Free Statistics

of Irreproducible Research!

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_variability.wasp
Title produced by softwareVariability
Date of computationTue, 04 Dec 2012 12:58:55 -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/2012/Dec/04/t1354643963mffuse8gcrtzyg0.htm/, Retrieved Thu, 28 Mar 2024 12:05:21 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=196439, Retrieved Thu, 28 Mar 2024 12:05:21 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact67
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Variability] [voorbereiding var...] [2012-12-04 17:58:55] [e9a6d890a409316933ed6704aac2b42b] [Current]
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Dataseries X:


19


25



17
22



21

26
20

14


23




20

22


15
20
22

20
28




25
26

17
23

13




24



14
22



23

22
24
21



23
22




21
26
15
25



17
25





27




25

19
26

20


20

18








18


19






23


17
23

23
11
18
24


16
24




24


21
25
22
21



24
24
21




18




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net
R Framework error message
Warning: there are blank lines in the 'Data' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.

\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' @ jenkins.wessa.net \tabularnewline
R Framework error message & 
Warning: there are blank lines in the 'Data' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.
\tabularnewline \hline \end{tabular} %Source: https://freestatistics.org/blog/index.php?pk=196439&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' @ jenkins.wessa.net[/C][/ROW]
[ROW][C]R Framework error message[/C][C]
Warning: there are blank lines in the 'Data' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.
[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=196439&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=196439&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' @ jenkins.wessa.net
R Framework error message
Warning: there are blank lines in the 'Data' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.







Variability - Ungrouped Data
Absolute range17
Relative range (unbiased)4.57942466547662
Relative range (biased)4.61620778381309
Variance (unbiased)13.7808499743984
Variance (biased)13.5621063240111
Standard Deviation (unbiased)3.71225672258781
Standard Deviation (biased)3.68267651634122
Coefficient of Variation (unbiased)0.175447992140309
Coefficient of Variation (biased)0.174049977891595
Mean Squared Error (MSE versus 0)461.253968253968
Mean Squared Error (MSE versus Mean)13.5621063240111
Mean Absolute Deviation from Mean (MAD Mean)2.97656840513983
Mean Absolute Deviation from Median (MAD Median)2.93650793650794
Median Absolute Deviation from Mean2.84126984126984
Median Absolute Deviation from Median2
Mean Squared Deviation from Mean13.5621063240111
Mean Squared Deviation from Median14.2698412698413
Interquartile Difference (Weighted Average at Xnp)5.25
Interquartile Difference (Weighted Average at X(n+1)p)5
Interquartile Difference (Empirical Distribution Function)5
Interquartile Difference (Empirical Distribution Function - Averaging)5
Interquartile Difference (Empirical Distribution Function - Interpolation)5
Interquartile Difference (Closest Observation)5
Interquartile Difference (True Basic - Statistics Graphics Toolkit)5
Interquartile Difference (MS Excel (old versions))5
Semi Interquartile Difference (Weighted Average at Xnp)2.625
Semi Interquartile Difference (Weighted Average at X(n+1)p)2.5
Semi Interquartile Difference (Empirical Distribution Function)2.5
Semi Interquartile Difference (Empirical Distribution Function - Averaging)2.5
Semi Interquartile Difference (Empirical Distribution Function - Interpolation)2.5
Semi Interquartile Difference (Closest Observation)2.5
Semi Interquartile Difference (True Basic - Statistics Graphics Toolkit)2.5
Semi Interquartile Difference (MS Excel (old versions))2.5
Coefficient of Quartile Variation (Weighted Average at Xnp)0.12280701754386
Coefficient of Quartile Variation (Weighted Average at X(n+1)p)0.116279069767442
Coefficient of Quartile Variation (Empirical Distribution Function)0.116279069767442
Coefficient of Quartile Variation (Empirical Distribution Function - Averaging)0.116279069767442
Coefficient of Quartile Variation (Empirical Distribution Function - Interpolation)0.116279069767442
Coefficient of Quartile Variation (Closest Observation)0.116279069767442
Coefficient of Quartile Variation (True Basic - Statistics Graphics Toolkit)0.116279069767442
Coefficient of Quartile Variation (MS Excel (old versions))0.116279069767442
Number of all Pairs of Observations1953
Squared Differences between all Pairs of Observations27.5616999487967
Mean Absolute Differences between all Pairs of Observations4.1884280593958
Gini Mean Difference4.1884280593958
Leik Measure of Dispersion0.504634223071897
Index of Diversity0.983646136590412
Index of Qualitative Variation0.999511396857999
Coefficient of Dispersion0.135298563869992
Observations63

