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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 computationSun, 18 Nov 2012 10:10:44 -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/Nov/18/t1353251469rdvfd83oixn98wy.htm/, Retrieved Mon, 29 Apr 2024 19:24:16 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=190199, Retrieved Mon, 29 Apr 2024 19:24:16 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact90
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Variability] [Variability blogged] [2012-11-18 15:10:44] [4c917d823355d00d361b7013e9f37760] [Current]
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Dataseries X:
79
58
60
108
49
0
121
1
20
43
69
78
86
44
104
63
158
102
77
82
115
101
80
50
83
123
73
81
105
47
105
94
44
114
38
107
30
71
84
0
59
33
42
96
106
56
57
59
39
34
76
20
91
115
85
76
8
79
21
30
76
101
94
27
92
123
75
128
105
55
56
41
72
67
75
114
118
77
22
66
69
105
116
88
73
99
62
53
118
30
100
49
24
67
46
57
75
135
68
124
33
98
58
68
81
131
110
37
130
93
118
39
13
74
81
109
151
51
28
40
56
27
37
83
54
27
28
59
133
12
0
106
23
44
71
116
4
62
12
18
14
60
7
98
64
29
32
25
16
48
100
46
45
129
130
136
59
25
32
63
95
14
36
113
47
92
70
19
50
41
91
111
41
120
135
27
87
25
131
45
29
58
4
47
109
7
12
0
37
37
46
15
42
7
54
54
14
16
33
32
21
15
38
22
28
10
31
32
32
43
27
37
20
32
0
5
26
10
27
11
29
25
55
23
5
43
23
34
36
35
0
37
28
16
26
38
23
22
30
16
18
28
32
21
23
29
50
12
21
18
27
41
13
12
21
8
26
27
13
16
2
42
5
37
17
38
37
29
32
35
17
20
7
46
24
40
3
10
37
17
28
19
29
8
10
15
15
28
17




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=190199&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=190199&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=190199&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 range158
Relative range (unbiased)4.28188489939183
Relative range (biased)4.28931228554535
Variance (unbiased)1361.58323721646
Variance (biased)1356.87187653405
Standard Deviation (unbiased)36.8996373588746
Standard Deviation (biased)36.8357418349902
Coefficient of Variation (unbiased)0.705383992374306
Coefficient of Variation (biased)0.704162547315264
Mean Squared Error (MSE versus 0)4093.35640138408
Mean Squared Error (MSE versus Mean)1356.87187653405
Mean Absolute Deviation from Mean (MAD Mean)30.9338489721148
Mean Absolute Deviation from Median (MAD Median)29.7958477508651
Median Absolute Deviation from Mean27.3114186851211
Median Absolute Deviation from Median23
Mean Squared Deviation from Mean1356.87187653405
Mean Squared Deviation from Median1484.82006920415
Interquartile Difference (Weighted Average at Xnp)53.75
Interquartile Difference (Weighted Average at X(n+1)p)54
Interquartile Difference (Empirical Distribution Function)53
Interquartile Difference (Empirical Distribution Function - Averaging)53
Interquartile Difference (Empirical Distribution Function - Interpolation)53
Interquartile Difference (Closest Observation)54
Interquartile Difference (True Basic - Statistics Graphics Toolkit)54
Interquartile Difference (MS Excel (old versions))54
Semi Interquartile Difference (Weighted Average at Xnp)26.875
Semi Interquartile Difference (Weighted Average at X(n+1)p)27
Semi Interquartile Difference (Empirical Distribution Function)26.5
Semi Interquartile Difference (Empirical Distribution Function - Averaging)26.5
Semi Interquartile Difference (Empirical Distribution Function - Interpolation)26.5
Semi Interquartile Difference (Closest Observation)27
Semi Interquartile Difference (True Basic - Statistics Graphics Toolkit)27
Semi Interquartile Difference (MS Excel (old versions))27
Coefficient of Quartile Variation (Weighted Average at Xnp)0.536159600997506
Coefficient of Quartile Variation (Weighted Average at X(n+1)p)0.534653465346535
Coefficient of Quartile Variation (Empirical Distribution Function)0.524752475247525
Coefficient of Quartile Variation (Empirical Distribution Function - Averaging)0.524752475247525
Coefficient of Quartile Variation (Empirical Distribution Function - Interpolation)0.524752475247525
