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of Irreproducible Research!

Author's title

Author*Unverified author*
R Software Modulerwasp_variability.wasp
Title produced by softwareVariability
Date of computationThu, 13 Aug 2009 03:54:46 -0600
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2009/Aug/13/t1250157312w91a3vq2pekcyr7.htm/, Retrieved Thu, 31 Oct 2024 23:41:02 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=42597, Retrieved Thu, 31 Oct 2024 23:41:02 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact261
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Variability] [Spreidingsmaten h...] [2009-08-13 09:54:46] [768ad88abce8b6ce0be22cfe8ac9beaf] [Current]
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Dataseries X:
613,20
614,70
618,40
628,20
629,00
629,70
630,40
630,40
639,30
639,40
640,90
640,80
642,10
645,30
647,60
648,40
648,80
648,90
648,90
648,90
650,30
650,30
650,00
650,00
650,50
658,40
666,00
675,50
680,70
690,60
690,60
691,10
692,90
693,80
692,80
697,50
699,00
702,10
704,80
715,50
721,80
726,40
727,70
727,40
731,30
734,40
733,40
733,40
738,10
742,60
747,20
751,10
752,60
758,90
759,10
764,30
765,60
767,60
767,60
765,60
768,20
770,90
775,10
777,60
778,60
778,90
779,40
779,90
781,70
789,10
788,70
788,80
790,80
794,10
795,10
797,30
803,80
805,60
804,60
804,50
805,80
806,80
805,20
814,90
816,60
819,50
823,00
824,00
831,40
831,70
831,10
832,10
833,30
838,80
838,00
837,30
994,20
994,20
994,20
994,20
994,20
1092,60
1100,00
1100,00
1092,60
1000,70
1000,70
1000,50
1000,50
1000,50
1000,50
1000,50
1000,50
1087,70
1113,20
1116,00
1085,20
1031,30
1028,70
1027,50
1027,50
1027,50
1027,50
1027,50
1027,50
1152,20
1155,30
1154,00
1119,90
1079,30
1074,30
1069,80




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time0 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135

\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 & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=42597&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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=42597&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=42597&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'Gwilym Jenkins' @ 72.249.127.135







Variability - Ungrouped Data
Absolute range542.1
Relative range (unbiased)3.46082046742386
Relative range (biased)3.4740045931378
Variance (unbiased)24535.8254562804
Variance (biased)24349.9479907025
Standard Deviation (unbiased)156.639156842344
Standard Deviation (biased)156.044698694645
Coefficient of Variation (unbiased)0.191471792336907
Coefficient of Variation (biased)0.190745141547259
Mean Squared Error (MSE versus 0)693604.090681818
Mean Squared Error (MSE versus Mean)24349.9479907025
Mean Absolute Deviation from Mean (MAD Mean)128.529717630854
Mean Absolute Deviation from Median (MAD Median)122.608333333333
Median Absolute Deviation from Mean127.479545454545
Median Absolute Deviation from Median88.55
Mean Squared Deviation from Mean24349.9479907025
Mean Squared Deviation from Median25865.4575
Interquartile Difference (Weighted Average at Xnp)301.4
Interquartile Difference (Weighted Average at X(n+1)p)301.375
Interquartile Difference (Empirical Distribution Function)301.4
Interquartile Difference (Empirical Distribution Function - Averaging)301.35
Interquartile Difference (Empirical Distribution Function - Interpolation)301.325
Interquartile Difference (Closest Observation)301.4
Interquartile Difference (True Basic - Statistics Graphics Toolkit)301.325
Interquartile Difference (MS Excel (old versions))301.4
Semi Interquartile Difference (Weighted Average at Xnp)150.7
Semi Interquartile Difference (Weighted Average at X(n+1)p)150.6875
Semi Interquartile Difference (Empirical Distribution Function)150.7
Semi Interquartile Difference (Empirical Distribution Function - Averaging)150.675
Semi Interquartile Difference (Empirical Distribution Function - Interpolation)150.6625
Semi Interquartile Difference (Closest Observation)150.7
Semi Interquartile Difference (True Basic - Statistics Graphics Toolkit)150.6625
Semi Interquartile Difference (MS Excel (old versions))150.7
Coefficient of Quartile Variation (Weighted Average at Xnp)0.178660343805572
Coefficient of Quartile Variation (Weighted Average at X(n+1)p)0.178642877254338
Coefficient of Quartile Variation (Empirical Distribution Function)0.178660343805572
Coefficient of Quartile Variation (Empirical Distribution Function - Averaging)0.17862541122077
Coefficient of Quartile Variation (Empirical Distribution Function - Interpolation)0.178607945704844
Coefficient of Quartile Variation (Closest Observation)0.178660343805572
Coefficient of Quartile Variation (True Basic - Statistics Graphics Toolkit)0.178607945704844
Coefficient of Quartile Variation (MS Excel (old versions))0.178660343805572
Number of all Pairs of Observations8646
Squared Differences between all Pairs of Observations49071.6509125607
Mean Absolute Differences between all Pairs of Observations173.942921582233
Gini Mean Difference173.942921582233
Leik Measure of Dispersion0.503166260215662
Index of Diversity0.99214860826497
Index of Qualitative Variation0.999722261763176
Coefficient of Dispersion0.164961454958421
Observations132

