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 12:22:18 -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/t13225009671bruyg81x2ydrz8.htm/, Retrieved Fri, 29 Mar 2024 07:18:27 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=147902, Retrieved Fri, 29 Mar 2024 07:18:27 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsKDGP2W83
Estimated Impact103
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Histogram] [Frequentietabel I...] [2011-11-28 12:49:41] [77b79fca1322508fd7e2d5b3e9715c12]
- RMPD  [Standard Deviation Plot] [Standard Deviatio...] [2011-11-28 16:08:27] [77b79fca1322508fd7e2d5b3e9715c12]
- RMPD      [Variability] [Opdracht3Opgave8] [2011-11-28 17:22:18] [76bda0bb7d6f469fbad64fdea2dd989f] [Current]
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Dataseries X:
100,32
100,33
100,35
100,38
100,44
100,47
100,47
100,48
100,48
100,49
100,52
100,53
100,62
100,89
100,92
100,93
100,97
100,98
101,01
101,02
101,07
101,1
101,11
101,19
101,31
101,52
101,56
101,61
101,65
101,66
101,75
101,83
101,98
102,06
102,07
102,1
102,42
102,91
102,91
103,11
103,14
103,14
103,23
103,23
103,26
103,3
103,32
103,44
103,54
103,86
103,88
103,88
103,89
103,98
103,98
103,98
104,24
104,29
104,29
104,31
104,41
104,54
104,67
104,8




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time0 seconds
R Server'Gertrude Mary Cox' @ cox.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 & 0 seconds \tabularnewline
R Server & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=147902&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]0 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=147902&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=147902&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 time0 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net







Variability - Ungrouped Data
Absolute range4.48
Relative range (unbiased)3.09136548577584
Relative range (biased)3.11580353789382
Variance (unbiased)2.10017420634921
Variance (biased)2.067358984375
Standard Deviation (unbiased)1.44919778027335
Standard Deviation (biased)1.43783134768129
Coefficient of Variation (unbiased)0.0141771563250895
Coefficient of Variation (biased)0.0140659612253524
Mean Squared Error (MSE versus 0)10451.123534375
Mean Squared Error (MSE versus Mean)2.067358984375
Mean Absolute Deviation from Mean (MAD Mean)1.305390625
Mean Absolute Deviation from Median (MAD Median)1.284375
Median Absolute Deviation from Mean1.270625
Median Absolute Deviation from Median1.34
Mean Squared Deviation from Mean2.067358984375
Mean Squared Deviation from Median2.166978125
Interquartile Difference (Weighted Average at Xnp)2.50999999999999
Interquartile Difference (Weighted Average at X(n+1)p)2.575
Interquartile Difference (Empirical Distribution Function)2.50999999999999
Interquartile Difference (Empirical Distribution Function - Averaging)2.54000000000001
Interquartile Difference (Empirical Distribution Function - Interpolation)2.505
Interquartile Difference (Closest Observation)2.50999999999999
Interquartile Difference (True Basic - Statistics Graphics Toolkit)2.50500000000001
Interquartile Difference (MS Excel (old versions))2.61
Semi Interquartile Difference (Weighted Average at Xnp)1.255
Semi Interquartile Difference (Weighted Average at X(n+1)p)1.2875
Semi Interquartile Difference (Empirical Distribution Function)1.255
Semi Interquartile Difference (Empirical Distribution Function - Averaging)1.27
Semi Interquartile Difference (Empirical Distribution Function - Interpolation)1.2525
Semi Interquartile Difference (Closest Observation)1.255
Semi Interquartile Difference (True Basic - Statistics Graphics Toolkit)1.2525
Semi Interquartile Difference (MS Excel (old versions))1.305
Coefficient of Quartile Variation (Weighted Average at Xnp)0.0122816460341537
Coefficient of Quartile Variation (Weighted Average at X(n+1)p)0.0125944584382872
Coefficient of Quartile Variation (Empirical Distribution Function)0.0122816460341537
Coefficient of Quartile Variation (Empirical Distribution Function - Averaging)0.012424183134416
