Free Statistics

of Irreproducible Research!

Author's title

Author*Unverified author*
R Software Modulerwasp_variability.wasp
Title produced by softwareVariability
Date of computationMon, 22 Apr 2013 03:52:39 -0400
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/Apr/22/t13666172211zb79w5i97b03mp.htm/, Retrieved Mon, 29 Apr 2024 14:12:55 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=208215, Retrieved Mon, 29 Apr 2024 14:12:55 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact109
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Variability] [oefening 3: deel 1] [2013-04-22 07:52:39] [6c59e828142382ec266fd8d68378aa9e] [Current]
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Dataseries X:
105,28
107
106,29
108,07
105,41
104,4
102,77
102,44
103,43
102,95
103,52
105,2
105,88
104,88
106,59
107,8
106,31
106,53
106,25
105,87
107,83
108,01
107,9
108,55
108,83
109,39
108,65
108,33
109,76
110,07
109,23
108,4
108,9
109,14
109,27
109,38
109,66
109,87
109,98
111,24
110,03
111,43
110,28
109,53
111,97
111,89
112,93
113,11
112,95
114,08
115,27
114,73
114,97
113,78
113,7
113,91
114,22
115,32
113,5
115,35
113,23
113,65
114,82
113,54
113,97
113,79
113,27
114,35
113,68
115,3
113,69
115,31




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

\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
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=208215&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]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=208215&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=208215&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







Variability - Ungrouped Data
Absolute range12.91
Relative range (unbiased)3.48302120517549
Relative range (biased)3.50746375912241
Variance (unbiased)13.7385294014084
Variance (biased)13.5477164930556
Standard Deviation (unbiased)3.70655222564157
Standard Deviation (biased)3.68072227871862
Coefficient of Variation (unbiased)0.0336924835018379
Coefficient of Variation (biased)0.033457689815529
Mean Squared Error (MSE versus 0)12116.0228430556
Mean Squared Error (MSE versus Mean)13.5477164930556
Mean Absolute Deviation from Mean (MAD Mean)3.13774305555556
Mean Absolute Deviation from Median (MAD Median)3.12597222222222
Median Absolute Deviation from Mean3.485
Median Absolute Deviation from Median3.44
Mean Squared Deviation from Mean13.5477164930556
Mean Squared Deviation from Median13.6384680555555
Interquartile Difference (Weighted Average at Xnp)6.65000000000001
Interquartile Difference (Weighted Average at X(n+1)p)6.47250000000001
Interquartile Difference (Empirical Distribution Function)6.65000000000001
Interquartile Difference (Empirical Distribution Function - Averaging)6.265
Interquartile Difference (Empirical Distribution Function - Interpolation)6.0575
Interquartile Difference (Closest Observation)6.65000000000001
Interquartile Difference (True Basic - Statistics Graphics Toolkit)6.05750000000002
Interquartile Difference (MS Excel (old versions))6.68000000000001
Semi Interquartile Difference (Weighted Average at Xnp)3.325
Semi Interquartile Difference (Weighted Average at X(n+1)p)3.23625000000001
Semi Interquartile Difference (Empirical Distribution Function)3.325
Semi Interquartile Difference (Empirical Distribution Function - Averaging)3.1325
Semi Interquartile Difference (Empirical Distribution Function - Interpolation)3.02875
Semi Interquartile Difference (Closest Observation)3.325
Semi Interquartile Difference (True Basic - Statistics Graphics Toolkit)3.02875000000001
Semi Interquartile Difference (MS Excel (old versions))3.34
Coefficient of Quartile Variation (Weighted Average at Xnp)0.0301382279628371
Coefficient of Quartile Variation (Weighted Average at X(n+1)p)0.0293042366070924
Coefficient of Quartile Variation (Empirical Distribution Function)0.0301382279628371
Coefficient of Quartile Variation (Empirical Distribution Function - Averaging)0.0283400809716599
Coefficient of Quartile Variation (Empirical Distribution Function - Interpolation)0.0273776030191067
Coefficient of Quartile Variation (Closest Observation)0.0301382279628371
Coefficient of Quartile Variation (True Basic - Statistics Graphics Toolkit)0.0273776030191068
Coefficient of Quartile Variation (MS Excel (old versions))0.0302700743157513
Number of all Pairs of Observations2556
Squared Differences between all Pairs of Observations27.4770588028169
Mean Absolute Differences between all Pairs of Observations4.26332942097028
Gini Mean Difference4.26332942097026
Leik Measure of Dispersion0.506200968100591
Index of Diversity0.98609556365267
Index of Qualitative Variation0.999984233563271
Coefficient of Dispersion0.0286003377591428
Observations72

