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 computationMon, 03 Oct 2011 16:09:02 -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/2011/Oct/03/t1317672613enx4sdt1b8rhu4m.htm/, Retrieved Thu, 31 Oct 2024 23:31:19 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=125414, Retrieved Thu, 31 Oct 2024 23:31:19 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact165
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F     [Variability] [Variability of th...] [2010-09-25 09:46:38] [b98453cac15ba1066b407e146608df68]
- R       [Variability] [Workshop 1 - Task 5] [2011-10-03 20:09:02] [c897fb90cb9e1f725365d7e541ad7850] [Current]
- RM        [Variability] [] [2012-12-20 15:55:32] [02887dc0cab5d76ef9ee7c596fbf5811]
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Dataseries X:
426.113
383.703
232.444
70.939
226.731
947.293
611.281
158.047
33.999
37.028
388.3
506.652
392.25
180.818
198.296
217.465
275.562
1030.944
57.47
136.452
556.277
213.361
274.482
220.553
236.71
260.642
2763.544
213.923
169.861
403.064
449.594
406.167
206.893
156.187
257.102
62.156
662.883
251.422
171.328
350.089
221.588
4.813
183.186
190.379
223.166
232.669
356.725
109.215
475.834
315.955
694.87
8.95
278.741
308.16
207.533
192.797
601.162
289.714
293.671
386.688
699.645
85.094
131.812
645.285
197.549
308.174
86.58
242.205
238.502
187.881
140.321
440.31
421.403
218.761
1305.923
137.55
262.517
348.821
150.034
64.016
261.596
259.7
171.26
203.077
249.148
211.655
252.64
438.555
239.89
401.915
216.886
184.641
380.155
653.641
313.906
366.936
236.302
229.641
235.577
103.898
263.906
241.171
216.548
295.281
193.299
204.386
257.567
136.813
240.755
59.609
213.511
380.531
242.344
250.407
183.613
191.835
266.793
246.542
330.563
403.556
208.108
324.04
308.532
199.297
200.156
262.875
287.069
190.157
199.746
265.777
435.956
72.844
756.46
206.771
4202.361
401.422
216.046
39.047
441.437




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'AstonUniversity' @ aston.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 & 'AstonUniversity' @ aston.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=125414&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]'AstonUniversity' @ aston.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=125414&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=125414&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'AstonUniversity' @ aston.wessa.net







Variability - Ungrouped Data
Absolute range4197.548
Relative range (unbiased)9.65231168825579
Relative range (biased)9.68722070523478
Variance (unbiased)189116.171423438
Variance (biased)187755.623427586
Standard Deviation (unbiased)434.874891691206
Standard Deviation (biased)433.307769867546
Coefficient of Variation (unbiased)1.3045953732984
Coefficient of Variation (biased)1.29989411341975
Mean Squared Error (MSE versus 0)298871.725801784
Mean Squared Error (MSE versus Mean)187755.623427586
Mean Absolute Deviation from Mean (MAD Mean)190.658904093991
Mean Absolute Deviation from Median (MAD Median)164.434194244604
Median Absolute Deviation from Mean116.454820143885
Median Absolute Deviation from Median67.003
Mean Squared Deviation from Mean187755.623427586
Mean Squared Deviation from Median196250.899172942
Interquartile Difference (Weighted Average at Xnp)166.72125
Interquartile Difference (Weighted Average at X(n+1)p)174.139
Interquartile Difference (Empirical Distribution Function)174.139
Interquartile Difference (Empirical Distribution Function - Averaging)174.139
Interquartile Difference (Empirical Distribution Function - Interpolation)168.7825
Interquartile Difference (Closest Observation)163.928
Interquartile Difference (True Basic - Statistics Graphics Toolkit)174.139
Interquartile Difference (MS Excel (old versions))174.139
Semi Interquartile Difference (Weighted Average at Xnp)83.360625
Semi Interquartile Difference (Weighted Average at X(n+1)p)87.0695
Semi Interquartile Difference (Empirical Distribution Function)87.0695
Semi Interquartile Difference (Empirical Distribution Function - Averaging)87.0695
Semi Interquartile Difference (Empirical Distribution Function - Interpolation)84.39125
Semi Interquartile Difference (Closest Observation)81.964
Semi Interquartile Difference (True Basic - Statistics Graphics Toolkit)87.0695
