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of Irreproducible Research!

Author's title

Author*Unverified author*
R Software Modulerwasp_variability.wasp
Title produced by softwareVariability
Date of computationWed, 12 Dec 2012 06:58:33 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2012/Dec/12/t13553135237rl4w6a4pr27d6k.htm/, Retrieved Thu, 31 Oct 2024 23:34:32 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=198825, Retrieved Thu, 31 Oct 2024 23:34:32 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact106
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Variability] [] [2012-12-12 11:58:33] [f926d2a8812ea27da1e154fca8928f89] [Current]
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Dataseries X:
23,9
24,06
24,33
24,39
24,39
24,49
24,83
25,08
25,11
25,13
25,17
25,11
25,35
25,36
25,35
25,34
25,39
25,58
25,71
25,66
25,74
25,73
25,72
25,55
25,71
25,92
25,93
26
26,02
26,08
26,17
26,18
26,21
26,28
26,34
26,17
26,38
26,36
26,27
26,26
26,49
26,99
27,14
27,1
27,01
26,93
26,97
26,35
26,93
26,92
27,05
27,01
26,9
26,93
26,95
26,89
26,7
26,55
26,48
25,71
26,17
26,31
26,58
26,49
26,57
26,6
26,69
26,59
26,75
26,79
26,8
26,62




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=198825&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=198825&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=198825&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 range3.24
Relative range (unbiased)3.99944918676501
Relative range (biased)4.02751584118566
Variance (unbiased)0.656280731611894
Variance (biased)0.647165721450618
Standard Deviation (unbiased)0.810111555041584
Standard Deviation (biased)0.80446610957244
Coefficient of Variation (unbiased)0.0310965085023773
Coefficient of Variation (biased)0.0308798054545829
Mean Squared Error (MSE versus 0)679.329265277778
Mean Squared Error (MSE versus Mean)0.647165721450618
Mean Absolute Deviation from Mean (MAD Mean)0.660717592592593
Mean Absolute Deviation from Median (MAD Median)0.642083333333333
Median Absolute Deviation from Mean0.603472222222223
Median Absolute Deviation from Median0.539999999999999
Mean Squared Deviation from Mean0.647165721450618
Mean Squared Deviation from Median0.680827777777778
Interquartile Difference (Weighted Average at Xnp)1.14
Interquartile Difference (Weighted Average at X(n+1)p)1.14
Interquartile Difference (Empirical Distribution Function)1.14
Interquartile Difference (Empirical Distribution Function - Averaging)1.13
Interquartile Difference (Empirical Distribution Function - Interpolation)1.12
Interquartile Difference (Closest Observation)1.14
Interquartile Difference (True Basic - Statistics Graphics Toolkit)1.12
Interquartile Difference (MS Excel (old versions))1.15
Semi Interquartile Difference (Weighted Average at Xnp)0.57
Semi Interquartile Difference (Weighted Average at X(n+1)p)0.569999999999999
Semi Interquartile Difference (Empirical Distribution Function)0.57
Semi Interquartile Difference (Empirical Distribution Function - Averaging)0.565000000000001
Semi Interquartile Difference (Empirical Distribution Function - Interpolation)0.560000000000002
Semi Interquartile Difference (Closest Observation)0.57
Semi Interquartile Difference (True Basic - Statistics Graphics Toolkit)0.560000000000002
Semi Interquartile Difference (MS Excel (old versions))0.574999999999999
Coefficient of Quartile Variation (Weighted Average at Xnp)0.021822358346095
Coefficient of Quartile Variation (Weighted Average at X(n+1)p)0.0218160941536694
Coefficient of Quartile Variation (Empirical Distribution Function)0.021822358346095
Coefficient of Quartile Variation (Empirical Distribution Function - Averaging)0.0216226559510142
Coefficient of Quartile Variation (Empirical Distribution Function - Interpolation)0.0214292547593993
Coefficient of Quartile Variation (Closest Observation)0.021822358346095
Coefficient of Quartile Variation (True Basic - Statistics Graphics Toolkit)0.0214292547593993
Coefficient of Quartile Variation (MS Excel (old versions))0.0220095693779904
