Free Statistics

of Irreproducible Research!

Author's title

Author*Unverified author*
R Software Modulerwasp_variability.wasp
Title produced by softwareVariability
Date of computationFri, 20 May 2011 14:00:23 +0000
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/May/20/t13058998474p3h0cru1kwzfrt.htm/, Retrieved Sun, 12 May 2024 14:35:46 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=122458, Retrieved Sun, 12 May 2024 14:35:46 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsKDGP2W83
Estimated Impact90
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [Datareeks-tijdree...] [2011-05-20 09:52:47] [84d07acf15b5851f5f3dc97fb3479c7e]
- RMPD  [(Partial) Autocorrelation Function] [ datareeks - gemi...] [2011-05-20 10:50:15] [1a2529c7ddde8b9806f7cce4d00981a3]
- RM D      [Variability] [datareeks - modul...] [2011-05-20 14:00:23] [31886bd2f92a612f059dd2285dd41f3c] [Current]
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Dataseries X:
5.81    
5.76    
5.99    
6.12    
6.03    
6.25    
5.80    
5.67    
5.89    
5.91    
5.86    
6.07    
6.27    
6.68    
6.77    
6.71    
6.62
6.50
5.89
6.05
6.43
6.47
6.62
6.77
6.70
6.95
6.73
7.07
7.28
7.32
6.76
6.93
6.99
7.16
7.28
7.08
7.34
7.87
6.28
6.30
6.36
6.28
5.89
6.04
5.96
6.10
6.26
6.02
6.25
6.41
6.22
6.57
6.18
6.26
6.10
6.02
6.06
6.35
6.21
6.48
6.74
6.53
6.80
6.75
6.56
6.66
6.18
6.40
6.43
6.54
6.44
6.64
6.82
6.97
7.00
6.91
6.74
6.98
6.37
6.56
6.63
6.87
6.68
6.75
6.84
7.15
7.09
6.97
7.15




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ www.wessa.org

\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' @ www.wessa.org \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=122458&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' @ www.wessa.org[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=122458&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=122458&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' @ www.wessa.org







Variability - Ungrouped Data
Absolute range2.2
Relative range (unbiased)4.98918950487231
Relative range (biased)5.01745709371743
Variance (unbiased)0.19443988764045
Variance (biased)0.192255169801793
Standard Deviation (unbiased)0.440953384883765
Standard Deviation (biased)0.43846912069357
Coefficient of Variation (unbiased)0.0676460419799277
Coefficient of Variation (biased)0.0672649344854396
Mean Squared Error (MSE versus 0)42.6836101123596
Mean Squared Error (MSE versus Mean)0.192255169801793
Mean Absolute Deviation from Mean (MAD Mean)0.363948996338846
Mean Absolute Deviation from Median (MAD Median)0.363820224719101
Median Absolute Deviation from Mean0.308539325842696
Median Absolute Deviation from Median0.31
Mean Squared Deviation from Mean0.192255169801793
Mean Squared Deviation from Median0.192386516853933
Interquartile Difference (Weighted Average at Xnp)0.6125
Interquartile Difference (Weighted Average at X(n+1)p)0.630000000000001
Interquartile Difference (Empirical Distribution Function)0.62
Interquartile Difference (Empirical Distribution Function - Averaging)0.62
Interquartile Difference (Empirical Distribution Function - Interpolation)0.62
Interquartile Difference (Closest Observation)0.62
Interquartile Difference (True Basic - Statistics Graphics Toolkit)0.630000000000001
Interquartile Difference (MS Excel (old versions))0.630000000000001
Semi Interquartile Difference (Weighted Average at Xnp)0.30625
Semi Interquartile Difference (Weighted Average at X(n+1)p)0.315
Semi Interquartile Difference (Empirical Distribution Function)0.31
Semi Interquartile Difference (Empirical Distribution Function - Averaging)0.31
Semi Interquartile Difference (Empirical Distribution Function - Interpolation)0.31
Semi Interquartile Difference (Closest Observation)0.31
Semi Interquartile Difference (True Basic - Statistics Graphics Toolkit)0.315
Semi Interquartile Difference (MS Excel (old versions))0.315
Coefficient of Quartile Variation (Weighted Average at Xnp)0.0472152630564656
Coefficient of Quartile Variation (Weighted Average at X(n+1)p)0.048498845265589
Coefficient of Quartile Variation (Empirical Distribution Function)0.0477657935285054
Coefficient of Quartile Variation (Empirical Distribution Function - Averaging)0.0477657935285054
Coefficient of Quartile Variation (Empirical Distribution Function - Interpolation)0.0477657935285054
Coefficient of Quartile Variation (Closest Observation)0.0477657935285054
Coefficient of Quartile Variation (True Basic - Statistics Graphics Toolkit)0.048498845265589
Coefficient of Quartile Variation (MS Excel (old versions))0.048498845265589
Number of all Pairs of Observations3916
Squared Differences between all Pairs of Observations0.388879775280899
Mean Absolute Differences between all Pairs of Observations0.50396322778345
Gini Mean Difference0.503963227783452
Leik Measure of Dispersion0.505341486919527
Index of Diversity0.988713207062794
Index of Qualitative Variation0.99994858441578
Coefficient of Dispersion0.055734915212687
Observations89