\begin{tabular}{lllllllll}
\hline
Variability - Ungrouped Data \tabularnewline
Absolute range & 12.91 \tabularnewline
Relative range (unbiased) & 3.48302120517549 \tabularnewline
Relative range (biased) & 3.50746375912241 \tabularnewline
Variance (unbiased) & 13.7385294014084 \tabularnewline
Variance (biased) & 13.5477164930556 \tabularnewline
Standard Deviation (unbiased) & 3.70655222564157 \tabularnewline
Standard Deviation (biased) & 3.68072227871862 \tabularnewline
Coefficient of Variation (unbiased) & 0.0336924835018379 \tabularnewline
Coefficient of Variation (biased) & 0.033457689815529 \tabularnewline
Mean Squared Error (MSE versus 0) & 12116.0228430556 \tabularnewline
Mean Squared Error (MSE versus Mean) & 13.5477164930556 \tabularnewline
Mean Absolute Deviation from Mean (MAD Mean) & 3.13774305555556 \tabularnewline
Mean Absolute Deviation from Median (MAD Median) & 3.12597222222222 \tabularnewline
Median Absolute Deviation from Mean & 3.485 \tabularnewline
Median Absolute Deviation from Median & 3.44 \tabularnewline
Mean Squared Deviation from Mean & 13.5477164930556 \tabularnewline
Mean Squared Deviation from Median & 13.6384680555555 \tabularnewline
Interquartile Difference (Weighted Average at Xnp) & 6.65000000000001 \tabularnewline
Interquartile Difference (Weighted Average at X(n+1)p) & 6.47250000000001 \tabularnewline
Interquartile Difference (Empirical Distribution Function) & 6.65000000000001 \tabularnewline
Interquartile Difference (Empirical Distribution Function - Averaging) & 6.265 \tabularnewline
Interquartile Difference (Empirical Distribution Function - Interpolation) & 6.0575 \tabularnewline
Interquartile Difference (Closest Observation) & 6.65000000000001 \tabularnewline
Interquartile Difference (True Basic - Statistics Graphics Toolkit) & 6.05750000000002 \tabularnewline
Interquartile Difference (MS Excel (old versions)) & 6.68000000000001 \tabularnewline
Semi Interquartile Difference (Weighted Average at Xnp) & 3.325 \tabularnewline
Semi Interquartile Difference (Weighted Average at X(n+1)p) & 3.23625000000001 \tabularnewline
Semi Interquartile Difference (Empirical Distribution Function) & 3.325 \tabularnewline
Semi Interquartile Difference (Empirical Distribution Function - Averaging) & 3.1325 \tabularnewline
Semi Interquartile Difference (Empirical Distribution Function - Interpolation) & 3.02875 \tabularnewline
Semi Interquartile Difference (Closest Observation) & 3.325 \tabularnewline
Semi Interquartile Difference (True Basic - Statistics Graphics Toolkit) & 3.02875000000001 \tabularnewline
Semi Interquartile Difference (MS Excel (old versions)) & 3.34 \tabularnewline
Coefficient of Quartile Variation (Weighted Average at Xnp) & 0.0301382279628371 \tabularnewline
Coefficient of Quartile Variation (Weighted Average at X(n+1)p) & 0.0293042366070924 \tabularnewline
Coefficient of Quartile Variation (Empirical Distribution Function) & 0.0301382279628371 \tabularnewline
Coefficient of Quartile Variation (Empirical Distribution Function - Averaging) & 0.0283400809716599 \tabularnewline
Coefficient of Quartile Variation (Empirical Distribution Function - Interpolation) & 0.0273776030191067 \tabularnewline
Coefficient of Quartile Variation (Closest Observation) & 0.0301382279628371 \tabularnewline
Coefficient of Quartile Variation (True Basic - Statistics Graphics Toolkit) & 0.0273776030191068 \tabularnewline
Coefficient of Quartile Variation (MS Excel (old versions)) & 0.0302700743157513 \tabularnewline
Number of all Pairs of Observations & 2556 \tabularnewline
Squared Differences between all Pairs of Observations & 27.4770588028169 \tabularnewline
Mean Absolute Differences between all Pairs of Observations & 4.26332942097028 \tabularnewline
Gini Mean Difference & 4.26332942097026 \tabularnewline
Leik Measure of Dispersion & 0.506200968100591 \tabularnewline
Index of Diversity & 0.98609556365267 \tabularnewline
Index of Qualitative Variation & 0.999984233563271 \tabularnewline
Coefficient of Dispersion & 0.0286003377591428 \tabularnewline
Observations & 72 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=208215&T=1