\begin{tabular}{lllllllll}
\hline
Variability - Ungrouped Data \tabularnewline
Absolute range & 542.1 \tabularnewline
Relative range (unbiased) & 3.46082046742386 \tabularnewline
Relative range (biased) & 3.4740045931378 \tabularnewline
Variance (unbiased) & 24535.8254562804 \tabularnewline
Variance (biased) & 24349.9479907025 \tabularnewline
Standard Deviation (unbiased) & 156.639156842344 \tabularnewline
Standard Deviation (biased) & 156.044698694645 \tabularnewline
Coefficient of Variation (unbiased) & 0.191471792336907 \tabularnewline
Coefficient of Variation (biased) & 0.190745141547259 \tabularnewline
Mean Squared Error (MSE versus 0) & 693604.090681818 \tabularnewline
Mean Squared Error (MSE versus Mean) & 24349.9479907025 \tabularnewline
Mean Absolute Deviation from Mean (MAD Mean) & 128.529717630854 \tabularnewline
Mean Absolute Deviation from Median (MAD Median) & 122.608333333333 \tabularnewline
Median Absolute Deviation from Mean & 127.479545454545 \tabularnewline
Median Absolute Deviation from Median & 88.55 \tabularnewline
Mean Squared Deviation from Mean & 24349.9479907025 \tabularnewline
Mean Squared Deviation from Median & 25865.4575 \tabularnewline
Interquartile Difference (Weighted Average at Xnp) & 301.4 \tabularnewline
Interquartile Difference (Weighted Average at X(n+1)p) & 301.375 \tabularnewline
Interquartile Difference (Empirical Distribution Function) & 301.4 \tabularnewline
Interquartile Difference (Empirical Distribution Function - Averaging) & 301.35 \tabularnewline
Interquartile Difference (Empirical Distribution Function - Interpolation) & 301.325 \tabularnewline
Interquartile Difference (Closest Observation) & 301.4 \tabularnewline
Interquartile Difference (True Basic - Statistics Graphics Toolkit) & 301.325 \tabularnewline
Interquartile Difference (MS Excel (old versions)) & 301.4 \tabularnewline
Semi Interquartile Difference (Weighted Average at Xnp) & 150.7 \tabularnewline
Semi Interquartile Difference (Weighted Average at X(n+1)p) & 150.6875 \tabularnewline
Semi Interquartile Difference (Empirical Distribution Function) & 150.7 \tabularnewline
Semi Interquartile Difference (Empirical Distribution Function - Averaging) & 150.675 \tabularnewline
Semi Interquartile Difference (Empirical Distribution Function - Interpolation) & 150.6625 \tabularnewline
Semi Interquartile Difference (Closest Observation) & 150.7 \tabularnewline
Semi Interquartile Difference (True Basic - Statistics Graphics Toolkit) & 150.6625 \tabularnewline
Semi Interquartile Difference (MS Excel (old versions)) & 150.7 \tabularnewline
Coefficient of Quartile Variation (Weighted Average at Xnp) & 0.178660343805572 \tabularnewline
Coefficient of Quartile Variation (Weighted Average at X(n+1)p) & 0.178642877254338 \tabularnewline
Coefficient of Quartile Variation (Empirical Distribution Function) & 0.178660343805572 \tabularnewline
Coefficient of Quartile Variation (Empirical Distribution Function - Averaging) & 0.17862541122077 \tabularnewline
Coefficient of Quartile Variation (Empirical Distribution Function - Interpolation) & 0.178607945704844 \tabularnewline
Coefficient of Quartile Variation (Closest Observation) & 0.178660343805572 \tabularnewline
Coefficient of Quartile Variation (True Basic - Statistics Graphics Toolkit) & 0.178607945704844 \tabularnewline
Coefficient of Quartile Variation (MS Excel (old versions)) & 0.178660343805572 \tabularnewline
Number of all Pairs of Observations & 8646 \tabularnewline
Squared Differences between all Pairs of Observations & 49071.6509125607 \tabularnewline
Mean Absolute Differences between all Pairs of Observations & 173.942921582233 \tabularnewline
Gini Mean Difference & 173.942921582233 \tabularnewline
Leik Measure of Dispersion & 0.503166260215662 \tabularnewline
Index of Diversity & 0.99214860826497 \tabularnewline
Index of Qualitative Variation & 0.999722261763176 \tabularnewline
Coefficient of Dispersion & 0.164961454958421 \tabularnewline
Observations & 132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=42597&T=1