\begin{tabular}{lllllllll}
\hline
Variability - Ungrouped Data \tabularnewline
Absolute range & 2.2 \tabularnewline
Relative range (unbiased) & 4.98918950487231 \tabularnewline
Relative range (biased) & 5.01745709371743 \tabularnewline
Variance (unbiased) & 0.19443988764045 \tabularnewline
Variance (biased) & 0.192255169801793 \tabularnewline
Standard Deviation (unbiased) & 0.440953384883765 \tabularnewline
Standard Deviation (biased) & 0.43846912069357 \tabularnewline
Coefficient of Variation (unbiased) & 0.0676460419799277 \tabularnewline
Coefficient of Variation (biased) & 0.0672649344854396 \tabularnewline
Mean Squared Error (MSE versus 0) & 42.6836101123596 \tabularnewline
Mean Squared Error (MSE versus Mean) & 0.192255169801793 \tabularnewline
Mean Absolute Deviation from Mean (MAD Mean) & 0.363948996338846 \tabularnewline
Mean Absolute Deviation from Median (MAD Median) & 0.363820224719101 \tabularnewline
Median Absolute Deviation from Mean & 0.308539325842696 \tabularnewline
Median Absolute Deviation from Median & 0.31 \tabularnewline
Mean Squared Deviation from Mean & 0.192255169801793 \tabularnewline
Mean Squared Deviation from Median & 0.192386516853933 \tabularnewline
Interquartile Difference (Weighted Average at Xnp) & 0.6125 \tabularnewline
Interquartile Difference (Weighted Average at X(n+1)p) & 0.630000000000001 \tabularnewline
Interquartile Difference (Empirical Distribution Function) & 0.62 \tabularnewline
Interquartile Difference (Empirical Distribution Function - Averaging) & 0.62 \tabularnewline
Interquartile Difference (Empirical Distribution Function - Interpolation) & 0.62 \tabularnewline
Interquartile Difference (Closest Observation) & 0.62 \tabularnewline
Interquartile Difference (True Basic - Statistics Graphics Toolkit) & 0.630000000000001 \tabularnewline
Interquartile Difference (MS Excel (old versions)) & 0.630000000000001 \tabularnewline
Semi Interquartile Difference (Weighted Average at Xnp) & 0.30625 \tabularnewline
Semi Interquartile Difference (Weighted Average at X(n+1)p) & 0.315 \tabularnewline
Semi Interquartile Difference (Empirical Distribution Function) & 0.31 \tabularnewline
Semi Interquartile Difference (Empirical Distribution Function - Averaging) & 0.31 \tabularnewline
Semi Interquartile Difference (Empirical Distribution Function - Interpolation) & 0.31 \tabularnewline
Semi Interquartile Difference (Closest Observation) & 0.31 \tabularnewline
Semi Interquartile Difference (True Basic - Statistics Graphics Toolkit) & 0.315 \tabularnewline
Semi Interquartile Difference (MS Excel (old versions)) & 0.315 \tabularnewline
Coefficient of Quartile Variation (Weighted Average at Xnp) & 0.0472152630564656 \tabularnewline
Coefficient of Quartile Variation (Weighted Average at X(n+1)p) & 0.048498845265589 \tabularnewline
Coefficient of Quartile Variation (Empirical Distribution Function) & 0.0477657935285054 \tabularnewline
Coefficient of Quartile Variation (Empirical Distribution Function - Averaging) & 0.0477657935285054 \tabularnewline
Coefficient of Quartile Variation (Empirical Distribution Function - Interpolation) & 0.0477657935285054 \tabularnewline
Coefficient of Quartile Variation (Closest Observation) & 0.0477657935285054 \tabularnewline
Coefficient of Quartile Variation (True Basic - Statistics Graphics Toolkit) & 0.048498845265589 \tabularnewline
Coefficient of Quartile Variation (MS Excel (old versions)) & 0.048498845265589 \tabularnewline
Number of all Pairs of Observations & 3916 \tabularnewline
Squared Differences between all Pairs of Observations & 0.388879775280899 \tabularnewline
Mean Absolute Differences between all Pairs of Observations & 0.50396322778345 \tabularnewline
Gini Mean Difference & 0.503963227783452 \tabularnewline
Leik Measure of Dispersion & 0.505341486919527 \tabularnewline
Index of Diversity & 0.988713207062794 \tabularnewline
Index of Qualitative Variation & 0.99994858441578 \tabularnewline
Coefficient of Dispersion & 0.055734915212687 \tabularnewline
Observations & 89 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=122458&T=1

