Free Statistics

of Irreproducible Research!

Author's title

Author*Unverified author*
R Software Modulerwasp_variability.wasp
Title produced by softwareVariability
Date of computationWed, 04 Dec 2013 06:26:08 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2013/Dec/04/t1386156384iuwcdhd44lrck2i.htm/, Retrieved Thu, 28 Mar 2024 09:46:22 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=230517, Retrieved Thu, 28 Mar 2024 09:46:22 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact77
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Variability] [] [2013-12-04 11:26:08] [548ba37af61861f215c3470847960b18] [Current]
Feedback Forum

Post a new message
Dataseries X:
462,23
464,79
465,22
468,52
469,02
469,15
469,15
469,15
469,15
469,41
469,45
469,45
469,93
477,19
478,97
480,44
480,56
481,8
483,24
483,45
483,53
483,59
483,59
483,59
492,36
495,71
499,29
499,78
500
500
500,29
500,42
500,61
498,9
499,06
496,61
498,41
501,26
505,4
506,07
506,2
507,14
507,14
507,28
507,34
507,48
506,97
506,97
510,1
515,84
519
520,1
521,26
521,04
521,12
521,12
521,1
521,16
521,14
521,13
522,17
531,39
532,12
533,34
535,72
536,25
536,25
536,68
536,76
536,79
536,99
536,99
542,38
544,1
546,96
547,04
550,27
550,32
551,17
552,83
552,35
552,44
552,47
548,78




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 2 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=230517&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]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=230517&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=230517&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 time2 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net







Variability - Ungrouped Data
Absolute range90.6
Relative range (unbiased)3.35663820002027
Relative range (biased)3.37679837047184
Variance (unbiased)728.52981495984
Variance (biased)719.856840972222
Standard Deviation (unbiased)26.9912914652085
Standard Deviation (biased)26.8301479864018
Coefficient of Variation (unbiased)0.053132550673886
Coefficient of Variation (biased)0.0528153385810708
Mean Squared Error (MSE versus 0)258783.010175
Mean Squared Error (MSE versus Mean)719.856840972222
Mean Absolute Deviation from Mean (MAD Mean)22.5880952380952
Mean Absolute Deviation from Median (MAD Median)22.4775
Median Absolute Deviation from Mean24.4391666666667
Median Absolute Deviation from Median23.625
Mean Squared Deviation from Mean719.856840972222
Mean Squared Deviation from Median720.916025
Interquartile Difference (Weighted Average at Xnp)48.59
Interquartile Difference (Weighted Average at X(n+1)p)49.49
Interquartile Difference (Empirical Distribution Function)48.59
Interquartile Difference (Empirical Distribution Function - Averaging)49.1700000000001
Interquartile Difference (Empirical Distribution Function - Interpolation)48.85
Interquartile Difference (Closest Observation)48.59
Interquartile Difference (True Basic - Statistics Graphics Toolkit)48.8500000000001
Interquartile Difference (MS Excel (old versions))49.8100000000001
Semi Interquartile Difference (Weighted Average at Xnp)24.295
Semi Interquartile Difference (Weighted Average at X(n+1)p)24.745
