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 08:27:21 -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/t1322486896xy2wsv7mp2pst1k.htm/, Retrieved Fri, 29 Mar 2024 06:48:55 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=147711, Retrieved Fri, 29 Mar 2024 06:48:55 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsKDGP2W83
Estimated Impact68
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Variability] [] [2011-11-28 13:27:21] [c81f0c87bb000ca3e7f952ee43cfaf8d] [Current]
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Dataseries X:
99,96
100,21
100,37
101,11
101,04
101,02
101,02
101,11
100,96
101,27
101,01
101,07
101,07
101,07
101,24
101,29
101,67
101,66
101,66
101,66
101,8
102,32
102,38
102,4
102,39
102,78
102,81
102,82
102,96
102,98
102,98
103,03
103,26
103,47
103,58
103,52
103,52
103,52
103,54
103,74
103,94
103,9
103,9
103,9
103,87
104,51
104,82
104,87
104,87
105,13
105,22
105,02
104,7
104,76
104,76
104,57
104,64
104,72
104,49
104,42




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=147711&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=147711&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=147711&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 range5.26
Relative range (unbiased)3.48644881963972
Relative range (biased)3.51587085028715
Variance (unbiased)2.27617107344633
Variance (biased)2.23823488888889
Standard Deviation (unbiased)1.50869847002187
Standard Deviation (biased)1.49607315626238
Coefficient of Variation (unbiased)0.0146658784438347
Coefficient of Variation (biased)0.0145431492699202
Mean Squared Error (MSE versus 0)10584.7494566667
Mean Squared Error (MSE versus Mean)2.23823488888889
Mean Absolute Deviation from Mean (MAD Mean)1.30757777777778
Mean Absolute Deviation from Median (MAD Median)1.301
Median Absolute Deviation from Mean1.565
Median Absolute Deviation from Median1.47499999999999
Mean Squared Deviation from Mean2.23823488888889
Mean Squared Deviation from Median2.25004333333334
Interquartile Difference (Weighted Average at Xnp)2.67
Interquartile Difference (Weighted Average at X(n+1)p)3.02499999999999
Interquartile Difference (Empirical Distribution Function)2.67
Interquartile Difference (Empirical Distribution Function - Averaging)2.90000000000001
Interquartile Difference (Empirical Distribution Function - Interpolation)2.77500000000001
Interquartile Difference (Closest Observation)2.67
Interquartile Difference (True Basic - Statistics Graphics Toolkit)2.77500000000001
Interquartile Difference (MS Excel (old versions))3.15000000000001
Semi Interquartile Difference (Weighted Average at Xnp)1.335
Semi Interquartile Difference (Weighted Average at X(n+1)p)1.5125
Semi Interquartile Difference (Empirical Distribution Function)1.335
Semi Interquartile Difference (Empirical Distribution Function - Averaging)1.45
Semi Interquartile Difference (Empirical Distribution Function - Interpolation)1.3875
Semi Interquartile Difference (Closest Observation)1.335
Semi Interquartile Difference (True Basic - Statistics Graphics Toolkit)1.3875
Semi Interquartile Difference (MS Excel (old versions))1.575
Coefficient of Quartile Variation (Weighted Average at Xnp)0.0130110618390917
Coefficient of Quartile Variation (Weighted Average at X(n+1)p)0.0147148242733795
Coefficient of Quartile Variation (Empirical Distribution Function)0.0130110618390917
Coefficient of Quartile Variation (Empirical Distribution Function - Averaging)0.0141146695220481
Coefficient of Quartile Variation (Empirical Distribution Function - Interpolation)0.0135138425576469
Coefficient of Quartile Variation (Closest Observation)0.0130110618390917
Coefficient of Quartile Variation (True Basic - Statistics Graphics Toolkit)0.0135138425576469
Coefficient of Quartile Variation (MS Excel (old versions))0.0153143079391317
Number of all Pairs of Observations1770
Squared Differences between all Pairs of Observations4.55234214689266
Mean Absolute Differences between all Pairs of Observations1.74257627118644