Semi Interquartile Difference (MS Excel (old versions))87.0695
Coefficient of Quartile Variation (Weighted Average at Xnp)0.302121968688968
Coefficient of Quartile Variation (Weighted Average at X(n+1)p)0.31111083320083
Coefficient of Quartile Variation (Empirical Distribution Function)0.31111083320083
Coefficient of Quartile Variation (Empirical Distribution Function - Averaging)0.31111083320083
Coefficient of Quartile Variation (Empirical Distribution Function - Interpolation)0.304179203194934
Coefficient of Quartile Variation (Closest Observation)0.298310167745786
Coefficient of Quartile Variation (True Basic - Statistics Graphics Toolkit)0.31111083320083
Coefficient of Quartile Variation (MS Excel (old versions))0.31111083320083
Number of all Pairs of Observations9591
Squared Differences between all Pairs of Observations378232.342846877
Mean Absolute Differences between all Pairs of Observations271.104164112189
Gini Mean Difference271.10416411219
Leik Measure of Dispersion0.546817227789221
Index of Diversity0.98064946254602
Index of Qualitative Variation0.987755618071715
Coefficient of Dispersion0.79055485151196
Observations139

\begin{tabular}{lllllllll}
\hline
Variability - Ungrouped Data \tabularnewline
Absolute range & 4197.548 \tabularnewline
Relative range (unbiased) & 9.65231168825579 \tabularnewline
Relative range (biased) & 9.68722070523478 \tabularnewline
Variance (unbiased) & 189116.171423438 \tabularnewline
Variance (biased) & 187755.623427586 \tabularnewline
Standard Deviation (unbiased) & 434.874891691206 \tabularnewline
Standard Deviation (biased) & 433.307769867546 \tabularnewline
Coefficient of Variation (unbiased) & 1.3045953732984 \tabularnewline
Coefficient of Variation (biased) & 1.29989411341975 \tabularnewline
Mean Squared Error (MSE versus 0) & 298871.725801784 \tabularnewline
Mean Squared Error (MSE versus Mean) & 187755.623427586 \tabularnewline
Mean Absolute Deviation from Mean (MAD Mean) & 190.658904093991 \tabularnewline
Mean Absolute Deviation from Median (MAD Median) & 164.434194244604 \tabularnewline
Median Absolute Deviation from Mean & 116.454820143885 \tabularnewline
Median Absolute Deviation from Median & 67.003 \tabularnewline
Mean Squared Deviation from Mean & 187755.623427586 \tabularnewline
Mean Squared Deviation from Median & 196250.899172942 \tabularnewline
Interquartile Difference (Weighted Average at Xnp) & 166.72125 \tabularnewline
Interquartile Difference (Weighted Average at X(n+1)p) & 174.139 \tabularnewline
Interquartile Difference (Empirical Distribution Function) & 174.139 \tabularnewline
Interquartile Difference (Empirical Distribution Function - Averaging) & 174.139 \tabularnewline
Interquartile Difference (Empirical Distribution Function - Interpolation) & 168.7825 \tabularnewline
Interquartile Difference (Closest Observation) & 163.928 \tabularnewline
Interquartile Difference (True Basic - Statistics Graphics Toolkit) & 174.139 \tabularnewline
Interquartile Difference (MS Excel (old versions)) & 174.139 \tabularnewline
Semi Interquartile Difference (Weighted Average at Xnp) & 83.360625 \tabularnewline
Semi Interquartile Difference (Weighted Average at X(n+1)p) & 87.0695 \tabularnewline
Semi Interquartile Difference (Empirical Distribution Function) & 87.0695 \tabularnewline
Semi Interquartile Difference (Empirical Distribution Function - Averaging) & 87.0695 \tabularnewline
Semi Interquartile Difference (Empirical Distribution Function - Interpolation) & 84.39125 \tabularnewline
Semi Interquartile Difference (Closest Observation) & 81.964 \tabularnewline
Semi Interquartile Difference (True Basic - Statistics Graphics Toolkit) & 87.0695 \tabularnewline
Semi Interquartile Difference (MS Excel (old versions)) & 87.0695 \tabularnewline
Coefficient of Quartile Variation (Weighted Average at Xnp) & 0.302121968688968 \tabularnewline
Coefficient of Quartile Variation (Weighted Average at X(n+1)p) & 0.31111083320083 \tabularnewline
Coefficient of Quartile Variation (Empirical Distribution Function) & 0.31111083320083 \tabularnewline
Coefficient of Quartile Variation (Empirical Distribution Function - Averaging) & 0.31111083320083 \tabularnewline