Semi Interquartile Difference (Empirical Distribution Function)24.295
Semi Interquartile Difference (Empirical Distribution Function - Averaging)24.585
Semi Interquartile Difference (Empirical Distribution Function - Interpolation)24.425
Semi Interquartile Difference (Closest Observation)24.295
Semi Interquartile Difference (True Basic - Statistics Graphics Toolkit)24.425
Semi Interquartile Difference (MS Excel (old versions))24.905
Coefficient of Quartile Variation (Weighted Average at Xnp)0.0478412839068577
Coefficient of Quartile Variation (Weighted Average at X(n+1)p)0.0486828385370556
Coefficient of Quartile Variation (Empirical Distribution Function)0.0478412839068577
Coefficient of Quartile Variation (Empirical Distribution Function - Averaging)0.0483818595086049
Coefficient of Quartile Variation (Empirical Distribution Function - Interpolation)0.0480807086614173
Coefficient of Quartile Variation (Closest Observation)0.0478412839068577
Coefficient of Quartile Variation (True Basic - Statistics Graphics Toolkit)0.0480807086614174
Coefficient of Quartile Variation (MS Excel (old versions))0.0489836458937721
Number of all Pairs of Observations3486
Squared Differences between all Pairs of Observations1457.05962991968
Mean Absolute Differences between all Pairs of Observations31.1623321858864
Gini Mean Difference31.1623321858865
Leik Measure of Dispersion0.50528897810843
Index of Diversity0.988062030238221
Index of Qualitative Variation0.99996639204832
Coefficient of Dispersion0.0445550924869228
Observations84

\begin{tabular}{lllllllll}
\hline
Variability - Ungrouped Data \tabularnewline
Absolute range & 90.6 \tabularnewline
Relative range (unbiased) & 3.35663820002027 \tabularnewline
Relative range (biased) & 3.37679837047184 \tabularnewline
Variance (unbiased) & 728.52981495984 \tabularnewline
Variance (biased) & 719.856840972222 \tabularnewline
Standard Deviation (unbiased) & 26.9912914652085 \tabularnewline
Standard Deviation (biased) & 26.8301479864018 \tabularnewline
Coefficient of Variation (unbiased) & 0.053132550673886 \tabularnewline
Coefficient of Variation (biased) & 0.0528153385810708 \tabularnewline
Mean Squared Error (MSE versus 0) & 258783.010175 \tabularnewline
Mean Squared Error (MSE versus Mean) & 719.856840972222 \tabularnewline
Mean Absolute Deviation from Mean (MAD Mean) & 22.5880952380952 \tabularnewline
Mean Absolute Deviation from Median (MAD Median) & 22.4775 \tabularnewline
Median Absolute Deviation from Mean & 24.4391666666667 \tabularnewline
Median Absolute Deviation from Median & 23.625 \tabularnewline
Mean Squared Deviation from Mean & 719.856840972222 \tabularnewline
Mean Squared Deviation from Median & 720.916025 \tabularnewline
Interquartile Difference (Weighted Average at Xnp) & 48.59 \tabularnewline
Interquartile Difference (Weighted Average at X(n+1)p) & 49.49 \tabularnewline
Interquartile Difference (Empirical Distribution Function) & 48.59 \tabularnewline
Interquartile Difference (Empirical Distribution Function - Averaging) & 49.1700000000001 \tabularnewline