Gini Mean Difference1.74257627118643
Leik Measure of Dispersion0.507940147491579
Index of Diversity0.983329808280155
Index of Qualitative Variation0.999996415200158
Coefficient of Dispersion0.0126973953950066
Observations60

\begin{tabular}{lllllllll}
\hline
Variability - Ungrouped Data \tabularnewline
Absolute range & 5.26 \tabularnewline
Relative range (unbiased) & 3.48644881963972 \tabularnewline
Relative range (biased) & 3.51587085028715 \tabularnewline
Variance (unbiased) & 2.27617107344633 \tabularnewline
Variance (biased) & 2.23823488888889 \tabularnewline
Standard Deviation (unbiased) & 1.50869847002187 \tabularnewline
Standard Deviation (biased) & 1.49607315626238 \tabularnewline
Coefficient of Variation (unbiased) & 0.0146658784438347 \tabularnewline
Coefficient of Variation (biased) & 0.0145431492699202 \tabularnewline
Mean Squared Error (MSE versus 0) & 10584.7494566667 \tabularnewline
Mean Squared Error (MSE versus Mean) & 2.23823488888889 \tabularnewline
Mean Absolute Deviation from Mean (MAD Mean) & 1.30757777777778 \tabularnewline
Mean Absolute Deviation from Median (MAD Median) & 1.301 \tabularnewline
Median Absolute Deviation from Mean & 1.565 \tabularnewline
Median Absolute Deviation from Median & 1.47499999999999 \tabularnewline
Mean Squared Deviation from Mean & 2.23823488888889 \tabularnewline
Mean Squared Deviation from Median & 2.25004333333334 \tabularnewline
Interquartile Difference (Weighted Average at Xnp) & 2.67 \tabularnewline
Interquartile Difference (Weighted Average at X(n+1)p) & 3.02499999999999 \tabularnewline
Interquartile Difference (Empirical Distribution Function) & 2.67 \tabularnewline
Interquartile Difference (Empirical Distribution Function - Averaging) & 2.90000000000001 \tabularnewline
Interquartile Difference (Empirical Distribution Function - Interpolation) & 2.77500000000001 \tabularnewline
Interquartile Difference (Closest Observation) & 2.67 \tabularnewline
Interquartile Difference (True Basic - Statistics Graphics Toolkit) & 2.77500000000001 \tabularnewline
Interquartile Difference (MS Excel (old versions)) & 3.15000000000001 \tabularnewline
Semi Interquartile Difference (Weighted Average at Xnp) & 1.335 \tabularnewline
Semi Interquartile Difference (Weighted Average at X(n+1)p) & 1.5125 \tabularnewline
Semi Interquartile Difference (Empirical Distribution Function) & 1.335 \tabularnewline
Semi Interquartile Difference (Empirical Distribution Function - Averaging) & 1.45 \tabularnewline
Semi Interquartile Difference (Empirical Distribution Function - Interpolation) & 1.3875 \tabularnewline
Semi Interquartile Difference (Closest Observation) & 1.335 \tabularnewline
Semi Interquartile Difference (True Basic - Statistics Graphics Toolkit) & 1.3875 \tabularnewline
Semi Interquartile Difference (MS Excel (old versions)) & 1.575 \tabularnewline
Coefficient of Quartile Variation (Weighted Average at Xnp) & 0.0130110618390917 \tabularnewline
Coefficient of Quartile Variation (Weighted Average at X(n+1)p) & 0.0147148242733795 \tabularnewline
Coefficient of Quartile Variation (Empirical Distribution Function) & 0.0130110618390917 \tabularnewline
Coefficient of Quartile Variation (Empirical Distribution Function - Averaging) & 0.0141146695220481 \tabularnewline
Coefficient of Quartile Variation (Empirical Distribution Function - Interpolation) & 0.0135138425576469 \tabularnewline
Coefficient of Quartile Variation (Closest Observation) & 0.0130110618390917 \tabularnewline
Coefficient of Quartile Variation (True Basic - Statistics Graphics Toolkit) & 0.0135138425576469 \tabularnewline
Coefficient of Quartile Variation (MS Excel (old versions)) & 0.0153143079391317 \tabularnewline
Number of all Pairs of Observations & 1770 \tabularnewline
Squared Differences between all Pairs of Observations & 4.55234214689266 \tabularnewline
Mean Absolute Differences between all Pairs of Observations & 1.74257627118644 \tabularnewline