Number of all Pairs of Observations2556
Squared Differences between all Pairs of Observations1.3125614632238
Mean Absolute Differences between all Pairs of Observations0.905982003129894
Gini Mean Difference0.905982003129896
Leik Measure of Dispersion0.503004721367105
Index of Diversity0.986097867189098
Index of Qualitative Variation0.999986569543875
Coefficient of Dispersion0.0251845851950674
Observations72

\begin{tabular}{lllllllll}
\hline
Variability - Ungrouped Data \tabularnewline
Absolute range & 3.24 \tabularnewline
Relative range (unbiased) & 3.99944918676501 \tabularnewline
Relative range (biased) & 4.02751584118566 \tabularnewline
Variance (unbiased) & 0.656280731611894 \tabularnewline
Variance (biased) & 0.647165721450618 \tabularnewline
Standard Deviation (unbiased) & 0.810111555041584 \tabularnewline
Standard Deviation (biased) & 0.80446610957244 \tabularnewline
Coefficient of Variation (unbiased) & 0.0310965085023773 \tabularnewline
Coefficient of Variation (biased) & 0.0308798054545829 \tabularnewline
Mean Squared Error (MSE versus 0) & 679.329265277778 \tabularnewline
Mean Squared Error (MSE versus Mean) & 0.647165721450618 \tabularnewline
Mean Absolute Deviation from Mean (MAD Mean) & 0.660717592592593 \tabularnewline
Mean Absolute Deviation from Median (MAD Median) & 0.642083333333333 \tabularnewline
Median Absolute Deviation from Mean & 0.603472222222223 \tabularnewline
Median Absolute Deviation from Median & 0.539999999999999 \tabularnewline
Mean Squared Deviation from Mean & 0.647165721450618 \tabularnewline
Mean Squared Deviation from Median & 0.680827777777778 \tabularnewline
Interquartile Difference (Weighted Average at Xnp) & 1.14 \tabularnewline
Interquartile Difference (Weighted Average at X(n+1)p) & 1.14 \tabularnewline
Interquartile Difference (Empirical Distribution Function) & 1.14 \tabularnewline
Interquartile Difference (Empirical Distribution Function - Averaging) & 1.13 \tabularnewline
Interquartile Difference (Empirical Distribution Function - Interpolation) & 1.12 \tabularnewline
Interquartile Difference (Closest Observation) & 1.14 \tabularnewline
Interquartile Difference (True Basic - Statistics Graphics Toolkit) & 1.12 \tabularnewline
Interquartile Difference (MS Excel (old versions)) & 1.15 \tabularnewline
Semi Interquartile Difference (Weighted Average at Xnp) & 0.57 \tabularnewline
Semi Interquartile Difference (Weighted Average at X(n+1)p) & 0.569999999999999 \tabularnewline
Semi Interquartile Difference (Empirical Distribution Function) & 0.57 \tabularnewline
Semi Interquartile Difference (Empirical Distribution Function - Averaging) & 0.565000000000001 \tabularnewline
Semi Interquartile Difference (Empirical Distribution Function - Interpolation) & 0.560000000000002 \tabularnewline
Semi Interquartile Difference (Closest Observation) & 0.57 \tabularnewline
Semi Interquartile Difference (True Basic - Statistics Graphics Toolkit) & 0.560000000000002 \tabularnewline
Semi Interquartile Difference (MS Excel (old versions)) & 0.574999999999999 \tabularnewline
Coefficient of Quartile Variation (Weighted Average at Xnp) & 0.021822358346095 \tabularnewline
Coefficient of Quartile Variation (Weighted Average at X(n+1)p) & 0.0218160941536694 \tabularnewline
Coefficient of Quartile Variation (Empirical Distribution Function) & 0.021822358346095 \tabularnewline
Coefficient of Quartile Variation (Empirical Distribution Function - Averaging) & 0.0216226559510142 \tabularnewline
Coefficient of Quartile Variation (Empirical Distribution Function - Interpolation) & 0.0214292547593993 \tabularnewline
Coefficient of Quartile Variation (Closest Observation) & 0.021822358346095 \tabularnewline
Coefficient of Quartile Variation (True Basic - Statistics Graphics Toolkit) & 0.0214292547593993 \tabularnewline
Coefficient of Quartile Variation (MS Excel (old versions)) & 0.0220095693779904 \tabularnewline
Number of all Pairs of Observations & 2556 \tabularnewline