Interquartile Difference (Empirical Distribution Function - Interpolation) & 48.85 \tabularnewline
Interquartile Difference (Closest Observation) & 48.59 \tabularnewline
Interquartile Difference (True Basic - Statistics Graphics Toolkit) & 48.8500000000001 \tabularnewline
Interquartile Difference (MS Excel (old versions)) & 49.8100000000001 \tabularnewline
Semi Interquartile Difference (Weighted Average at Xnp) & 24.295 \tabularnewline
Semi Interquartile Difference (Weighted Average at X(n+1)p) & 24.745 \tabularnewline
Semi Interquartile Difference (Empirical Distribution Function) & 24.295 \tabularnewline
Semi Interquartile Difference (Empirical Distribution Function - Averaging) & 24.585 \tabularnewline
Semi Interquartile Difference (Empirical Distribution Function - Interpolation) & 24.425 \tabularnewline
Semi Interquartile Difference (Closest Observation) & 24.295 \tabularnewline
Semi Interquartile Difference (True Basic - Statistics Graphics Toolkit) & 24.425 \tabularnewline
Semi Interquartile Difference (MS Excel (old versions)) & 24.905 \tabularnewline
Coefficient of Quartile Variation (Weighted Average at Xnp) & 0.0478412839068577 \tabularnewline
Coefficient of Quartile Variation (Weighted Average at X(n+1)p) & 0.0486828385370556 \tabularnewline
Coefficient of Quartile Variation (Empirical Distribution Function) & 0.0478412839068577 \tabularnewline
Coefficient of Quartile Variation (Empirical Distribution Function - Averaging) & 0.0483818595086049 \tabularnewline
Coefficient of Quartile Variation (Empirical Distribution Function - Interpolation) & 0.0480807086614173 \tabularnewline
Coefficient of Quartile Variation (Closest Observation) & 0.0478412839068577 \tabularnewline
Coefficient of Quartile Variation (True Basic - Statistics Graphics Toolkit) & 0.0480807086614174 \tabularnewline
Coefficient of Quartile Variation (MS Excel (old versions)) & 0.0489836458937721 \tabularnewline
Number of all Pairs of Observations & 3486 \tabularnewline
Squared Differences between all Pairs of Observations & 1457.05962991968 \tabularnewline
Mean Absolute Differences between all Pairs of Observations & 31.1623321858864 \tabularnewline
Gini Mean Difference & 31.1623321858865 \tabularnewline
Leik Measure of Dispersion & 0.50528897810843 \tabularnewline
Index of Diversity & 0.988062030238221 \tabularnewline
Index of Qualitative Variation & 0.99996639204832 \tabularnewline
Coefficient of Dispersion & 0.0445550924869228 \tabularnewline
Observations & 84 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=230517&T=1

[TABLE]
[ROW][C]Variability - Ungrouped Data[/C][/ROW]
[ROW][C]Absolute range[/C][C]90.6[/C][/ROW]
[ROW][C]Relative range (unbiased)[/C][C]3.35663820002027[/C][/ROW]
[ROW][C]Relative range (biased)[/C][C]3.37679837047184[/C][/ROW]
[ROW][C]Variance (unbiased)[/C][C]728.52981495984[/C][/ROW]
[ROW][C]Variance (biased)[/C][C]719.856840972222[/C][/ROW]
[ROW][C]Standard Deviation (unbiased)[/C][C]26.9912914652085[/C][/ROW]
[ROW][C]Standard Deviation (biased)[/C][C]26.8301479864018[/C][/ROW]
[ROW][C]Coefficient of Variation (unbiased)[/C][C]0.053132550673886[/C][/ROW]
[ROW][C]Coefficient of Variation (biased)[/C][C]0.0528153385810708[/C][/ROW]