Coefficient of Quartile Variation (Empirical Distribution Function - Interpolation)0.0122538828421181
Coefficient of Quartile Variation (Closest Observation)0.0122816460341537
Coefficient of Quartile Variation (True Basic - Statistics Graphics Toolkit)0.0122538828421182
Coefficient of Quartile Variation (MS Excel (old versions))0.0127647087592312
Number of all Pairs of Observations2016
Squared Differences between all Pairs of Observations4.2003484126984
Mean Absolute Differences between all Pairs of Observations1.66420634920635
Gini Mean Difference1.66420634920635
Leik Measure of Dispersion0.508172730571586
Index of Diversity0.984371908573981
Index of Qualitative Variation0.999996859503727
Coefficient of Dispersion0.0128098780727148
Observations64

\begin{tabular}{lllllllll}
\hline
Variability - Ungrouped Data \tabularnewline
Absolute range & 4.48 \tabularnewline
Relative range (unbiased) & 3.09136548577584 \tabularnewline
Relative range (biased) & 3.11580353789382 \tabularnewline
Variance (unbiased) & 2.10017420634921 \tabularnewline
Variance (biased) & 2.067358984375 \tabularnewline
Standard Deviation (unbiased) & 1.44919778027335 \tabularnewline
Standard Deviation (biased) & 1.43783134768129 \tabularnewline
Coefficient of Variation (unbiased) & 0.0141771563250895 \tabularnewline
Coefficient of Variation (biased) & 0.0140659612253524 \tabularnewline
Mean Squared Error (MSE versus 0) & 10451.123534375 \tabularnewline
Mean Squared Error (MSE versus Mean) & 2.067358984375 \tabularnewline
Mean Absolute Deviation from Mean (MAD Mean) & 1.305390625 \tabularnewline
Mean Absolute Deviation from Median (MAD Median) & 1.284375 \tabularnewline
Median Absolute Deviation from Mean & 1.270625 \tabularnewline
Median Absolute Deviation from Median & 1.34 \tabularnewline
Mean Squared Deviation from Mean & 2.067358984375 \tabularnewline
Mean Squared Deviation from Median & 2.166978125 \tabularnewline
Interquartile Difference (Weighted Average at Xnp) & 2.50999999999999 \tabularnewline
Interquartile Difference (Weighted Average at X(n+1)p) & 2.575 \tabularnewline
Interquartile Difference (Empirical Distribution Function) & 2.50999999999999 \tabularnewline
Interquartile Difference (Empirical Distribution Function - Averaging) & 2.54000000000001 \tabularnewline
Interquartile Difference (Empirical Distribution Function - Interpolation) & 2.505 \tabularnewline
Interquartile Difference (Closest Observation) & 2.50999999999999 \tabularnewline
Interquartile Difference (True Basic - Statistics Graphics Toolkit) & 2.50500000000001 \tabularnewline
Interquartile Difference (MS Excel (old versions)) & 2.61 \tabularnewline
Semi Interquartile Difference (Weighted Average at Xnp) & 1.255 \tabularnewline
Semi Interquartile Difference (Weighted Average at X(n+1)p) & 1.2875 \tabularnewline
Semi Interquartile Difference (Empirical Distribution Function) & 1.255 \tabularnewline
Semi Interquartile Difference (Empirical Distribution Function - Averaging) & 1.27 \tabularnewline
Semi Interquartile Difference (Empirical Distribution Function - Interpolation) & 1.2525 \tabularnewline
Semi Interquartile Difference (Closest Observation) & 1.255 \tabularnewline
Semi Interquartile Difference (True Basic - Statistics Graphics Toolkit) & 1.2525 \tabularnewline
Semi Interquartile Difference (MS Excel (old versions)) & 1.305 \tabularnewline
Coefficient of Quartile Variation (Weighted Average at Xnp) & 0.0122816460341537 \tabularnewline
Coefficient of Quartile Variation (Weighted Average at X(n+1)p) & 0.0125944584382872 \tabularnewline
Coefficient of Quartile Variation (Empirical Distribution Function) & 0.0122816460341537 \tabularnewline
Coefficient of Quartile Variation (Empirical Distribution Function - Averaging) & 0.012424183134416 \tabularnewline
Coefficient of Quartile Variation (Empirical Distribution Function - Interpolation) & 0.0122538828421181 \tabularnewline
Coefficient of Quartile Variation (Closest Observation) & 0.0122816460341537 \tabularnewline
Coefficient of Quartile Variation (True Basic - Statistics Graphics Toolkit) & 0.0122538828421182 \tabularnewline