\begin{tabular}{lllllllll}
\hline
Variability - Ungrouped Data \tabularnewline
Absolute range & 17 \tabularnewline
Relative range (unbiased) & 4.57942466547662 \tabularnewline
Relative range (biased) & 4.61620778381309 \tabularnewline
Variance (unbiased) & 13.7808499743984 \tabularnewline
Variance (biased) & 13.5621063240111 \tabularnewline
Standard Deviation (unbiased) & 3.71225672258781 \tabularnewline
Standard Deviation (biased) & 3.68267651634122 \tabularnewline
Coefficient of Variation (unbiased) & 0.175447992140309 \tabularnewline
Coefficient of Variation (biased) & 0.174049977891595 \tabularnewline
Mean Squared Error (MSE versus 0) & 461.253968253968 \tabularnewline
Mean Squared Error (MSE versus Mean) & 13.5621063240111 \tabularnewline
Mean Absolute Deviation from Mean (MAD Mean) & 2.97656840513983 \tabularnewline
Mean Absolute Deviation from Median (MAD Median) & 2.93650793650794 \tabularnewline
Median Absolute Deviation from Mean & 2.84126984126984 \tabularnewline
Median Absolute Deviation from Median & 2 \tabularnewline
Mean Squared Deviation from Mean & 13.5621063240111 \tabularnewline
Mean Squared Deviation from Median & 14.2698412698413 \tabularnewline
Interquartile Difference (Weighted Average at Xnp) & 5.25 \tabularnewline
Interquartile Difference (Weighted Average at X(n+1)p) & 5 \tabularnewline
Interquartile Difference (Empirical Distribution Function) & 5 \tabularnewline
Interquartile Difference (Empirical Distribution Function - Averaging) & 5 \tabularnewline
Interquartile Difference (Empirical Distribution Function - Interpolation) & 5 \tabularnewline
Interquartile Difference (Closest Observation) & 5 \tabularnewline
Interquartile Difference (True Basic - Statistics Graphics Toolkit) & 5 \tabularnewline
Interquartile Difference (MS Excel (old versions)) & 5 \tabularnewline
Semi Interquartile Difference (Weighted Average at Xnp) & 2.625 \tabularnewline
Semi Interquartile Difference (Weighted Average at X(n+1)p) & 2.5 \tabularnewline
Semi Interquartile Difference (Empirical Distribution Function) & 2.5 \tabularnewline
Semi Interquartile Difference (Empirical Distribution Function - Averaging) & 2.5 \tabularnewline
Semi Interquartile Difference (Empirical Distribution Function - Interpolation) & 2.5 \tabularnewline
Semi Interquartile Difference (Closest Observation) & 2.5 \tabularnewline
Semi Interquartile Difference (True Basic - Statistics Graphics Toolkit) & 2.5 \tabularnewline
Semi Interquartile Difference (MS Excel (old versions)) & 2.5 \tabularnewline
Coefficient of Quartile Variation (Weighted Average at Xnp) & 0.12280701754386 \tabularnewline
Coefficient of Quartile Variation (Weighted Average at X(n+1)p) & 0.116279069767442 \tabularnewline
Coefficient of Quartile Variation (Empirical Distribution Function) & 0.116279069767442 \tabularnewline
Coefficient of Quartile Variation (Empirical Distribution Function - Averaging) & 0.116279069767442 \tabularnewline
Coefficient of Quartile Variation (Empirical Distribution Function - Interpolation) & 0.116279069767442 \tabularnewline
Coefficient of Quartile Variation (Closest Observation) & 0.116279069767442 \tabularnewline
Coefficient of Quartile Variation (True Basic - Statistics Graphics Toolkit) & 0.116279069767442 \tabularnewline
Coefficient of Quartile Variation (MS Excel (old versions)) & 0.116279069767442 \tabularnewline
Number of all Pairs of Observations & 1953 \tabularnewline
Squared Differences between all Pairs of Observations & 27.5616999487967 \tabularnewline
Mean Absolute Differences between all Pairs of Observations & 4.1884280593958 \tabularnewline
Gini Mean Difference & 4.1884280593958 \tabularnewline
Leik Measure of Dispersion & 0.504634223071897 \tabularnewline
Index of Diversity & 0.983646136590412 \tabularnewline
Index of Qualitative Variation & 0.999511396857999 \tabularnewline
Coefficient of Dispersion & 0.135298563869992 \tabularnewline
Observations & 63 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=196439&T=1