[TABLE]
[ROW][C]Variability - Ungrouped Data[/C][/ROW]
[ROW][C]Absolute range[/C][C]2.2[/C][/ROW]
[ROW][C]Relative range (unbiased)[/C][C]4.98918950487231[/C][/ROW]
[ROW][C]Relative range (biased)[/C][C]5.01745709371743[/C][/ROW]
[ROW][C]Variance (unbiased)[/C][C]0.19443988764045[/C][/ROW]
[ROW][C]Variance (biased)[/C][C]0.192255169801793[/C][/ROW]
[ROW][C]Standard Deviation (unbiased)[/C][C]0.440953384883765[/C][/ROW]
[ROW][C]Standard Deviation (biased)[/C][C]0.43846912069357[/C][/ROW]
[ROW][C]Coefficient of Variation (unbiased)[/C][C]0.0676460419799277[/C][/ROW]
[ROW][C]Coefficient of Variation (biased)[/C][C]0.0672649344854396[/C][/ROW]
[ROW][C]Mean Squared Error (MSE versus 0)[/C][C]42.6836101123596[/C][/ROW]
[ROW][C]Mean Squared Error (MSE versus Mean)[/C][C]0.192255169801793[/C][/ROW]
[ROW][C]Mean Absolute Deviation from Mean (MAD Mean)[/C][C]0.363948996338846[/C][/ROW]
[ROW][C]Mean Absolute Deviation from Median (MAD Median)[/C][C]0.363820224719101[/C][/ROW]
[ROW][C]Median Absolute Deviation from Mean[/C][C]0.308539325842696[/C][/ROW]
[ROW][C]Median Absolute Deviation from Median[/C][C]0.31[/C][/ROW]
[ROW][C]Mean Squared Deviation from Mean[/C][C]0.192255169801793[/C][/ROW]
[ROW][C]Mean Squared Deviation from Median[/C][C]0.192386516853933[/C][/ROW]
[ROW][C]Interquartile Difference (Weighted Average at Xnp)[/C][C]0.6125[/C][/ROW]
[ROW][C]Interquartile Difference (Weighted Average at X(n+1)p)[/C][C]0.630000000000001[/C][/ROW]
[ROW][C]Interquartile Difference (Empirical Distribution Function)[/C][C]0.62[/C][/ROW]
[ROW][C]Interquartile Difference (Empirical Distribution Function - Averaging)[/C][C]0.62[/C][/ROW]
[ROW][C]Interquartile Difference (Empirical Distribution Function - Interpolation)[/C][C]0.62[/C][/ROW]
[ROW][C]Interquartile Difference (Closest Observation)[/C][C]0.62[/C][/ROW]
[ROW][C]Interquartile Difference (True Basic - Statistics Graphics Toolkit)[/C][C]0.630000000000001[/C][/ROW]
[ROW][C]Interquartile Difference (MS Excel (old versions))[/C][C]0.630000000000001[/C][/ROW]
[ROW][C]Semi Interquartile Difference (Weighted Average at Xnp)[/C][C]0.30625[/C][/ROW]
[ROW][C]Semi Interquartile Difference (Weighted Average at X(n+1)p)[/C][C]0.315[/C][/ROW]
[ROW][C]Semi Interquartile Difference (Empirical Distribution Function)[/C][C]0.31[/C][/ROW]
[ROW][C]Semi Interquartile Difference (Empirical Distribution Function - Averaging)[/C][C]0.31[/C][/ROW]
[ROW][C]Semi Interquartile Difference (Empirical Distribution Function - Interpolation)[/C][C]0.31[/C][/ROW]
[ROW][C]Semi Interquartile Difference (Closest Observation)[/C][C]0.31[/C][/ROW]
[ROW][C]Semi Interquartile Difference (True Basic - Statistics Graphics Toolkit)[/C][C]0.315[/C][/ROW]
[ROW][C]Semi Interquartile Difference (MS Excel (old versions))[/C][C]0.315[/C][/ROW]
[ROW][C]Coefficient of Quartile Variation (Weighted Average at Xnp)[/C][C]0.0472152630564656[/C][/ROW]
[ROW][C]Coefficient of Quartile Variation (Weighted Average at X(n+1)p)[/C][C]0.048498845265589[/C][/ROW]
[ROW][C]Coefficient of Quartile Variation (Empirical Distribution Function)[/C][C]0.0477657935285054[/C][/ROW]
[ROW][C]Coefficient of Quartile Variation (Empirical Distribution Function - Averaging)[/C][C]0.0477657935285054[/C][/ROW]
[ROW][C]Coefficient of Quartile Variation (Empirical Distribution Function - Interpolation)[/C][C]0.0477657935285054[/C][/ROW]
[ROW][C]Coefficient of Quartile Variation (Closest Observation)[/C][C]0.0477657935285054[/C][/ROW]
[ROW][C]Coefficient of Quartile Variation (True Basic - Statistics Graphics Toolkit)[/C][C]0.048498845265589[/C][/ROW]
[ROW][C]Coefficient of Quartile Variation (MS Excel (old versions))[/C][C]0.048498845265589[/C][/ROW]
[ROW][C]Number of all Pairs of Observations[/C][C]3916[/C][/ROW]
[ROW][C]Squared Differences between all Pairs of Observations[/C][C]0.388879775280899[/C][/ROW]