[TABLE]
[ROW][C]Variability - Ungrouped Data[/C][/ROW]
[ROW][C]Absolute range[/C][C]12.91[/C][/ROW]
[ROW][C]Relative range (unbiased)[/C][C]3.48302120517549[/C][/ROW]
[ROW][C]Relative range (biased)[/C][C]3.50746375912241[/C][/ROW]
[ROW][C]Variance (unbiased)[/C][C]13.7385294014084[/C][/ROW]
[ROW][C]Variance (biased)[/C][C]13.5477164930556[/C][/ROW]
[ROW][C]Standard Deviation (unbiased)[/C][C]3.70655222564157[/C][/ROW]
[ROW][C]Standard Deviation (biased)[/C][C]3.68072227871862[/C][/ROW]
[ROW][C]Coefficient of Variation (unbiased)[/C][C]0.0336924835018379[/C][/ROW]
[ROW][C]Coefficient of Variation (biased)[/C][C]0.033457689815529[/C][/ROW]
[ROW][C]Mean Squared Error (MSE versus 0)[/C][C]12116.0228430556[/C][/ROW]
[ROW][C]Mean Squared Error (MSE versus Mean)[/C][C]13.5477164930556[/C][/ROW]
[ROW][C]Mean Absolute Deviation from Mean (MAD Mean)[/C][C]3.13774305555556[/C][/ROW]
[ROW][C]Mean Absolute Deviation from Median (MAD Median)[/C][C]3.12597222222222[/C][/ROW]
[ROW][C]Median Absolute Deviation from Mean[/C][C]3.485[/C][/ROW]
[ROW][C]Median Absolute Deviation from Median[/C][C]3.44[/C][/ROW]
[ROW][C]Mean Squared Deviation from Mean[/C][C]13.5477164930556[/C][/ROW]
[ROW][C]Mean Squared Deviation from Median[/C][C]13.6384680555555[/C][/ROW]
[ROW][C]Interquartile Difference (Weighted Average at Xnp)[/C][C]6.65000000000001[/C][/ROW]
[ROW][C]Interquartile Difference (Weighted Average at X(n+1)p)[/C][C]6.47250000000001[/C][/ROW]
[ROW][C]Interquartile Difference (Empirical Distribution Function)[/C][C]6.65000000000001[/C][/ROW]
[ROW][C]Interquartile Difference (Empirical Distribution Function - Averaging)[/C][C]6.265[/C][/ROW]
[ROW][C]Interquartile Difference (Empirical Distribution Function - Interpolation)[/C][C]6.0575[/C][/ROW]
[ROW][C]Interquartile Difference (Closest Observation)[/C][C]6.65000000000001[/C][/ROW]
[ROW][C]Interquartile Difference (True Basic - Statistics Graphics Toolkit)[/C][C]6.05750000000002[/C][/ROW]
[ROW][C]Interquartile Difference (MS Excel (old versions))[/C][C]6.68000000000001[/C][/ROW]
[ROW][C]Semi Interquartile Difference (Weighted Average at Xnp)[/C][C]3.325[/C][/ROW]
[ROW][C]Semi Interquartile Difference (Weighted Average at X(n+1)p)[/C][C]3.23625000000001[/C][/ROW]
[ROW][C]Semi Interquartile Difference (Empirical Distribution Function)[/C][C]3.325[/C][/ROW]
[ROW][C]Semi Interquartile Difference (Empirical Distribution Function - Averaging)[/C][C]3.1325[/C][/ROW]
[ROW][C]Semi Interquartile Difference (Empirical Distribution Function - Interpolation)[/C][C]3.02875[/C][/ROW]
[ROW][C]Semi Interquartile Difference (Closest Observation)[/C][C]3.325[/C][/ROW]
[ROW][C]Semi Interquartile Difference (True Basic - Statistics Graphics Toolkit)[/C][C]3.02875000000001[/C][/ROW]
[ROW][C]Semi Interquartile Difference (MS Excel (old versions))[/C][C]3.34[/C][/ROW]
[ROW][C]Coefficient of Quartile Variation (Weighted Average at Xnp)[/C][C]0.0301382279628371[/C][/ROW]
[ROW][C]Coefficient of Quartile Variation (Weighted Average at X(n+1)p)[/C][C]0.0293042366070924[/C][/ROW]
[ROW][C]Coefficient of Quartile Variation (Empirical Distribution Function)[/C][C]0.0301382279628371[/C][/ROW]
[ROW][C]Coefficient of Quartile Variation (Empirical Distribution Function - Averaging)[/C][C]0.0283400809716599[/C][/ROW]
[ROW][C]Coefficient of Quartile Variation (Empirical Distribution Function - Interpolation)[/C][C]0.0273776030191067[/C][/ROW]
[ROW][C]Coefficient of Quartile Variation (Closest Observation)[/C][C]0.0301382279628371[/C][/ROW]
[ROW][C]Coefficient of Quartile Variation (True Basic - Statistics Graphics Toolkit)[/C][C]0.0273776030191068[/C][/ROW]
[ROW][C]Coefficient of Quartile Variation (MS Excel (old versions))[/C][C]0.0302700743157513[/C][/ROW]
[ROW][C]Number of all Pairs of Observations[/C][C]2556[/C][/ROW]