[TABLE]
[ROW][C]Variability - Ungrouped Data[/C][/ROW]
[ROW][C]Absolute range[/C][C]17[/C][/ROW]
[ROW][C]Relative range (unbiased)[/C][C]4.57942466547662[/C][/ROW]
[ROW][C]Relative range (biased)[/C][C]4.61620778381309[/C][/ROW]
[ROW][C]Variance (unbiased)[/C][C]13.7808499743984[/C][/ROW]
[ROW][C]Variance (biased)[/C][C]13.5621063240111[/C][/ROW]
[ROW][C]Standard Deviation (unbiased)[/C][C]3.71225672258781[/C][/ROW]
[ROW][C]Standard Deviation (biased)[/C][C]3.68267651634122[/C][/ROW]
[ROW][C]Coefficient of Variation (unbiased)[/C][C]0.175447992140309[/C][/ROW]
[ROW][C]Coefficient of Variation (biased)[/C][C]0.174049977891595[/C][/ROW]
[ROW][C]Mean Squared Error (MSE versus 0)[/C][C]461.253968253968[/C][/ROW]
[ROW][C]Mean Squared Error (MSE versus Mean)[/C][C]13.5621063240111[/C][/ROW]
[ROW][C]Mean Absolute Deviation from Mean (MAD Mean)[/C][C]2.97656840513983[/C][/ROW]
[ROW][C]Mean Absolute Deviation from Median (MAD Median)[/C][C]2.93650793650794[/C][/ROW]
[ROW][C]Median Absolute Deviation from Mean[/C][C]2.84126984126984[/C][/ROW]
[ROW][C]Median Absolute Deviation from Median[/C][C]2[/C][/ROW]
[ROW][C]Mean Squared Deviation from Mean[/C][C]13.5621063240111[/C][/ROW]
[ROW][C]Mean Squared Deviation from Median[/C][C]14.2698412698413[/C][/ROW]
[ROW][C]Interquartile Difference (Weighted Average at Xnp)[/C][C]5.25[/C][/ROW]
[ROW][C]Interquartile Difference (Weighted Average at X(n+1)p)[/C][C]5[/C][/ROW]
[ROW][C]Interquartile Difference (Empirical Distribution Function)[/C][C]5[/C][/ROW]
[ROW][C]Interquartile Difference (Empirical Distribution Function - Averaging)[/C][C]5[/C][/ROW]
[ROW][C]Interquartile Difference (Empirical Distribution Function - Interpolation)[/C][C]5[/C][/ROW]
[ROW][C]Interquartile Difference (Closest Observation)[/C][C]5[/C][/ROW]
[ROW][C]Interquartile Difference (True Basic - Statistics Graphics Toolkit)[/C][C]5[/C][/ROW]
[ROW][C]Interquartile Difference (MS Excel (old versions))[/C][C]5[/C][/ROW]
[ROW][C]Semi Interquartile Difference (Weighted Average at Xnp)[/C][C]2.625[/C][/ROW]
[ROW][C]Semi Interquartile Difference (Weighted Average at X(n+1)p)[/C][C]2.5[/C][/ROW]
[ROW][C]Semi Interquartile Difference (Empirical Distribution Function)[/C][C]2.5[/C][/ROW]
[ROW][C]Semi Interquartile Difference (Empirical Distribution Function - Averaging)[/C][C]2.5[/C][/ROW]
[ROW][C]Semi Interquartile Difference (Empirical Distribution Function - Interpolation)[/C][C]2.5[/C][/ROW]
[ROW][C]Semi Interquartile Difference (Closest Observation)[/C][C]2.5[/C][/ROW]
[ROW][C]Semi Interquartile Difference (True Basic - Statistics Graphics Toolkit)[/C][C]2.5[/C][/ROW]
[ROW][C]Semi Interquartile Difference (MS Excel (old versions))[/C][C]2.5[/C][/ROW]
[ROW][C]Coefficient of Quartile Variation (Weighted Average at Xnp)[/C][C]0.12280701754386[/C][/ROW]
[ROW][C]Coefficient of Quartile Variation (Weighted Average at X(n+1)p)[/C][C]0.116279069767442[/C][/ROW]
[ROW][C]Coefficient of Quartile Variation (Empirical Distribution Function)[/C][C]0.116279069767442[/C][/ROW]
[ROW][C]Coefficient of Quartile Variation (Empirical Distribution Function - Averaging)[/C][C]0.116279069767442[/C][/ROW]
[ROW][C]Coefficient of Quartile Variation (Empirical Distribution Function - Interpolation)[/C][C]0.116279069767442[/C][/ROW]
[ROW][C]Coefficient of Quartile Variation (Closest Observation)[/C][C]0.116279069767442[/C][/ROW]
[ROW][C]Coefficient of Quartile Variation (True Basic - Statistics Graphics Toolkit)[/C][C]0.116279069767442[/C][/ROW]
[ROW][C]Coefficient of Quartile Variation (MS Excel (old versions))[/C][C]0.116279069767442[/C][/ROW]
[ROW][C]Number of all Pairs of Observations[/C][C]1953[/C][/ROW]