Coefficient of Quartile Variation (MS Excel (old versions)) & 0.0127647087592312 \tabularnewline
Number of all Pairs of Observations & 2016 \tabularnewline
Squared Differences between all Pairs of Observations & 4.2003484126984 \tabularnewline
Mean Absolute Differences between all Pairs of Observations & 1.66420634920635 \tabularnewline
Gini Mean Difference & 1.66420634920635 \tabularnewline
Leik Measure of Dispersion & 0.508172730571586 \tabularnewline
Index of Diversity & 0.984371908573981 \tabularnewline
Index of Qualitative Variation & 0.999996859503727 \tabularnewline
Coefficient of Dispersion & 0.0128098780727148 \tabularnewline
Observations & 64 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=147902&T=1

[TABLE]
[ROW][C]Variability - Ungrouped Data[/C][/ROW]
[ROW][C]Absolute range[/C][C]4.48[/C][/ROW]
[ROW][C]Relative range (unbiased)[/C][C]3.09136548577584[/C][/ROW]
[ROW][C]Relative range (biased)[/C][C]3.11580353789382[/C][/ROW]
[ROW][C]Variance (unbiased)[/C][C]2.10017420634921[/C][/ROW]
[ROW][C]Variance (biased)[/C][C]2.067358984375[/C][/ROW]
[ROW][C]Standard Deviation (unbiased)[/C][C]1.44919778027335[/C][/ROW]
[ROW][C]Standard Deviation (biased)[/C][C]1.43783134768129[/C][/ROW]
[ROW][C]Coefficient of Variation (unbiased)[/C][C]0.0141771563250895[/C][/ROW]
[ROW][C]Coefficient of Variation (biased)[/C][C]0.0140659612253524[/C][/ROW]
[ROW][C]Mean Squared Error (MSE versus 0)[/C][C]10451.123534375[/C][/ROW]
[ROW][C]Mean Squared Error (MSE versus Mean)[/C][C]2.067358984375[/C][/ROW]
[ROW][C]Mean Absolute Deviation from Mean (MAD Mean)[/C][C]1.305390625[/C][/ROW]
[ROW][C]Mean Absolute Deviation from Median (MAD Median)[/C][C]1.284375[/C][/ROW]
[ROW][C]Median Absolute Deviation from Mean[/C][C]1.270625[/C][/ROW]
[ROW][C]Median Absolute Deviation from Median[/C][C]1.34[/C][/ROW]
[ROW][C]Mean Squared Deviation from Mean[/C][C]2.067358984375[/C][/ROW]
[ROW][C]Mean Squared Deviation from Median[/C][C]2.166978125[/C][/ROW]
[ROW][C]Interquartile Difference (Weighted Average at Xnp)[/C][C]2.50999999999999[/C][/ROW]
[ROW][C]Interquartile Difference (Weighted Average at X(n+1)p)[/C][C]2.575[/C][/ROW]
[ROW][C]Interquartile Difference (Empirical Distribution Function)[/C][C]2.50999999999999[/C][/ROW]
[ROW][C]Interquartile Difference (Empirical Distribution Function - Averaging)[/C][C]2.54000000000001[/C][/ROW]
[ROW][C]Interquartile Difference (Empirical Distribution Function - Interpolation)[/C][C]2.505[/C][/ROW]
[ROW][C]Interquartile Difference (Closest Observation)[/C][C]2.50999999999999[/C][/ROW]
[ROW][C]Interquartile Difference (True Basic - Statistics Graphics Toolkit)[/C][C]2.50500000000001[/C][/ROW]
[ROW][C]Interquartile Difference (MS Excel (old versions))[/C][C]2.61[/C][/ROW]
[ROW][C]Semi Interquartile Difference (Weighted Average at Xnp)[/C][C]1.255[/C][/ROW]
[ROW][C]Semi Interquartile Difference (Weighted Average at X(n+1)p)[/C][C]1.2875[/C][/ROW]
[ROW][C]Semi Interquartile Difference (Empirical Distribution Function)[/C][C]1.255[/C][/ROW]
[ROW][C]Semi Interquartile Difference (Empirical Distribution Function - Averaging)[/C][C]1.27[/C][/ROW]
[ROW][C]Semi Interquartile Difference (Empirical Distribution Function - Interpolation)[/C][C]1.2525[/C][/ROW]
[ROW][C]Semi Interquartile Difference (Closest Observation)[/C][C]1.255[/C][/ROW]
[ROW][C]Semi Interquartile Difference (True Basic - Statistics Graphics Toolkit)[/C][C]1.2525[/C][/ROW]
[ROW][C]Semi Interquartile Difference (MS Excel (old versions))[/C][C]1.305[/C][/ROW]
[ROW][C]Coefficient of Quartile Variation (Weighted Average at Xnp)[/C][C]0.0122816460341537[/C][/ROW]
[ROW][C]Coefficient of Quartile Variation (Weighted Average at X(n+1)p)[/C][C]0.0125944584382872[/C][/ROW]
[ROW][C]Coefficient of Quartile Variation (Empirical Distribution Function)[/C][C]0.0122816460341537[/C][/ROW]
[ROW][C]Coefficient of Quartile Variation (Empirical Distribution Function - Averaging)[/C][C]0.012424183134416[/C][/ROW]
[ROW][C]Coefficient of Quartile Variation (Empirical Distribution Function - Interpolation)[/C][C]0.0122538828421181[/C][/ROW]
[ROW][C]Coefficient of Quartile Variation (Closest Observation)[/C][C]0.0122816460341537[/C][/ROW]