[ROW][C]Mean Squared Error (MSE versus 0)[/C][C]258783.010175[/C][/ROW]
[ROW][C]Mean Squared Error (MSE versus Mean)[/C][C]719.856840972222[/C][/ROW]
[ROW][C]Mean Absolute Deviation from Mean (MAD Mean)[/C][C]22.5880952380952[/C][/ROW]
[ROW][C]Mean Absolute Deviation from Median (MAD Median)[/C][C]22.4775[/C][/ROW]
[ROW][C]Median Absolute Deviation from Mean[/C][C]24.4391666666667[/C][/ROW]
[ROW][C]Median Absolute Deviation from Median[/C][C]23.625[/C][/ROW]
[ROW][C]Mean Squared Deviation from Mean[/C][C]719.856840972222[/C][/ROW]
[ROW][C]Mean Squared Deviation from Median[/C][C]720.916025[/C][/ROW]
[ROW][C]Interquartile Difference (Weighted Average at Xnp)[/C][C]48.59[/C][/ROW]
[ROW][C]Interquartile Difference (Weighted Average at X(n+1)p)[/C][C]49.49[/C][/ROW]
[ROW][C]Interquartile Difference (Empirical Distribution Function)[/C][C]48.59[/C][/ROW]
[ROW][C]Interquartile Difference (Empirical Distribution Function - Averaging)[/C][C]49.1700000000001[/C][/ROW]
[ROW][C]Interquartile Difference (Empirical Distribution Function - Interpolation)[/C][C]48.85[/C][/ROW]
[ROW][C]Interquartile Difference (Closest Observation)[/C][C]48.59[/C][/ROW]
[ROW][C]Interquartile Difference (True Basic - Statistics Graphics Toolkit)[/C][C]48.8500000000001[/C][/ROW]
[ROW][C]Interquartile Difference (MS Excel (old versions))[/C][C]49.8100000000001[/C][/ROW]
[ROW][C]Semi Interquartile Difference (Weighted Average at Xnp)[/C][C]24.295[/C][/ROW]
[ROW][C]Semi Interquartile Difference (Weighted Average at X(n+1)p)[/C][C]24.745[/C][/ROW]
[ROW][C]Semi Interquartile Difference (Empirical Distribution Function)[/C][C]24.295[/C][/ROW]
[ROW][C]Semi Interquartile Difference (Empirical Distribution Function - Averaging)[/C][C]24.585[/C][/ROW]
[ROW][C]Semi Interquartile Difference (Empirical Distribution Function - Interpolation)[/C][C]24.425[/C][/ROW]
[ROW][C]Semi Interquartile Difference (Closest Observation)[/C][C]24.295[/C][/ROW]
[ROW][C]Semi Interquartile Difference (True Basic - Statistics Graphics Toolkit)[/C][C]24.425[/C][/ROW]
[ROW][C]Semi Interquartile Difference (MS Excel (old versions))[/C][C]24.905[/C][/ROW]
[ROW][C]Coefficient of Quartile Variation (Weighted Average at Xnp)[/C][C]0.0478412839068577[/C][/ROW]
[ROW][C]Coefficient of Quartile Variation (Weighted Average at X(n+1)p)[/C][C]0.0486828385370556[/C][/ROW]
[ROW][C]Coefficient of Quartile Variation (Empirical Distribution Function)[/C][C]0.0478412839068577[/C][/ROW]
[ROW][C]Coefficient of Quartile Variation (Empirical Distribution Function - Averaging)[/C][C]0.0483818595086049[/C][/ROW]
[ROW][C]Coefficient of Quartile Variation (Empirical Distribution Function - Interpolation)[/C][C]0.0480807086614173[/C][/ROW]
[ROW][C]Coefficient of Quartile Variation (Closest Observation)[/C][C]0.0478412839068577[/C][/ROW]
[ROW][C]Coefficient of Quartile Variation (True Basic - Statistics Graphics Toolkit)[/C][C]0.0480807086614174[/C][/ROW]
[ROW][C]Coefficient of Quartile Variation (MS Excel (old versions))[/C][C]0.0489836458937721[/C][/ROW]
[ROW][C]Number of all Pairs of Observations[/C][C]3486[/C][/ROW]