Coefficient of Quartile Variation (Closest Observation)0.54
Coefficient of Quartile Variation (True Basic - Statistics Graphics Toolkit)0.534653465346535
Coefficient of Quartile Variation (MS Excel (old versions))0.534653465346535
Number of all Pairs of Observations41616
Squared Differences between all Pairs of Observations2723.16647443291
Mean Absolute Differences between all Pairs of Observations41.2768646674356
Gini Mean Difference41.2768646674356
Leik Measure of Dispersion0.42300936337846
Index of Diversity0.994824066114043
Index of Qualitative Variation0.998278316343606
Coefficient of Dispersion0.754484121271093
Observations289

\begin{tabular}{lllllllll}
\hline
Variability - Ungrouped Data \tabularnewline
Absolute range & 158 \tabularnewline
Relative range (unbiased) & 4.28188489939183 \tabularnewline
Relative range (biased) & 4.28931228554535 \tabularnewline
Variance (unbiased) & 1361.58323721646 \tabularnewline
Variance (biased) & 1356.87187653405 \tabularnewline
Standard Deviation (unbiased) & 36.8996373588746 \tabularnewline
Standard Deviation (biased) & 36.8357418349902 \tabularnewline
Coefficient of Variation (unbiased) & 0.705383992374306 \tabularnewline
Coefficient of Variation (biased) & 0.704162547315264 \tabularnewline
Mean Squared Error (MSE versus 0) & 4093.35640138408 \tabularnewline
Mean Squared Error (MSE versus Mean) & 1356.87187653405 \tabularnewline
Mean Absolute Deviation from Mean (MAD Mean) & 30.9338489721148 \tabularnewline
Mean Absolute Deviation from Median (MAD Median) & 29.7958477508651 \tabularnewline
Median Absolute Deviation from Mean & 27.3114186851211 \tabularnewline
Median Absolute Deviation from Median & 23 \tabularnewline
Mean Squared Deviation from Mean & 1356.87187653405 \tabularnewline
Mean Squared Deviation from Median & 1484.82006920415 \tabularnewline
Interquartile Difference (Weighted Average at Xnp) & 53.75 \tabularnewline
Interquartile Difference (Weighted Average at X(n+1)p) & 54 \tabularnewline
Interquartile Difference (Empirical Distribution Function) & 53 \tabularnewline
Interquartile Difference (Empirical Distribution Function - Averaging) & 53 \tabularnewline
Interquartile Difference (Empirical Distribution Function - Interpolation) & 53 \tabularnewline
Interquartile Difference (Closest Observation) & 54 \tabularnewline
Interquartile Difference (True Basic - Statistics Graphics Toolkit) & 54 \tabularnewline
Interquartile Difference (MS Excel (old versions)) & 54 \tabularnewline
Semi Interquartile Difference (Weighted Average at Xnp) & 26.875 \tabularnewline
Semi Interquartile Difference (Weighted Average at X(n+1)p) & 27 \tabularnewline
Semi Interquartile Difference (Empirical Distribution Function) & 26.5 \tabularnewline
Semi Interquartile Difference (Empirical Distribution Function - Averaging) & 26.5 \tabularnewline
Semi Interquartile Difference (Empirical Distribution Function - Interpolation) & 26.5 \tabularnewline
Semi Interquartile Difference (Closest Observation) & 27 \tabularnewline
Semi Interquartile Difference (True Basic - Statistics Graphics Toolkit) & 27 \tabularnewline
Semi Interquartile Difference (MS Excel (old versions)) & 27 \tabularnewline
Coefficient of Quartile Variation (Weighted Average at Xnp) & 0.536159600997506 \tabularnewline
Coefficient of Quartile Variation (Weighted Average at X(n+1)p) & 0.534653465346535 \tabularnewline
Coefficient of Quartile Variation (Empirical Distribution Function) & 0.524752475247525 \tabularnewline
Coefficient of Quartile Variation (Empirical Distribution Function - Averaging) & 0.524752475247525 \tabularnewline
Coefficient of Quartile Variation (Empirical Distribution Function - Interpolation) & 0.524752475247525 \tabularnewline
Coefficient of Quartile Variation (Closest Observation) & 0.54 \tabularnewline
Coefficient of Quartile Variation (True Basic - Statistics Graphics Toolkit) & 0.534653465346535 \tabularnewline
Coefficient of Quartile Variation (MS Excel (old versions)) & 0.534653465346535 \tabularnewline