[ROW][C]Coefficient of Quartile Variation (True Basic - Statistics Graphics Toolkit)[/C][C]0.0122538828421182[/C][/ROW]
[ROW][C]Coefficient of Quartile Variation (MS Excel (old versions))[/C][C]0.0127647087592312[/C][/ROW]
[ROW][C]Number of all Pairs of Observations[/C][C]2016[/C][/ROW]
[ROW][C]Squared Differences between all Pairs of Observations[/C][C]4.2003484126984[/C][/ROW]
[ROW][C]Mean Absolute Differences between all Pairs of Observations[/C][C]1.66420634920635[/C][/ROW]
[ROW][C]Gini Mean Difference[/C][C]1.66420634920635[/C][/ROW]
[ROW][C]Leik Measure of Dispersion[/C][C]0.508172730571586[/C][/ROW]
[ROW][C]Index of Diversity[/C][C]0.984371908573981[/C][/ROW]
[ROW][C]Index of Qualitative Variation[/C][C]0.999996859503727[/C][/ROW]
[ROW][C]Coefficient of Dispersion[/C][C]0.0128098780727148[/C][/ROW]
[ROW][C]Observations[/C][C]64[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=147902&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=147902&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 range4.48
Relative range (unbiased)3.09136548577584
Relative range (biased)3.11580353789382
Variance (unbiased)2.10017420634921
Variance (biased)2.067358984375
Standard Deviation (unbiased)1.44919778027335
Standard Deviation (biased)1.43783134768129
Coefficient of Variation (unbiased)0.0141771563250895
Coefficient of Variation (biased)0.0140659612253524
Mean Squared Error (MSE versus 0)10451.123534375
Mean Squared Error (MSE versus Mean)2.067358984375
Mean Absolute Deviation from Mean (MAD Mean)1.305390625
Mean Absolute Deviation from Median (MAD Median)1.284375
Median Absolute Deviation from Mean1.270625
Median Absolute Deviation from Median1.34
Mean Squared Deviation from Mean2.067358984375
Mean Squared Deviation from Median2.166978125
Interquartile Difference (Weighted Average at Xnp)2.50999999999999
Interquartile Difference (Weighted Average at X(n+1)p)2.575
Interquartile Difference (Empirical Distribution Function)2.50999999999999
Interquartile Difference (Empirical Distribution Function - Averaging)2.54000000000001
Interquartile Difference (Empirical Distribution Function - Interpolation)2.505
Interquartile Difference (Closest Observation)2.50999999999999
Interquartile Difference (True Basic - Statistics Graphics Toolkit)2.50500000000001
Interquartile Difference (MS Excel (old versions))2.61
Semi Interquartile Difference (Weighted Average at Xnp)1.255
Semi Interquartile Difference (Weighted Average at X(n+1)p)1.2875
Semi Interquartile Difference (Empirical Distribution Function)1.255
Semi Interquartile Difference (Empirical Distribution Function - Averaging)1.27
Semi Interquartile Difference (Empirical Distribution Function - Interpolation)1.2525
Semi Interquartile Difference (Closest Observation)1.255
Semi Interquartile Difference (True Basic - Statistics Graphics Toolkit)1.2525
Semi Interquartile Difference (MS Excel (old versions))1.305
Coefficient of Quartile Variation (Weighted Average at Xnp)0.0122816460341537
Coefficient of Quartile Variation (Weighted Average at X(n+1)p)0.0125944584382872
Coefficient of Quartile Variation (Empirical Distribution Function)0.0122816460341537
Coefficient of Quartile Variation (Empirical Distribution Function - Averaging)0.012424183134416
Coefficient of Quartile Variation (Empirical Distribution Function - Interpolation)0.0122538828421181
Coefficient of Quartile Variation (Closest Observation)0.0122816460341537
Coefficient of Quartile Variation (True Basic - Statistics Graphics Toolkit)0.0122538828421182
Coefficient of Quartile Variation (MS Excel (old versions))0.0127647087592312
Number of all Pairs of Observations2016
Squared Differences between all Pairs of Observations4.2003484126984
Mean Absolute Differences between all Pairs of Observations1.66420634920635
Gini Mean Difference1.66420634920635
Leik Measure of Dispersion0.508172730571586
Index of Diversity0.984371908573981
Index of Qualitative Variation0.999996859503727
Coefficient of Dispersion0.0128098780727148
Observations64



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')