Coefficient of Quartile Variation (Empirical Distribution Function - Interpolation) & 0.304179203194934 \tabularnewline
Coefficient of Quartile Variation (Closest Observation) & 0.298310167745786 \tabularnewline
Coefficient of Quartile Variation (True Basic - Statistics Graphics Toolkit) & 0.31111083320083 \tabularnewline
Coefficient of Quartile Variation (MS Excel (old versions)) & 0.31111083320083 \tabularnewline
Number of all Pairs of Observations & 9591 \tabularnewline
Squared Differences between all Pairs of Observations & 378232.342846877 \tabularnewline
Mean Absolute Differences between all Pairs of Observations & 271.104164112189 \tabularnewline
Gini Mean Difference & 271.10416411219 \tabularnewline
Leik Measure of Dispersion & 0.546817227789221 \tabularnewline
Index of Diversity & 0.98064946254602 \tabularnewline
Index of Qualitative Variation & 0.987755618071715 \tabularnewline
Coefficient of Dispersion & 0.79055485151196 \tabularnewline
Observations & 139 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=125414&T=1

[TABLE]
[ROW][C]Variability - Ungrouped Data[/C][/ROW]
[ROW][C]Absolute range[/C][C]4197.548[/C][/ROW]
[ROW][C]Relative range (unbiased)[/C][C]9.65231168825579[/C][/ROW]
[ROW][C]Relative range (biased)[/C][C]9.68722070523478[/C][/ROW]
[ROW][C]Variance (unbiased)[/C][C]189116.171423438[/C][/ROW]
[ROW][C]Variance (biased)[/C][C]187755.623427586[/C][/ROW]
[ROW][C]Standard Deviation (unbiased)[/C][C]434.874891691206[/C][/ROW]
[ROW][C]Standard Deviation (biased)[/C][C]433.307769867546[/C][/ROW]
[ROW][C]Coefficient of Variation (unbiased)[/C][C]1.3045953732984[/C][/ROW]
[ROW][C]Coefficient of Variation (biased)[/C][C]1.29989411341975[/C][/ROW]
[ROW][C]Mean Squared Error (MSE versus 0)[/C][C]298871.725801784[/C][/ROW]
[ROW][C]Mean Squared Error (MSE versus Mean)[/C][C]187755.623427586[/C][/ROW]
[ROW][C]Mean Absolute Deviation from Mean (MAD Mean)[/C][C]190.658904093991[/C][/ROW]
[ROW][C]Mean Absolute Deviation from Median (MAD Median)[/C][C]164.434194244604[/C][/ROW]
[ROW][C]Median Absolute Deviation from Mean[/C][C]116.454820143885[/C][/ROW]
[ROW][C]Median Absolute Deviation from Median[/C][C]67.003[/C][/ROW]
[ROW][C]Mean Squared Deviation from Mean[/C][C]187755.623427586[/C][/ROW]
[ROW][C]Mean Squared Deviation from Median[/C][C]196250.899172942[/C][/ROW]
[ROW][C]Interquartile Difference (Weighted Average at Xnp)[/C][C]166.72125[/C][/ROW]
[ROW][C]Interquartile Difference (Weighted Average at X(n+1)p)[/C][C]174.139[/C][/ROW]
[ROW][C]Interquartile Difference (Empirical Distribution Function)[/C][C]174.139[/C][/ROW]
[ROW][C]Interquartile Difference (Empirical Distribution Function - Averaging)[/C][C]174.139[/C][/ROW]
[ROW][C]Interquartile Difference (Empirical Distribution Function - Interpolation)[/C][C]168.7825[/C][/ROW]
[ROW][C]Interquartile Difference (Closest Observation)[/C][C]163.928[/C][/ROW]
[ROW][C]Interquartile Difference (True Basic - Statistics Graphics Toolkit)[/C][C]174.139[/C][/ROW]
[ROW][C]Interquartile Difference (MS Excel (old versions))[/C][C]174.139[/C][/ROW]
[ROW][C]Semi Interquartile Difference (Weighted Average at Xnp)[/C][C]83.360625[/C][/ROW]
[ROW][C]Semi Interquartile Difference (Weighted Average at X(n+1)p)[/C][C]87.0695[/C][/ROW]
[ROW][C]Semi Interquartile Difference (Empirical Distribution Function)[/C][C]87.0695[/C][/ROW]
[ROW][C]Semi Interquartile Difference (Empirical Distribution Function - Averaging)[/C][C]87.0695[/C][/ROW]
[ROW][C]Semi Interquartile Difference (Empirical Distribution Function - Interpolation)[/C][C]84.39125[/C][/ROW]
[ROW][C]Semi Interquartile Difference (Closest Observation)[/C][C]81.964[/C][/ROW]
[ROW][C]Semi Interquartile Difference (True Basic - Statistics Graphics Toolkit)[/C][C]87.0695[/C][/ROW]
[ROW][C]Semi Interquartile Difference (MS Excel (old versions))[/C][C]87.0695[/C][/ROW]
[ROW][C]Coefficient of Quartile Variation (Weighted Average at Xnp)[/C][C]0.302121968688968[/C][/ROW]
[ROW][C]Coefficient of Quartile Variation (Weighted Average at X(n+1)p)[/C][C]0.31111083320083[/C][/ROW]
[ROW][C]Coefficient of Quartile Variation (Empirical Distribution Function)[/C][C]0.31111083320083[/C][/ROW]
[ROW][C]Coefficient of Quartile Variation (Empirical Distribution Function - Averaging)[/C][C]0.31111083320083[/C][/ROW]