Gini Mean Difference & 1.74257627118643 \tabularnewline
Leik Measure of Dispersion & 0.507940147491579 \tabularnewline
Index of Diversity & 0.983329808280155 \tabularnewline
Index of Qualitative Variation & 0.999996415200158 \tabularnewline
Coefficient of Dispersion & 0.0126973953950066 \tabularnewline
Observations & 60 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=147711&T=1

[TABLE]
[ROW][C]Variability - Ungrouped Data[/C][/ROW]
[ROW][C]Absolute range[/C][C]5.26[/C][/ROW]
[ROW][C]Relative range (unbiased)[/C][C]3.48644881963972[/C][/ROW]
[ROW][C]Relative range (biased)[/C][C]3.51587085028715[/C][/ROW]
[ROW][C]Variance (unbiased)[/C][C]2.27617107344633[/C][/ROW]
[ROW][C]Variance (biased)[/C][C]2.23823488888889[/C][/ROW]
[ROW][C]Standard Deviation (unbiased)[/C][C]1.50869847002187[/C][/ROW]
[ROW][C]Standard Deviation (biased)[/C][C]1.49607315626238[/C][/ROW]
[ROW][C]Coefficient of Variation (unbiased)[/C][C]0.0146658784438347[/C][/ROW]
[ROW][C]Coefficient of Variation (biased)[/C][C]0.0145431492699202[/C][/ROW]
[ROW][C]Mean Squared Error (MSE versus 0)[/C][C]10584.7494566667[/C][/ROW]
[ROW][C]Mean Squared Error (MSE versus Mean)[/C][C]2.23823488888889[/C][/ROW]
[ROW][C]Mean Absolute Deviation from Mean (MAD Mean)[/C][C]1.30757777777778[/C][/ROW]
[ROW][C]Mean Absolute Deviation from Median (MAD Median)[/C][C]1.301[/C][/ROW]
[ROW][C]Median Absolute Deviation from Mean[/C][C]1.565[/C][/ROW]
[ROW][C]Median Absolute Deviation from Median[/C][C]1.47499999999999[/C][/ROW]
[ROW][C]Mean Squared Deviation from Mean[/C][C]2.23823488888889[/C][/ROW]
[ROW][C]Mean Squared Deviation from Median[/C][C]2.25004333333334[/C][/ROW]
[ROW][C]Interquartile Difference (Weighted Average at Xnp)[/C][C]2.67[/C][/ROW]
[ROW][C]Interquartile Difference (Weighted Average at X(n+1)p)[/C][C]3.02499999999999[/C][/ROW]
[ROW][C]Interquartile Difference (Empirical Distribution Function)[/C][C]2.67[/C][/ROW]
[ROW][C]Interquartile Difference (Empirical Distribution Function - Averaging)[/C][C]2.90000000000001[/C][/ROW]
[ROW][C]Interquartile Difference (Empirical Distribution Function - Interpolation)[/C][C]2.77500000000001[/C][/ROW]
[ROW][C]Interquartile Difference (Closest Observation)[/C][C]2.67[/C][/ROW]
[ROW][C]Interquartile Difference (True Basic - Statistics Graphics Toolkit)[/C][C]2.77500000000001[/C][/ROW]
[ROW][C]Interquartile Difference (MS Excel (old versions))[/C][C]3.15000000000001[/C][/ROW]
[ROW][C]Semi Interquartile Difference (Weighted Average at Xnp)[/C][C]1.335[/C][/ROW]
[ROW][C]Semi Interquartile Difference (Weighted Average at X(n+1)p)[/C][C]1.5125[/C][/ROW]
[ROW][C]Semi Interquartile Difference (Empirical Distribution Function)[/C][C]1.335[/C][/ROW]
[ROW][C]Semi Interquartile Difference (Empirical Distribution Function - Averaging)[/C][C]1.45[/C][/ROW]
[ROW][C]Semi Interquartile Difference (Empirical Distribution Function - Interpolation)[/C][C]1.3875[/C][/ROW]
[ROW][C]Semi Interquartile Difference (Closest Observation)[/C][C]1.335[/C][/ROW]
[ROW][C]Semi Interquartile Difference (True Basic - Statistics Graphics Toolkit)[/C][C]1.3875[/C][/ROW]
[ROW][C]Semi Interquartile Difference (MS Excel (old versions))[/C][C]1.575[/C][/ROW]
[ROW][C]Coefficient of Quartile Variation (Weighted Average at Xnp)[/C][C]0.0130110618390917[/C][/ROW]
[ROW][C]Coefficient of Quartile Variation (Weighted Average at X(n+1)p)[/C][C]0.0147148242733795[/C][/ROW]
[ROW][C]Coefficient of Quartile Variation (Empirical Distribution Function)[/C][C]0.0130110618390917[/C][/ROW]
[ROW][C]Coefficient of Quartile Variation (Empirical Distribution Function - Averaging)[/C][C]0.0141146695220481[/C][/ROW]
[ROW][C]Coefficient of Quartile Variation (Empirical Distribution Function - Interpolation)[/C][C]0.0135138425576469[/C][/ROW]
[ROW][C]Coefficient of Quartile Variation (Closest Observation)[/C][C]0.0130110618390917[/C][/ROW]
[ROW][C]Coefficient of Quartile Variation (True Basic - Statistics Graphics Toolkit)[/C][C]0.0135138425576469[/C][/ROW]