[ROW][C]Mean Absolute Differences between all Pairs of Observations[/C][C]0.50396322778345[/C][/ROW]
[ROW][C]Gini Mean Difference[/C][C]0.503963227783452[/C][/ROW]
[ROW][C]Leik Measure of Dispersion[/C][C]0.505341486919527[/C][/ROW]
[ROW][C]Index of Diversity[/C][C]0.988713207062794[/C][/ROW]
[ROW][C]Index of Qualitative Variation[/C][C]0.99994858441578[/C][/ROW]
[ROW][C]Coefficient of Dispersion[/C][C]0.055734915212687[/C][/ROW]
[ROW][C]Observations[/C][C]89[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=122458&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=122458&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 range2.2
Relative range (unbiased)4.98918950487231
Relative range (biased)5.01745709371743
Variance (unbiased)0.19443988764045
Variance (biased)0.192255169801793
Standard Deviation (unbiased)0.440953384883765
Standard Deviation (biased)0.43846912069357
Coefficient of Variation (unbiased)0.0676460419799277
Coefficient of Variation (biased)0.0672649344854396
Mean Squared Error (MSE versus 0)42.6836101123596
Mean Squared Error (MSE versus Mean)0.192255169801793
Mean Absolute Deviation from Mean (MAD Mean)0.363948996338846
Mean Absolute Deviation from Median (MAD Median)0.363820224719101
Median Absolute Deviation from Mean0.308539325842696
Median Absolute Deviation from Median0.31
Mean Squared Deviation from Mean0.192255169801793
Mean Squared Deviation from Median0.192386516853933
Interquartile Difference (Weighted Average at Xnp)0.6125
Interquartile Difference (Weighted Average at X(n+1)p)0.630000000000001
Interquartile Difference (Empirical Distribution Function)0.62
Interquartile Difference (Empirical Distribution Function - Averaging)0.62
Interquartile Difference (Empirical Distribution Function - Interpolation)0.62
Interquartile Difference (Closest Observation)0.62
Interquartile Difference (True Basic - Statistics Graphics Toolkit)0.630000000000001
Interquartile Difference (MS Excel (old versions))0.630000000000001
Semi Interquartile Difference (Weighted Average at Xnp)0.30625
Semi Interquartile Difference (Weighted Average at X(n+1)p)0.315
Semi Interquartile Difference (Empirical Distribution Function)0.31
Semi Interquartile Difference (Empirical Distribution Function - Averaging)0.31
Semi Interquartile Difference (Empirical Distribution Function - Interpolation)0.31
Semi Interquartile Difference (Closest Observation)0.31
Semi Interquartile Difference (True Basic - Statistics Graphics Toolkit)0.315
Semi Interquartile Difference (MS Excel (old versions))0.315
Coefficient of Quartile Variation (Weighted Average at Xnp)0.0472152630564656
Coefficient of Quartile Variation (Weighted Average at X(n+1)p)0.048498845265589
Coefficient of Quartile Variation (Empirical Distribution Function)0.0477657935285054
Coefficient of Quartile Variation (Empirical Distribution Function - Averaging)0.0477657935285054
Coefficient of Quartile Variation (Empirical Distribution Function - Interpolation)0.0477657935285054
Coefficient of Quartile Variation (Closest Observation)0.0477657935285054
Coefficient of Quartile Variation (True Basic - Statistics Graphics Toolkit)0.048498845265589
Coefficient of Quartile Variation (MS Excel (old versions))0.048498845265589
Number of all Pairs of Observations3916
Squared Differences between all Pairs of Observations0.388879775280899
Mean Absolute Differences between all Pairs of Observations0.50396322778345
Gini Mean Difference0.503963227783452
Leik Measure of Dispersion0.505341486919527
Index of Diversity0.988713207062794
Index of Qualitative Variation0.99994858441578
Coefficient of Dispersion0.055734915212687
Observations89



Parameters (Session):
par1 = 48 ; par2 = 1 ; par3 = 0 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;
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')