[ROW][C]Squared Differences between all Pairs of Observations[/C][C]27.4770588028169[/C][/ROW]
[ROW][C]Mean Absolute Differences between all Pairs of Observations[/C][C]4.26332942097028[/C][/ROW]
[ROW][C]Gini Mean Difference[/C][C]4.26332942097026[/C][/ROW]
[ROW][C]Leik Measure of Dispersion[/C][C]0.506200968100591[/C][/ROW]
[ROW][C]Index of Diversity[/C][C]0.98609556365267[/C][/ROW]
[ROW][C]Index of Qualitative Variation[/C][C]0.999984233563271[/C][/ROW]
[ROW][C]Coefficient of Dispersion[/C][C]0.0286003377591428[/C][/ROW]
[ROW][C]Observations[/C][C]72[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=208215&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=208215&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 range12.91
Relative range (unbiased)3.48302120517549
Relative range (biased)3.50746375912241
Variance (unbiased)13.7385294014084
Variance (biased)13.5477164930556
Standard Deviation (unbiased)3.70655222564157
Standard Deviation (biased)3.68072227871862
Coefficient of Variation (unbiased)0.0336924835018379
Coefficient of Variation (biased)0.033457689815529
Mean Squared Error (MSE versus 0)12116.0228430556
Mean Squared Error (MSE versus Mean)13.5477164930556
Mean Absolute Deviation from Mean (MAD Mean)3.13774305555556
Mean Absolute Deviation from Median (MAD Median)3.12597222222222
Median Absolute Deviation from Mean3.485
Median Absolute Deviation from Median3.44
Mean Squared Deviation from Mean13.5477164930556
Mean Squared Deviation from Median13.6384680555555
Interquartile Difference (Weighted Average at Xnp)6.65000000000001
Interquartile Difference (Weighted Average at X(n+1)p)6.47250000000001
Interquartile Difference (Empirical Distribution Function)6.65000000000001
Interquartile Difference (Empirical Distribution Function - Averaging)6.265
Interquartile Difference (Empirical Distribution Function - Interpolation)6.0575
Interquartile Difference (Closest Observation)6.65000000000001
Interquartile Difference (True Basic - Statistics Graphics Toolkit)6.05750000000002
Interquartile Difference (MS Excel (old versions))6.68000000000001
Semi Interquartile Difference (Weighted Average at Xnp)3.325
Semi Interquartile Difference (Weighted Average at X(n+1)p)3.23625000000001
Semi Interquartile Difference (Empirical Distribution Function)3.325
Semi Interquartile Difference (Empirical Distribution Function - Averaging)3.1325
Semi Interquartile Difference (Empirical Distribution Function - Interpolation)3.02875
Semi Interquartile Difference (Closest Observation)3.325
Semi Interquartile Difference (True Basic - Statistics Graphics Toolkit)3.02875000000001
Semi Interquartile Difference (MS Excel (old versions))3.34
Coefficient of Quartile Variation (Weighted Average at Xnp)0.0301382279628371
Coefficient of Quartile Variation (Weighted Average at X(n+1)p)0.0293042366070924
Coefficient of Quartile Variation (Empirical Distribution Function)0.0301382279628371
Coefficient of Quartile Variation (Empirical Distribution Function - Averaging)0.0283400809716599
Coefficient of Quartile Variation (Empirical Distribution Function - Interpolation)0.0273776030191067
Coefficient of Quartile Variation (Closest Observation)0.0301382279628371
Coefficient of Quartile Variation (True Basic - Statistics Graphics Toolkit)0.0273776030191068
Coefficient of Quartile Variation (MS Excel (old versions))0.0302700743157513
Number of all Pairs of Observations2556
Squared Differences between all Pairs of Observations27.4770588028169
Mean Absolute Differences between all Pairs of Observations4.26332942097028
Gini Mean Difference4.26332942097026
Leik Measure of Dispersion0.506200968100591
Index of Diversity0.98609556365267
Index of Qualitative Variation0.999984233563271
Coefficient of Dispersion0.0286003377591428
Observations72



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')