[ROW][C]Squared Differences between all Pairs of Observations[/C][C]1457.05962991968[/C][/ROW]
[ROW][C]Mean Absolute Differences between all Pairs of Observations[/C][C]31.1623321858864[/C][/ROW]
[ROW][C]Gini Mean Difference[/C][C]31.1623321858865[/C][/ROW]
[ROW][C]Leik Measure of Dispersion[/C][C]0.50528897810843[/C][/ROW]
[ROW][C]Index of Diversity[/C][C]0.988062030238221[/C][/ROW]
[ROW][C]Index of Qualitative Variation[/C][C]0.99996639204832[/C][/ROW]
[ROW][C]Coefficient of Dispersion[/C][C]0.0445550924869228[/C][/ROW]
[ROW][C]Observations[/C][C]84[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=230517&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=230517&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 range90.6
Relative range (unbiased)3.35663820002027
Relative range (biased)3.37679837047184
Variance (unbiased)728.52981495984
Variance (biased)719.856840972222
Standard Deviation (unbiased)26.9912914652085
Standard Deviation (biased)26.8301479864018
Coefficient of Variation (unbiased)0.053132550673886
Coefficient of Variation (biased)0.0528153385810708
Mean Squared Error (MSE versus 0)258783.010175
Mean Squared Error (MSE versus Mean)719.856840972222
Mean Absolute Deviation from Mean (MAD Mean)22.5880952380952
Mean Absolute Deviation from Median (MAD Median)22.4775
Median Absolute Deviation from Mean24.4391666666667
Median Absolute Deviation from Median23.625
Mean Squared Deviation from Mean719.856840972222
Mean Squared Deviation from Median720.916025
Interquartile Difference (Weighted Average at Xnp)48.59
Interquartile Difference (Weighted Average at X(n+1)p)49.49
Interquartile Difference (Empirical Distribution Function)48.59
Interquartile Difference (Empirical Distribution Function - Averaging)49.1700000000001
Interquartile Difference (Empirical Distribution Function - Interpolation)48.85
Interquartile Difference (Closest Observation)48.59
Interquartile Difference (True Basic - Statistics Graphics Toolkit)48.8500000000001
Interquartile Difference (MS Excel (old versions))49.8100000000001
Semi Interquartile Difference (Weighted Average at Xnp)24.295
Semi Interquartile Difference (Weighted Average at X(n+1)p)24.745
Semi Interquartile Difference (Empirical Distribution Function)24.295
Semi Interquartile Difference (Empirical Distribution Function - Averaging)24.585
Semi Interquartile Difference (Empirical Distribution Function - Interpolation)24.425
Semi Interquartile Difference (Closest Observation)24.295
Semi Interquartile Difference (True Basic - Statistics Graphics Toolkit)24.425
Semi Interquartile Difference (MS Excel (old versions))24.905
Coefficient of Quartile Variation (Weighted Average at Xnp)0.0478412839068577
Coefficient of Quartile Variation (Weighted Average at X(n+1)p)0.0486828385370556
Coefficient of Quartile Variation (Empirical Distribution Function)0.0478412839068577
Coefficient of Quartile Variation (Empirical Distribution Function - Averaging)0.0483818595086049
Coefficient of Quartile Variation (Empirical Distribution Function - Interpolation)0.0480807086614173
Coefficient of Quartile Variation (Closest Observation)0.0478412839068577