[TABLE]
[ROW][C]Variability - Ungrouped Data[/C][/ROW]
[ROW][C]Absolute range[/C][C]542.1[/C][/ROW]
[ROW][C]Relative range (unbiased)[/C][C]3.46082046742386[/C][/ROW]
[ROW][C]Relative range (biased)[/C][C]3.4740045931378[/C][/ROW]
[ROW][C]Variance (unbiased)[/C][C]24535.8254562804[/C][/ROW]
[ROW][C]Variance (biased)[/C][C]24349.9479907025[/C][/ROW]
[ROW][C]Standard Deviation (unbiased)[/C][C]156.639156842344[/C][/ROW]
[ROW][C]Standard Deviation (biased)[/C][C]156.044698694645[/C][/ROW]
[ROW][C]Coefficient of Variation (unbiased)[/C][C]0.191471792336907[/C][/ROW]
[ROW][C]Coefficient of Variation (biased)[/C][C]0.190745141547259[/C][/ROW]
[ROW][C]Mean Squared Error (MSE versus 0)[/C][C]693604.090681818[/C][/ROW]
[ROW][C]Mean Squared Error (MSE versus Mean)[/C][C]24349.9479907025[/C][/ROW]
[ROW][C]Mean Absolute Deviation from Mean (MAD Mean)[/C][C]128.529717630854[/C][/ROW]
[ROW][C]Mean Absolute Deviation from Median (MAD Median)[/C][C]122.608333333333[/C][/ROW]
[ROW][C]Median Absolute Deviation from Mean[/C][C]127.479545454545[/C][/ROW]
[ROW][C]Median Absolute Deviation from Median[/C][C]88.55[/C][/ROW]
[ROW][C]Mean Squared Deviation from Mean[/C][C]24349.9479907025[/C][/ROW]
[ROW][C]Mean Squared Deviation from Median[/C][C]25865.4575[/C][/ROW]
[ROW][C]Interquartile Difference (Weighted Average at Xnp)[/C][C]301.4[/C][/ROW]
[ROW][C]Interquartile Difference (Weighted Average at X(n+1)p)[/C][C]301.375[/C][/ROW]
[ROW][C]Interquartile Difference (Empirical Distribution Function)[/C][C]301.4[/C][/ROW]
[ROW][C]Interquartile Difference (Empirical Distribution Function - Averaging)[/C][C]301.35[/C][/ROW]
[ROW][C]Interquartile Difference (Empirical Distribution Function - Interpolation)[/C][C]301.325[/C][/ROW]
[ROW][C]Interquartile Difference (Closest Observation)[/C][C]301.4[/C][/ROW]
[ROW][C]Interquartile Difference (True Basic - Statistics Graphics Toolkit)[/C][C]301.325[/C][/ROW]
[ROW][C]Interquartile Difference (MS Excel (old versions))[/C][C]301.4[/C][/ROW]
[ROW][C]Semi Interquartile Difference (Weighted Average at Xnp)[/C][C]150.7[/C][/ROW]
[ROW][C]Semi Interquartile Difference (Weighted Average at X(n+1)p)[/C][C]150.6875[/C][/ROW]
[ROW][C]Semi Interquartile Difference (Empirical Distribution Function)[/C][C]150.7[/C][/ROW]
[ROW][C]Semi Interquartile Difference (Empirical Distribution Function - Averaging)[/C][C]150.675[/C][/ROW]
[ROW][C]Semi Interquartile Difference (Empirical Distribution Function - Interpolation)[/C][C]150.6625[/C][/ROW]
[ROW][C]Semi Interquartile Difference (Closest Observation)[/C][C]150.7[/C][/ROW]
[ROW][C]Semi Interquartile Difference (True Basic - Statistics Graphics Toolkit)[/C][C]150.6625[/C][/ROW]
[ROW][C]Semi Interquartile Difference (MS Excel (old versions))[/C][C]150.7[/C][/ROW]
[ROW][C]Coefficient of Quartile Variation (Weighted Average at Xnp)[/C][C]0.178660343805572[/C][/ROW]
[ROW][C]Coefficient of Quartile Variation (Weighted Average at X(n+1)p)[/C][C]0.178642877254338[/C][/ROW]
[ROW][C]Coefficient of Quartile Variation (Empirical Distribution Function)[/C][C]0.178660343805572[/C][/ROW]
[ROW][C]Coefficient of Quartile Variation (Empirical Distribution Function - Averaging)[/C][C]0.17862541122077[/C][/ROW]
[ROW][C]Coefficient of Quartile Variation (Empirical Distribution Function - Interpolation)[/C][C]0.178607945704844[/C][/ROW]
[ROW][C]Coefficient of Quartile Variation (Closest Observation)[/C][C]0.178660343805572[/C][/ROW]
[ROW][C]Coefficient of Quartile Variation (True Basic - Statistics Graphics Toolkit)[/C][C]0.178607945704844[/C][/ROW]
[ROW][C]Coefficient of Quartile Variation (MS Excel (old versions))[/C][C]0.178660343805572[/C][/ROW]
[ROW][C]Number of all Pairs of Observations[/C][C]8646[/C][/ROW]