Squared Differences between all Pairs of Observations & 1.3125614632238 \tabularnewline
Mean Absolute Differences between all Pairs of Observations & 0.905982003129894 \tabularnewline
Gini Mean Difference & 0.905982003129896 \tabularnewline
Leik Measure of Dispersion & 0.503004721367105 \tabularnewline
Index of Diversity & 0.986097867189098 \tabularnewline
Index of Qualitative Variation & 0.999986569543875 \tabularnewline
Coefficient of Dispersion & 0.0251845851950674 \tabularnewline
Observations & 72 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=198825&T=1

[TABLE]
[ROW][C]Variability - Ungrouped Data[/C][/ROW]
[ROW][C]Absolute range[/C][C]3.24[/C][/ROW]
[ROW][C]Relative range (unbiased)[/C][C]3.99944918676501[/C][/ROW]
[ROW][C]Relative range (biased)[/C][C]4.02751584118566[/C][/ROW]
[ROW][C]Variance (unbiased)[/C][C]0.656280731611894[/C][/ROW]
[ROW][C]Variance (biased)[/C][C]0.647165721450618[/C][/ROW]
[ROW][C]Standard Deviation (unbiased)[/C][C]0.810111555041584[/C][/ROW]
[ROW][C]Standard Deviation (biased)[/C][C]0.80446610957244[/C][/ROW]
[ROW][C]Coefficient of Variation (unbiased)[/C][C]0.0310965085023773[/C][/ROW]
[ROW][C]Coefficient of Variation (biased)[/C][C]0.0308798054545829[/C][/ROW]
[ROW][C]Mean Squared Error (MSE versus 0)[/C][C]679.329265277778[/C][/ROW]
[ROW][C]Mean Squared Error (MSE versus Mean)[/C][C]0.647165721450618[/C][/ROW]
[ROW][C]Mean Absolute Deviation from Mean (MAD Mean)[/C][C]0.660717592592593[/C][/ROW]
[ROW][C]Mean Absolute Deviation from Median (MAD Median)[/C][C]0.642083333333333[/C][/ROW]
[ROW][C]Median Absolute Deviation from Mean[/C][C]0.603472222222223[/C][/ROW]
[ROW][C]Median Absolute Deviation from Median[/C][C]0.539999999999999[/C][/ROW]
[ROW][C]Mean Squared Deviation from Mean[/C][C]0.647165721450618[/C][/ROW]
[ROW][C]Mean Squared Deviation from Median[/C][C]0.680827777777778[/C][/ROW]
[ROW][C]Interquartile Difference (Weighted Average at Xnp)[/C][C]1.14[/C][/ROW]
[ROW][C]Interquartile Difference (Weighted Average at X(n+1)p)[/C][C]1.14[/C][/ROW]
[ROW][C]Interquartile Difference (Empirical Distribution Function)[/C][C]1.14[/C][/ROW]
[ROW][C]Interquartile Difference (Empirical Distribution Function - Averaging)[/C][C]1.13[/C][/ROW]
[ROW][C]Interquartile Difference (Empirical Distribution Function - Interpolation)[/C][C]1.12[/C][/ROW]
[ROW][C]Interquartile Difference (Closest Observation)[/C][C]1.14[/C][/ROW]
[ROW][C]Interquartile Difference (True Basic - Statistics Graphics Toolkit)[/C][C]1.12[/C][/ROW]
[ROW][C]Interquartile Difference (MS Excel (old versions))[/C][C]1.15[/C][/ROW]
[ROW][C]Semi Interquartile Difference (Weighted Average at Xnp)[/C][C]0.57[/C][/ROW]
[ROW][C]Semi Interquartile Difference (Weighted Average at X(n+1)p)[/C][C]0.569999999999999[/C][/ROW]
[ROW][C]Semi Interquartile Difference (Empirical Distribution Function)[/C][C]0.57[/C][/ROW]
[ROW][C]Semi Interquartile Difference (Empirical Distribution Function - Averaging)[/C][C]0.565000000000001[/C][/ROW]
[ROW][C]Semi Interquartile Difference (Empirical Distribution Function - Interpolation)[/C][C]0.560000000000002[/C][/ROW]
[ROW][C]Semi Interquartile Difference (Closest Observation)[/C][C]0.57[/C][/ROW]
[ROW][C]Semi Interquartile Difference (True Basic - Statistics Graphics Toolkit)[/C][C]0.560000000000002[/C][/ROW]
[ROW][C]Semi Interquartile Difference (MS Excel (old versions))[/C][C]0.574999999999999[/C][/ROW]
[ROW][C]Coefficient of Quartile Variation (Weighted Average at Xnp)[/C][C]0.021822358346095[/C][/ROW]
[ROW][C]Coefficient of Quartile Variation (Weighted Average at X(n+1)p)[/C][C]0.0218160941536694[/C][/ROW]
[ROW][C]Coefficient of Quartile Variation (Empirical Distribution Function)[/C][C]0.021822358346095[/C][/ROW]
[ROW][C]Coefficient of Quartile Variation (Empirical Distribution Function - Averaging)[/C][C]0.0216226559510142[/C][/ROW]
[ROW][C]Coefficient of Quartile Variation (Empirical Distribution Function - Interpolation)[/C][C]0.0214292547593993[/C][/ROW]
[ROW][C]Coefficient of Quartile Variation (Closest Observation)[/C][C]0.021822358346095[/C][/ROW]