Coefficient of Quartile Variation (True Basic - Statistics Graphics Toolkit)0.0480807086614174
Coefficient of Quartile Variation (MS Excel (old versions))0.0489836458937721
Number of all Pairs of Observations3486
Squared Differences between all Pairs of Observations1457.05962991968
Mean Absolute Differences between all Pairs of Observations31.1623321858864
Gini Mean Difference31.1623321858865
Leik Measure of Dispersion0.50528897810843
Index of Diversity0.988062030238221
Index of Qualitative Variation0.99996639204832
Coefficient of Dispersion0.0445550924869228
Observations84



Parameters (Session):
Parameters (R input):
R code (references can be found in the software module):
num <- 50
res <- array(NA,dim=c(num,3))
q1 <- function(data,n,p,i,f) {
np <- n*p;
i <<- floor(np)
f <<- np - i
qvalue <- (1-f)*data[i] + f*data[i+1]
}
q2 <- function(data,n,p,i,f) {
np <- (n+1)*p
i <<- floor(np)
f <<- np - i
qvalue <- (1-f)*data[i] + f*data[i+1]
}
q3 <- function(data,n,p,i,f) {
np <- n*p
i <<- floor(np)
f <<- np - i
if (f==0) {
qvalue <- data[i]
} else {
qvalue <- data[i+1]
}
}
q4 <- function(data,n,p,i,f) {
np <- n*p
i <<- floor(np)
f <<- np - i
if (f==0) {
qvalue <- (data[i]+data[i+1])/2
} else {
qvalue <- data[i+1]
}
}
q5 <- function(data,n,p,i,f) {
np <- (n-1)*p
i <<- floor(np)
f <<- np - i
if (f==0) {
qvalue <- data[i+1]
} else {
qvalue <- data[i+1] + f*(data[i+2]-data[i+1])
}
}
q6 <- function(data,n,p,i,f) {
np <- n*p+0.5
i <<- floor(np)
f <<- np - i
qvalue <- data[i]
}
q7 <- function(data,n,p,i,f) {
np <- (n+1)*p
i <<- floor(np)
f <<- np - i
if (f==0) {
qvalue <- data[i]
} else {
qvalue <- f*data[i] + (1-f)*data[i+1]
}
}
q8 <- function(data,n,p,i,f) {
np <- (n+1)*p
i <<- floor(np)
f <<- np - i
if (f==0) {
qvalue <- data[i]
} else {
if (f == 0.5) {
qvalue <- (data[i]+data[i+1])/2
} else {
if (f < 0.5) {
qvalue <- data[i]
} else {
qvalue <- data[i+1]
}
}
}
}
iqd <- function(x,def) {
x <-sort(x[!is.na(x)])
n<-length(x)
if (def==1) {
qvalue1 <- q1(x,n,0.25,i,f)
qvalue3 <- q1(x,n,0.75,i,f)
}
if (def==2) {
qvalue1 <- q2(x,n,0.25,i,f)
qvalue3 <- q2(x,n,0.75,i,f)
}
if (def==3) {
qvalue1 <- q3(x,n,0.25,i,f)
qvalue3 <- q3(x,n,0.75,i,f)
}
if (def==4) {
qvalue1 <- q4(x,n,0.25,i,f)
qvalue3 <- q4(x,n,0.75,i,f)
}
if (def==5) {
qvalue1 <- q5(x,n,0.25,i,f)
qvalue3 <- q5(x,n,0.75,i,f)
}
if (def==6) {
qvalue1 <- q6(x,n,0.25,i,f)
qvalue3 <- q6(x,n,0.75,i,f)
}
if (def==7) {
qvalue1 <- q7(x,n,0.25,i,f)
qvalue3 <- q7(x,n,0.75,i,f)
}
if (def==8) {
qvalue1 <- q8(x,n,0.25,i,f)
qvalue3 <- q8(x,n,0.75,i,f)
}
iqdiff <- qvalue3 - qvalue1
return(c(iqdiff,iqdiff/2,iqdiff/(qvalue3 + qvalue1)))
}
range <- max(x) - min(x)
lx <- length(x)
biasf <- (lx-1)/lx
varx <- var(x)
bvarx <- varx*biasf
sdx <- sqrt(varx)
mx <- mean(x)
bsdx <- sqrt(bvarx)
x2 <- x*x
mse0 <- sum(x2)/lx
xmm <- x-mx
xmm2 <- xmm*xmm
msem <- sum(xmm2)/lx
axmm <- abs(x - mx)
medx <- median(x)
axmmed <- abs(x - medx)
xmmed <- x - medx
xmmed2 <- xmmed*xmmed
msemed <- sum(xmmed2)/lx
qarr <- array(NA,dim=c(8,3))
for (j in 1:8) {
qarr[j,] <- iqd(x,j)
}
sdpo <- 0
adpo <- 0
for (i in 1:(lx-1)) {
for (j in (i+1):lx) {
ldi <- x[i]-x[j]
aldi <- abs(ldi)
sdpo = sdpo + ldi * ldi