[ROW][C]Squared Differences between all Pairs of Observations[/C][C]27.5616999487967[/C][/ROW]
[ROW][C]Mean Absolute Differences between all Pairs of Observations[/C][C]4.1884280593958[/C][/ROW]
[ROW][C]Gini Mean Difference[/C][C]4.1884280593958[/C][/ROW]
[ROW][C]Leik Measure of Dispersion[/C][C]0.504634223071897[/C][/ROW]
[ROW][C]Index of Diversity[/C][C]0.983646136590412[/C][/ROW]
[ROW][C]Index of Qualitative Variation[/C][C]0.999511396857999[/C][/ROW]
[ROW][C]Coefficient of Dispersion[/C][C]0.135298563869992[/C][/ROW]
[ROW][C]Observations[/C][C]63[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=196439&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=196439&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 range17
Relative range (unbiased)4.57942466547662
Relative range (biased)4.61620778381309
Variance (unbiased)13.7808499743984
Variance (biased)13.5621063240111
Standard Deviation (unbiased)3.71225672258781
Standard Deviation (biased)3.68267651634122
Coefficient of Variation (unbiased)0.175447992140309
Coefficient of Variation (biased)0.174049977891595
Mean Squared Error (MSE versus 0)461.253968253968
Mean Squared Error (MSE versus Mean)13.5621063240111
Mean Absolute Deviation from Mean (MAD Mean)2.97656840513983
Mean Absolute Deviation from Median (MAD Median)2.93650793650794
Median Absolute Deviation from Mean2.84126984126984
Median Absolute Deviation from Median2
Mean Squared Deviation from Mean13.5621063240111
Mean Squared Deviation from Median14.2698412698413
Interquartile Difference (Weighted Average at Xnp)5.25
Interquartile Difference (Weighted Average at X(n+1)p)5
Interquartile Difference (Empirical Distribution Function)5
Interquartile Difference (Empirical Distribution Function - Averaging)5
Interquartile Difference (Empirical Distribution Function - Interpolation)5
Interquartile Difference (Closest Observation)5
Interquartile Difference (True Basic - Statistics Graphics Toolkit)5
Interquartile Difference (MS Excel (old versions))5
Semi Interquartile Difference (Weighted Average at Xnp)2.625
Semi Interquartile Difference (Weighted Average at X(n+1)p)2.5
Semi Interquartile Difference (Empirical Distribution Function)2.5
Semi Interquartile Difference (Empirical Distribution Function - Averaging)2.5
Semi Interquartile Difference (Empirical Distribution Function - Interpolation)2.5
Semi Interquartile Difference (Closest Observation)2.5
Semi Interquartile Difference (True Basic - Statistics Graphics Toolkit)2.5
Semi Interquartile Difference (MS Excel (old versions))2.5
Coefficient of Quartile Variation (Weighted Average at Xnp)0.12280701754386
Coefficient of Quartile Variation (Weighted Average at X(n+1)p)0.116279069767442
Coefficient of Quartile Variation (Empirical Distribution Function)0.116279069767442
Coefficient of Quartile Variation (Empirical Distribution Function - Averaging)0.116279069767442
Coefficient of Quartile Variation (Empirical Distribution Function - Interpolation)0.116279069767442
Coefficient of Quartile Variation (Closest Observation)0.116279069767442
Coefficient of Quartile Variation (True Basic - Statistics Graphics Toolkit)0.116279069767442
Coefficient of Quartile Variation (MS Excel (old versions))0.116279069767442
Number of all Pairs of Observations1953
Squared Differences between all Pairs of Observations27.5616999487967
Mean Absolute Differences between all Pairs of Observations4.1884280593958
Gini Mean Difference4.1884280593958
Leik Measure of Dispersion0.504634223071897
Index of Diversity0.983646136590412
Index of Qualitative Variation0.999511396857999
Coefficient of Dispersion0.135298563869992
Observations63



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')