[ROW][C]Coefficient of Quartile Variation (MS Excel (old versions))[/C][C]0.0153143079391317[/C][/ROW]
[ROW][C]Number of all Pairs of Observations[/C][C]1770[/C][/ROW]
[ROW][C]Squared Differences between all Pairs of Observations[/C][C]4.55234214689266[/C][/ROW]
[ROW][C]Mean Absolute Differences between all Pairs of Observations[/C][C]1.74257627118644[/C][/ROW]
[ROW][C]Gini Mean Difference[/C][C]1.74257627118643[/C][/ROW]
[ROW][C]Leik Measure of Dispersion[/C][C]0.507940147491579[/C][/ROW]
[ROW][C]Index of Diversity[/C][C]0.983329808280155[/C][/ROW]
[ROW][C]Index of Qualitative Variation[/C][C]0.999996415200158[/C][/ROW]
[ROW][C]Coefficient of Dispersion[/C][C]0.0126973953950066[/C][/ROW]
[ROW][C]Observations[/C][C]60[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=147711&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=147711&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 range5.26
Relative range (unbiased)3.48644881963972
Relative range (biased)3.51587085028715
Variance (unbiased)2.27617107344633
Variance (biased)2.23823488888889
Standard Deviation (unbiased)1.50869847002187
Standard Deviation (biased)1.49607315626238
Coefficient of Variation (unbiased)0.0146658784438347
Coefficient of Variation (biased)0.0145431492699202
Mean Squared Error (MSE versus 0)10584.7494566667
Mean Squared Error (MSE versus Mean)2.23823488888889
Mean Absolute Deviation from Mean (MAD Mean)1.30757777777778
Mean Absolute Deviation from Median (MAD Median)1.301
Median Absolute Deviation from Mean1.565
Median Absolute Deviation from Median1.47499999999999
Mean Squared Deviation from Mean2.23823488888889
Mean Squared Deviation from Median2.25004333333334
Interquartile Difference (Weighted Average at Xnp)2.67
Interquartile Difference (Weighted Average at X(n+1)p)3.02499999999999
Interquartile Difference (Empirical Distribution Function)2.67
Interquartile Difference (Empirical Distribution Function - Averaging)2.90000000000001
Interquartile Difference (Empirical Distribution Function - Interpolation)2.77500000000001
Interquartile Difference (Closest Observation)2.67
Interquartile Difference (True Basic - Statistics Graphics Toolkit)2.77500000000001
Interquartile Difference (MS Excel (old versions))3.15000000000001
Semi Interquartile Difference (Weighted Average at Xnp)1.335
Semi Interquartile Difference (Weighted Average at X(n+1)p)1.5125
Semi Interquartile Difference (Empirical Distribution Function)1.335
Semi Interquartile Difference (Empirical Distribution Function - Averaging)1.45
Semi Interquartile Difference (Empirical Distribution Function - Interpolation)1.3875
Semi Interquartile Difference (Closest Observation)1.335
Semi Interquartile Difference (True Basic - Statistics Graphics Toolkit)1.3875
Semi Interquartile Difference (MS Excel (old versions))1.575
Coefficient of Quartile Variation (Weighted Average at Xnp)0.0130110618390917
Coefficient of Quartile Variation (Weighted Average at X(n+1)p)0.0147148242733795
Coefficient of Quartile Variation (Empirical Distribution Function)0.0130110618390917
Coefficient of Quartile Variation (Empirical Distribution Function - Averaging)0.0141146695220481
Coefficient of Quartile Variation (Empirical Distribution Function - Interpolation)0.0135138425576469
Coefficient of Quartile Variation (Closest Observation)0.0130110618390917
Coefficient of Quartile Variation (True Basic - Statistics Graphics Toolkit)0.0135138425576469
Coefficient of Quartile Variation (MS Excel (old versions))0.0153143079391317
Number of all Pairs of Observations1770
Squared Differences between all Pairs of Observations4.55234214689266
Mean Absolute Differences between all Pairs of Observations1.74257627118644
Gini Mean Difference1.74257627118643
Leik Measure of Dispersion0.507940147491579
Index of Diversity0.983329808280155
Index of Qualitative Variation0.999996415200158
Coefficient of Dispersion0.0126973953950066
Observations60



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')