adpo = adpo + aldi
}
}
denom <- (lx*(lx-1)/2)
sdpo = sdpo / denom
adpo = adpo / denom
gmd <- 0
for (i in 1:lx) {
for (j in 1:lx) {
ldi <- abs(x[i]-x[j])
gmd = gmd + ldi
}
}
gmd <- gmd / (lx*(lx-1))
sumx <- sum(x)
pk <- x / sumx
ck <- cumsum(pk)
dk <- array(NA,dim=lx)
for (i in 1:lx) {
if (ck[i] <= 0.5) dk[i] <- ck[i] else dk[i] <- 1 - ck[i]
}
bigd <- sum(dk) * 2 / (lx-1)
iod <- 1 - sum(pk*pk)
res[1,] <- c('Absolute range','absolute.htm', range)
res[2,] <- c('Relative range (unbiased)','relative.htm', range/sd(x))
res[3,] <- c('Relative range (biased)','relative.htm', range/sqrt(varx*biasf))
res[4,] <- c('Variance (unbiased)','unbiased.htm', varx)
res[5,] <- c('Variance (biased)','biased.htm', bvarx)
res[6,] <- c('Standard Deviation (unbiased)','unbiased1.htm', sdx)
res[7,] <- c('Standard Deviation (biased)','biased1.htm', bsdx)
res[8,] <- c('Coefficient of Variation (unbiased)','variation.htm', sdx/mx)
res[9,] <- c('Coefficient of Variation (biased)','variation.htm', bsdx/mx)
res[10,] <- c('Mean Squared Error (MSE versus 0)','mse.htm', mse0)
res[11,] <- c('Mean Squared Error (MSE versus Mean)','mse.htm', msem)
res[12,] <- c('Mean Absolute Deviation from Mean (MAD Mean)', 'mean2.htm', sum(axmm)/lx)
res[13,] <- c('Mean Absolute Deviation from Median (MAD Median)', 'median1.htm', sum(axmmed)/lx)
res[14,] <- c('Median Absolute Deviation from Mean', 'mean3.htm', median(axmm))
res[15,] <- c('Median Absolute Deviation from Median', 'median2.htm', median(axmmed))
res[16,] <- c('Mean Squared Deviation from Mean', 'mean1.htm', msem)
res[17,] <- c('Mean Squared Deviation from Median', 'median.htm', msemed)
load(file='createtable')
mylink1 <- hyperlink('difference.htm','Interquartile Difference','')
mylink2 <- paste(mylink1,hyperlink('method_1.htm','(Weighted Average at Xnp)',''),sep=' ')
res[18,] <- c('', mylink2, qarr[1,1])
mylink2 <- paste(mylink1,hyperlink('method_2.htm','(Weighted Average at X(n+1)p)',''),sep=' ')
res[19,] <- c('', mylink2, qarr[2,1])
mylink2 <- paste(mylink1,hyperlink('method_3.htm','(Empirical Distribution Function)',''),sep=' ')
res[20,] <- c('', mylink2, qarr[3,1])
mylink2 <- paste(mylink1,hyperlink('method_4.htm','(Empirical Distribution Function - Averaging)',''),sep=' ')
res[21,] <- c('', mylink2, qarr[4,1])
mylink2 <- paste(mylink1,hyperlink('method_5.htm','(Empirical Distribution Function - Interpolation)',''),sep=' ')
res[22,] <- c('', mylink2, qarr[5,1])
mylink2 <- paste(mylink1,hyperlink('method_6.htm','(Closest Observation)',''),sep=' ')
res[23,] <- c('', mylink2, qarr[6,1])
mylink2 <- paste(mylink1,hyperlink('method_7.htm','(True Basic - Statistics Graphics Toolkit)',''),sep=' ')
res[24,] <- c('', mylink2, qarr[7,1])
mylink2 <- paste(mylink1,hyperlink('method_8.htm','(MS Excel (old versions))',''),sep=' ')
res[25,] <- c('', mylink2, qarr[8,1])
mylink1 <- hyperlink('deviation.htm','Semi Interquartile Difference','')
mylink2 <- paste(mylink1,hyperlink('method_1.htm','(Weighted Average at Xnp)',''),sep=' ')
res[26,] <- c('', mylink2, qarr[1,2])
mylink2 <- paste(mylink1,hyperlink('method_2.htm','(Weighted Average at X(n+1)p)',''),sep=' ')
