation (True Basic - Statistics Graphics Toolkit)0.0513266940594749
Coefficient of Quartile Variation (MS Excel (old versions))0.0515463917525774
Number of all Pairs of Observations8646
Squared Differences between all Pairs of Observations4.6737463798288
Mean Absolute Differences between all Pairs of Observations1.72243812167477
Gini Mean Difference1.72243812167476
Leik Measure of Dispersion0.49494283566548
Index of Diversity0.992368974817939
Index of Qualitative Variation0.999944310503572
Coefficient of Dispersion0.0661319073083779
Observations132



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')