[ROW][C]Coefficient of Quartile Variation (Empirical Distribution Function - Interpolation)[/C][C]0.304179203194934[/C][/ROW]
[ROW][C]Coefficient of Quartile Variation (Closest Observation)[/C][C]0.298310167745786[/C][/ROW]
[ROW][C]Coefficient of Quartile Variation (True Basic - Statistics Graphics Toolkit)[/C][C]0.31111083320083[/C][/ROW]
[ROW][C]Coefficient of Quartile Variation (MS Excel (old versions))[/C][C]0.31111083320083[/C][/ROW]
[ROW][C]Number of all Pairs of Observations[/C][C]9591[/C][/ROW]
[ROW][C]Squared Differences between all Pairs of Observations[/C][C]378232.342846877[/C][/ROW]
[ROW][C]Mean Absolute Differences between all Pairs of Observations[/C][C]271.104164112189[/C][/ROW]
[ROW][C]Gini Mean Difference[/C][C]271.10416411219[/C][/ROW]
[ROW][C]Leik Measure of Dispersion[/C][C]0.546817227789221[/C][/ROW]
[ROW][C]Index of Diversity[/C][C]0.98064946254602[/C][/ROW]
[ROW][C]Index of Qualitative Variation[/C][C]0.987755618071715[/C][/ROW]
[ROW][C]Coefficient of Dispersion[/C][C]0.79055485151196[/C][/ROW]
[ROW][C]Observations[/C][C]139[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=125414&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=125414&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 range4197.548
Relative range (unbiased)9.65231168825579
Relative range (biased)9.68722070523478
Variance (unbiased)189116.171423438
Variance (biased)187755.623427586
Standard Deviation (unbiased)434.874891691206
Standard Deviation (biased)433.307769867546
Coefficient of Variation (unbiased)1.3045953732984
Coefficient of Variation (biased)1.29989411341975
Mean Squared Error (MSE versus 0)298871.725801784
Mean Squared Error (MSE versus Mean)187755.623427586
Mean Absolute Deviation from Mean (MAD Mean)190.658904093991
Mean Absolute Deviation from Median (MAD Median)164.434194244604
Median Absolute Deviation from Mean116.454820143885
Median Absolute Deviation from Median67.003
Mean Squared Deviation from Mean187755.623427586
Mean Squared Deviation from Median196250.899172942
Interquartile Difference (Weighted Average at Xnp)166.72125
Interquartile Difference (Weighted Average at X(n+1)p)174.139
Interquartile Difference (Empirical Distribution Function)174.139
Interquartile Difference (Empirical Distribution Function - Averaging)174.139
Interquartile Difference (Empirical Distribution Function - Interpolation)168.7825
Interquartile Difference (Closest Observation)163.928
Interquartile Difference (True Basic - Statistics Graphics Toolkit)174.139
Interquartile Difference (MS Excel (old versions))174.139
Semi Interquartile Difference (Weighted Average at Xnp)83.360625
Semi Interquartile Difference (Weighted Average at X(n+1)p)87.0695
Semi Interquartile Difference (Empirical Distribution Function)87.0695
Semi Interquartile Difference (Empirical Distribution Function - Averaging)87.0695
Semi Interquartile Difference (Empirical Distribution Function - Interpolation)84.39125
Semi Interquartile Difference (Closest Observation)81.964
Semi Interquartile Difference (True Basic - Statistics Graphics Toolkit)87.0695
Semi Interquartile Difference (MS Excel (old versions))87.0695
Coefficient of Quartile Variation (Weighted Average at Xnp)0.302121968688968
Coefficient of Quartile Variation (Weighted Average at X(n+1)p)0.31111083320083
Coefficient of Quartile Variation (Empirical Distribution Function)0.31111083320083
Coefficient of Quartile Variation (Empirical Distribution Function - Averaging)0.31111083320083
Coefficient of Quartile Variation (Empirical Distribution Function - Interpolation)0.304179203194934
Coefficient of Quartile Variation (Closest Observation)0.298310167745786
Coefficient of Quartile Variation (True Basic - Statistics Graphics Toolkit)0.31111083320083
Coefficient of Quartile Variation (MS Excel (old versions))0.31111083320083
Number of all Pairs of Observations9591
Squared Differences between all Pairs of Observations378232.342846877
Mean Absolute Differences between all Pairs of Observations271.104164112189
Gini Mean Difference271.10416411219
Leik Measure of Dispersion0.546817227789221
Index of Diversity0.98064946254602
Index of Qualitative Variation0.987755618071715
Coefficient of Dispersion0.79055485151196
Observations139



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')