res[27,] <- c('', mylink2, qarr[2,2])
mylink2 <- paste(mylink1,hyperlink('method_3.htm','(Empirical Distribution Function)',''),sep=' ')
res[28,] <- c('', mylink2, qarr[3,2])
mylink2 <- paste(mylink1,hyperlink('method_4.htm','(Empirical Distribution Function - Averaging)',''),sep=' ')
res[29,] <- c('', mylink2, qarr[4,2])
mylink2 <- paste(mylink1,hyperlink('method_5.htm','(Empirical Distribution Function - Interpolation)',''),sep=' ')
res[30,] <- c('', mylink2, qarr[5,2])
mylink2 <- paste(mylink1,hyperlink('method_6.htm','(Closest Observation)',''),sep=' ')
res[31,] <- c('', mylink2, qarr[6,2])
mylink2 <- paste(mylink1,hyperlink('method_7.htm','(True Basic - Statistics Graphics Toolkit)',''),sep=' ')
res[32,] <- c('', mylink2, qarr[7,2])
mylink2 <- paste(mylink1,hyperlink('method_8.htm','(MS Excel (old versions))',''),sep=' ')
res[33,] <- c('', mylink2, qarr[8,2])
mylink1 <- hyperlink('variation1.htm','Coefficient of Quartile Variation','')
mylink2 <- paste(mylink1,hyperlink('method_1.htm','(Weighted Average at Xnp)',''),sep=' ')
res[34,] <- c('', mylink2, qarr[1,3])
mylink2 <- paste(mylink1,hyperlink('method_2.htm','(Weighted Average at X(n+1)p)',''),sep=' ')
res[35,] <- c('', mylink2, qarr[2,3])
mylink2 <- paste(mylink1,hyperlink('method_3.htm','(Empirical Distribution Function)',''),sep=' ')
res[36,] <- c('', mylink2, qarr[3,3])
mylink2 <- paste(mylink1,hyperlink('method_4.htm','(Empirical Distribution Function - Averaging)',''),sep=' ')
res[37,] <- c('', mylink2, qarr[4,3])
mylink2 <- paste(mylink1,hyperlink('method_5.htm','(Empirical Distribution Function - Interpolation)',''),sep=' ')
res[38,] <- c('', mylink2, qarr[5,3])
mylink2 <- paste(mylink1,hyperlink('method_6.htm','(Closest Observation)',''),sep=' ')
res[39,] <- c('', mylink2, qarr[6,3])
mylink2 <- paste(mylink1,hyperlink('method_7.htm','(True Basic - Statistics Graphics Toolkit)',''),sep=' ')
res[40,] <- c('', mylink2, qarr[7,3])
mylink2 <- paste(mylink1,hyperlink('method_8.htm','(MS Excel (old versions))',''),sep=' ')
res[41,] <- c('', mylink2, qarr[8,3])
res[42,] <- c('Number of all Pairs of Observations', 'pair_numbers.htm', lx*(lx-1)/2)
res[43,] <- c('Squared Differences between all Pairs of Observations', 'squared_differences.htm', sdpo)
res[44,] <- c('Mean Absolute Differences between all Pairs of Observations', 'mean_abs_differences.htm', adpo)
res[45,] <- c('Gini Mean Difference', 'gini_mean_difference.htm', gmd)
res[46,] <- c('Leik Measure of Dispersion', 'leiks_d.htm', bigd)
res[47,] <- c('Index of Diversity', 'diversity.htm', iod)
res[48,] <- c('Index of Qualitative Variation', 'qualitative_variation.htm', iod*lx/(lx-1))
res[49,] <- c('Coefficient of Dispersion', 'dispersion.htm', sum(axmm)/lx/medx)
res[50,] <- c('Observations', '', lx)
res
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Variability - Ungrouped Data',2,TRUE)
a<-table.row.end(a)
for (i in 1:num) {
a<-table.row.start(a)
if (res[i,1] != '') {
a<-table.element(a,hyperlink(res[i,2],res[i,1],''),header=TRUE)
} else {
a<-table.element(a,res[i,2],header=TRUE)
}
a<-table.element(a,res[i,3])
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable.tab')