Number of all Pairs of Observations & 41616 \tabularnewline
Squared Differences between all Pairs of Observations & 2723.16647443291 \tabularnewline
Mean Absolute Differences between all Pairs of Observations & 41.2768646674356 \tabularnewline
Gini Mean Difference & 41.2768646674356 \tabularnewline
Leik Measure of Dispersion & 0.42300936337846 \tabularnewline
Index of Diversity & 0.994824066114043 \tabularnewline
Index of Qualitative Variation & 0.998278316343606 \tabularnewline
Coefficient of Dispersion & 0.754484121271093 \tabularnewline
Observations & 289 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=190199&T=1

[TABLE]
[ROW][C]Variability - Ungrouped Data[/C][/ROW]
[ROW][C]Absolute range[/C][C]158[/C][/ROW]
[ROW][C]Relative range (unbiased)[/C][C]4.28188489939183[/C][/ROW]
[ROW][C]Relative range (biased)[/C][C]4.28931228554535[/C][/ROW]
[ROW][C]Variance (unbiased)[/C][C]1361.58323721646[/C][/ROW]
[ROW][C]Variance (biased)[/C][C]1356.87187653405[/C][/ROW]
[ROW][C]Standard Deviation (unbiased)[/C][C]36.8996373588746[/C][/ROW]
[ROW][C]Standard Deviation (biased)[/C][C]36.8357418349902[/C][/ROW]
[ROW][C]Coefficient of Variation (unbiased)[/C][C]0.705383992374306[/C][/ROW]
[ROW][C]Coefficient of Variation (biased)[/C][C]0.704162547315264[/C][/ROW]
[ROW][C]Mean Squared Error (MSE versus 0)[/C][C]4093.35640138408[/C][/ROW]
[ROW][C]Mean Squared Error (MSE versus Mean)[/C][C]1356.87187653405[/C][/ROW]
[ROW][C]Mean Absolute Deviation from Mean (MAD Mean)[/C][C]30.9338489721148[/C][/ROW]
[ROW][C]Mean Absolute Deviation from Median (MAD Median)[/C][C]29.7958477508651[/C][/ROW]
[ROW][C]Median Absolute Deviation from Mean[/C][C]27.3114186851211[/C][/ROW]
[ROW][C]Median Absolute Deviation from Median[/C][C]23[/C][/ROW]
[ROW][C]Mean Squared Deviation from Mean[/C][C]1356.87187653405[/C][/ROW]
[ROW][C]Mean Squared Deviation from Median[/C][C]1484.82006920415[/C][/ROW]
[ROW][C]Interquartile Difference (Weighted Average at Xnp)[/C][C]53.75[/C][/ROW]
[ROW][C]Interquartile Difference (Weighted Average at X(n+1)p)[/C][C]54[/C][/ROW]
[ROW][C]Interquartile Difference (Empirical Distribution Function)[/C][C]53[/C][/ROW]
[ROW][C]Interquartile Difference (Empirical Distribution Function - Averaging)[/C][C]53[/C][/ROW]
[ROW][C]Interquartile Difference (Empirical Distribution Function - Interpolation)[/C][C]53[/C][/ROW]
[ROW][C]Interquartile Difference (Closest Observation)[/C][C]54[/C][/ROW]
[ROW][C]Interquartile Difference (True Basic - Statistics Graphics Toolkit)[/C][C]54[/C][/ROW]
[ROW][C]Interquartile Difference (MS Excel (old versions))[/C][C]54[/C][/ROW]
[ROW][C]Semi Interquartile Difference (Weighted Average at Xnp)[/C][C]26.875[/C][/ROW]
[ROW][C]Semi Interquartile Difference (Weighted Average at X(n+1)p)[/C][C]27[/C][/ROW]
[ROW][C]Semi Interquartile Difference (Empirical Distribution Function)[/C][C]26.5[/C][/ROW]
[ROW][C]Semi Interquartile Difference (Empirical Distribution Function - Averaging)[/C][C]26.5[/C][/ROW]
[ROW][C]Semi Interquartile Difference (Empirical Distribution Function - Interpolation)[/C][C]26.5[/C][/ROW]
[ROW][C]Semi Interquartile Difference (Closest Observation)[/C][C]27[/C][/ROW]
[ROW][C]Semi Interquartile Difference (True Basic - Statistics Graphics Toolkit)[/C][C]27[/C][/ROW]
[ROW][C]Semi Interquartile Difference (MS Excel (old versions))[/C][C]27[/C][/ROW]
[ROW][C]Coefficient of Quartile Variation (Weighted Average at Xnp)[/C][C]0.536159600997506[/C][/ROW]
[ROW][C]Coefficient of Quartile Variation (Weighted Average at X(n+1)p)[/C][C]0.534653465346535[/C][/ROW]
[ROW][C]Coefficient of Quartile Variation (Empirical Distribution Function)[/C][C]0.524752475247525[/C][/ROW]
[ROW][C]Coefficient of Quartile Variation (Empirical Distribution Function - Averaging)[/C][C]0.524752475247525[/C][/ROW]
[ROW][C]Coefficient of Quartile Variation (Empirical Distribution Function - Interpolation)[/C][C]0.524752475247525[/C][/ROW]
[ROW][C]Coefficient of Quartile Variation (Closest Observation)[/C][C]0.54[/C][/ROW]