[ROW][C]Coefficient of Quartile Variation (True Basic - Statistics Graphics Toolkit)[/C][C]0.0214292547593993[/C][/ROW]
[ROW][C]Coefficient of Quartile Variation (MS Excel (old versions))[/C][C]0.0220095693779904[/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]1.3125614632238[/C][/ROW]
[ROW][C]Mean Absolute Differences between all Pairs of Observations[/C][C]0.905982003129894[/C][/ROW]
[ROW][C]Gini Mean Difference[/C][C]0.905982003129896[/C][/ROW]
[ROW][C]Leik Measure of Dispersion[/C][C]0.503004721367105[/C][/ROW]
[ROW][C]Index of Diversity[/C][C]0.986097867189098[/C][/ROW]
[ROW][C]Index of Qualitative Variation[/C][C]0.999986569543875[/C][/ROW]
[ROW][C]Coefficient of Dispersion[/C][C]0.0251845851950674[/C][/ROW]
[ROW][C]Observations[/C][C]72[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=198825&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=198825&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 range3.24
Relative range (unbiased)3.99944918676501
Relative range (biased)4.02751584118566
Variance (unbiased)0.656280731611894
Variance (biased)0.647165721450618
Standard Deviation (unbiased)0.810111555041584
Standard Deviation (biased)0.80446610957244
Coefficient of Variation (unbiased)0.0310965085023773
Coefficient of Variation (biased)0.0308798054545829
Mean Squared Error (MSE versus 0)679.329265277778
Mean Squared Error (MSE versus Mean)0.647165721450618
Mean Absolute Deviation from Mean (MAD Mean)0.660717592592593
Mean Absolute Deviation from Median (MAD Median)0.642083333333333
Median Absolute Deviation from Mean0.603472222222223
Median Absolute Deviation from Median0.539999999999999
Mean Squared Deviation from Mean0.647165721450618
Mean Squared Deviation from Median0.680827777777778
Interquartile Difference (Weighted Average at Xnp)1.14
Interquartile Difference (Weighted Average at X(n+1)p)1.14
Interquartile Difference (Empirical Distribution Function)1.14
Interquartile Difference (Empirical Distribution Function - Averaging)1.13
Interquartile Difference (Empirical Distribution Function - Interpolation)1.12
Interquartile Difference (Closest Observation)1.14
Interquartile Difference (True Basic - Statistics Graphics Toolkit)1.12
Interquartile Difference (MS Excel (old versions))1.15
Semi Interquartile Difference (Weighted Average at Xnp)0.57
Semi Interquartile Difference (Weighted Average at X(n+1)p)0.569999999999999
Semi Interquartile Difference (Empirical Distribution Function)0.57
Semi Interquartile Difference (Empirical Distribution Function - Averaging)0.565000000000001
Semi Interquartile Difference (Empirical Distribution Function - Interpolation)0.560000000000002
Semi Interquartile Difference (Closest Observation)0.57
Semi Interquartile Difference (True Basic - Statistics Graphics Toolkit)0.560000000000002
Semi Interquartile Difference (MS Excel (old versions))0.574999999999999
Coefficient of Quartile Variation (Weighted Average at Xnp)0.021822358346095
Coefficient of Quartile Variation (Weighted Average at X(n+1)p)0.0218160941536694
Coefficient of Quartile Variation (Empirical Distribution Function)0.021822358346095
Coefficient of Quartile Variation (Empirical Distribution Function - Averaging)0.0216226559510142
Coefficient of Quartile Variation (Empirical Distribution Function - Interpolation)0.0214292547593993
Coefficient of Quartile Variation (Closest Observation)0.021822358346095
Coefficient of Quartile Variation (True Basic - Statistics Graphics Toolkit)0.0214292547593993
Coefficient of Quartile Variation (MS Excel (old versions))0.0220095693779904
Number of all Pairs of Observations2556
Squared Differences between all Pairs of Observations1.3125614632238
Mean Absolute Differences between all Pairs of Observations0.905982003129894
Gini Mean Difference0.905982003129896
Leik Measure of Dispersion0.503004721367105
Index of Diversity0.986097867189098
Index of Qualitative Variation0.999986569543875
Coefficient of Dispersion0.0251845851950674
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')