[ROW][C]Squared Differences between all Pairs of Observations[/C][C]49071.6509125607[/C][/ROW]
[ROW][C]Mean Absolute Differences between all Pairs of Observations[/C][C]173.942921582233[/C][/ROW]
[ROW][C]Gini Mean Difference[/C][C]173.942921582233[/C][/ROW]
[ROW][C]Leik Measure of Dispersion[/C][C]0.503166260215662[/C][/ROW]
[ROW][C]Index of Diversity[/C][C]0.99214860826497[/C][/ROW]
[ROW][C]Index of Qualitative Variation[/C][C]0.999722261763176[/C][/ROW]
[ROW][C]Coefficient of Dispersion[/C][C]0.164961454958421[/C][/ROW]
[ROW][C]Observations[/C][C]132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=42597&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=42597&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 range542.1
Relative range (unbiased)3.46082046742386
Relative range (biased)3.4740045931378
Variance (unbiased)24535.8254562804
Variance (biased)24349.9479907025
Standard Deviation (unbiased)156.639156842344
Standard Deviation (biased)156.044698694645
Coefficient of Variation (unbiased)0.191471792336907
Coefficient of Variation (biased)0.190745141547259
Mean Squared Error (MSE versus 0)693604.090681818
Mean Squared Error (MSE versus Mean)24349.9479907025
Mean Absolute Deviation from Mean (MAD Mean)128.529717630854
Mean Absolute Deviation from Median (MAD Median)122.608333333333
Median Absolute Deviation from Mean127.479545454545
Median Absolute Deviation from Median88.55
Mean Squared Deviation from Mean24349.9479907025
Mean Squared Deviation from Median25865.4575
Interquartile Difference (Weighted Average at Xnp)301.4
Interquartile Difference (Weighted Average at X(n+1)p)301.375
Interquartile Difference (Empirical Distribution Function)301.4
Interquartile Difference (Empirical Distribution Function - Averaging)301.35
Interquartile Difference (Empirical Distribution Function - Interpolation)301.325
Interquartile Difference (Closest Observation)301.4
Interquartile Difference (True Basic - Statistics Graphics Toolkit)301.325
Interquartile Difference (MS Excel (old versions))301.4
Semi Interquartile Difference (Weighted Average at Xnp)150.7
Semi Interquartile Difference (Weighted Average at X(n+1)p)150.6875
Semi Interquartile Difference (Empirical Distribution Function)150.7
Semi Interquartile Difference (Empirical Distribution Function - Averaging)150.675
Semi Interquartile Difference (Empirical Distribution Function - Interpolation)150.6625
Semi Interquartile Difference (Closest Observation)150.7
Semi Interquartile Difference (True Basic - Statistics Graphics Toolkit)150.6625
Semi Interquartile Difference (MS Excel (old versions))150.7
Coefficient of Quartile Variation (Weighted Average at Xnp)0.178660343805572
Coefficient of Quartile Variation (Weighted Average at X(n+1)p)0.178642877254338
Coefficient of Quartile Variation (Empirical Distribution Function)0.178660343805572
Coefficient of Quartile Variation (Empirical Distribution Function - Averaging)0.17862541122077
Coefficient of Quartile Variation (Empirical Distribution Function - Interpolation)0.178607945704844
Coefficient of Quartile Variation (Closest Observation)0.178660343805572
Coefficient of Quartile Variation (True Basic - Statistics Graphics Toolkit)0.178607945704844
Coefficient of Quartile Variation (MS Excel (old versions))0.178660343805572
Number of all Pairs of Observations8646
Squared Differences between all Pairs of Observations49071.6509125607
Mean Absolute Differences between all Pairs of Observations173.942921582233
Gini Mean Difference173.942921582233
Leik Measure of Dispersion0.503166260215662
Index of Diversity0.99214860826497
Index of Qualitative Variation0.999722261763176
Coefficient of Dispersion0.164961454958421
Observations132



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')