[ROW][C]Coefficient of Quartile Variation (True Basic - Statistics Graphics Toolkit)[/C][C]0.534653465346535[/C][/ROW]
[ROW][C]Coefficient of Quartile Variation (MS Excel (old versions))[/C][C]0.534653465346535[/C][/ROW]
[ROW][C]Number of all Pairs of Observations[/C][C]41616[/C][/ROW]
[ROW][C]Squared Differences between all Pairs of Observations[/C][C]2723.16647443291[/C][/ROW]
[ROW][C]Mean Absolute Differences between all Pairs of Observations[/C][C]41.2768646674356[/C][/ROW]
[ROW][C]Gini Mean Difference[/C][C]41.2768646674356[/C][/ROW]
[ROW][C]Leik Measure of Dispersion[/C][C]0.42300936337846[/C][/ROW]
[ROW][C]Index of Diversity[/C][C]0.994824066114043[/C][/ROW]
[ROW][C]Index of Qualitative Variation[/C][C]0.998278316343606[/C][/ROW]
[ROW][C]Coefficient of Dispersion[/C][C]0.754484121271093[/C][/ROW]
[ROW][C]Observations[/C][C]289[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=190199&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=190199&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 range158
Relative range (unbiased)4.28188489939183
Relative range (biased)4.28931228554535
Variance (unbiased)1361.58323721646
Variance (biased)1356.87187653405
Standard Deviation (unbiased)36.8996373588746
Standard Deviation (biased)36.8357418349902
Coefficient of Variation (unbiased)0.705383992374306
Coefficient of Variation (biased)0.704162547315264
Mean Squared Error (MSE versus 0)4093.35640138408
Mean Squared Error (MSE versus Mean)1356.87187653405
Mean Absolute Deviation from Mean (MAD Mean)30.9338489721148
Mean Absolute Deviation from Median (MAD Median)29.7958477508651
Median Absolute Deviation from Mean27.3114186851211
Median Absolute Deviation from Median23
Mean Squared Deviation from Mean1356.87187653405
Mean Squared Deviation from Median1484.82006920415
Interquartile Difference (Weighted Average at Xnp)53.75
Interquartile Difference (Weighted Average at X(n+1)p)54
Interquartile Difference (Empirical Distribution Function)53
Interquartile Difference (Empirical Distribution Function - Averaging)53
Interquartile Difference (Empirical Distribution Function - Interpolation)53
Interquartile Difference (Closest Observation)54
Interquartile Difference (True Basic - Statistics Graphics Toolkit)54
Interquartile Difference (MS Excel (old versions))54
Semi Interquartile Difference (Weighted Average at Xnp)26.875
Semi Interquartile Difference (Weighted Average at X(n+1)p)27
Semi Interquartile Difference (Empirical Distribution Function)26.5
Semi Interquartile Difference (Empirical Distribution Function - Averaging)26.5
Semi Interquartile Difference (Empirical Distribution Function - Interpolation)26.5
Semi Interquartile Difference (Closest Observation)27
Semi Interquartile Difference (True Basic - Statistics Graphics Toolkit)27
Semi Interquartile Difference (MS Excel (old versions))27
Coefficient of Quartile Variation (Weighted Average at Xnp)0.536159600997506
Coefficient of Quartile Variation (Weighted Average at X(n+1)p)0.534653465346535
Coefficient of Quartile Variation (Empirical Distribution Function)0.524752475247525
Coefficient of Quartile Variation (Empirical Distribution Function - Averaging)0.524752475247525
Coefficient of Quartile Variation (Empirical Distribution Function - Interpolation)0.524752475247525
Coefficient of Quartile Variation (Closest Observation)0.54
Coefficient of Quartile Variation (True Basic - Statistics Graphics Toolkit)0.534653465346535
Coefficient of Quartile Variation (MS Excel (old versions))0.534653465346535
Number of all Pairs of Observations41616
Squared Differences between all Pairs of Observations2723.16647443291
Mean Absolute Differences between all Pairs of Observations41.2768646674356
Gini Mean Difference41.2768646674356
Leik Measure of Dispersion0.42300936337846
Index of Diversity0.994824066114043
Index of Qualitative Variation0.998278316343606
Coefficient of Dispersion0.754484121271093
Observations289



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')