Free Statistics

of Irreproducible Research!

Author's title

Author*Unverified author*
R Software Modulerwasp_variability.wasp
Title produced by softwareVariability
Date of computationTue, 25 Apr 2017 15:28:12 +0100
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2017/Apr/25/t1493130532potln9zdqnb0yvh.htm/, Retrieved Sat, 11 May 2024 19:11:37 +0200
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=, Retrieved Sat, 11 May 2024 19:11:37 +0200
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact0
Dataseries X:
95,2
95,34
95,32
96,04
99,65
100,85
108,18
108,18
103,14
99,71
99,39
98,99
98,83
99,52
99,5
99,5
99,39
101,79
106,03
105,41
104,32
101,17
99,79
100,08
100,27
101,63
101,74
103,73
103,29
105,71
107,42
107,57
105,13
103,61
102,35
102,14
104,32
104,69
106,02
104,78
106,36
109,27
113,46
113,46
110,61
104,37
103,82
104,1




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

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=&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'George Udny Yule' @ yule.wessa.net







Variability - Ungrouped Data
Absolute range18.26
Relative range (unbiased)4.27586742136544
Relative range (biased)4.32111595575438
Variance (unbiased)18.2369868351064
Variance (biased)17.857049609375
Standard Deviation (unbiased)4.27047852530678
Standard Deviation (biased)4.22576024040349
Coefficient of Variation (unbiased)0.0414511471222881
Coefficient of Variation (biased)0.0410170917358489
Mean Squared Error (MSE versus 0)10631.87889375
Mean Squared Error (MSE versus Mean)17.857049609375
Mean Absolute Deviation from Mean (MAD Mean)3.39044270833333
Mean Absolute Deviation from Median (MAD Median)3.385625
Median Absolute Deviation from Mean3.00062500000001
Median Absolute Deviation from Median3.04000000000001
Mean Squared Deviation from Mean17.857049609375
Mean Squared Deviation from Median17.8933875
Interquartile Difference (Weighted Average at Xnp)5.75999999999999
Interquartile Difference (Weighted Average at X(n+1)p)5.96999999999998
Interquartile Difference (Empirical Distribution Function)5.75999999999999
Interquartile Difference (Empirical Distribution Function - Averaging)5.88
Interquartile Difference (Empirical Distribution Function - Interpolation)5.79000000000001
Interquartile Difference (Closest Observation)5.75999999999999
Interquartile Difference (True Basic - Statistics Graphics Toolkit)5.79000000000001
Interquartile Difference (MS Excel (old versions))6.05999999999999
Semi Interquartile Difference (Weighted Average at Xnp)2.88
Semi Interquartile Difference (Weighted Average at X(n+1)p)2.98499999999999
Semi Interquartile Difference (Empirical Distribution Function)2.88
Semi Interquartile Difference (Empirical Distribution Function - Averaging)2.94
Semi Interquartile Difference (Empirical Distribution Function - Interpolation)2.895
Semi Interquartile Difference (Closest Observation)2.88
Semi Interquartile Difference (True Basic - Statistics Graphics Toolkit)2.895
Semi Interquartile Difference (MS Excel (old versions))3.02999999999999
Coefficient of Quartile Variation (Weighted Average at Xnp)0.028089339705452
Coefficient of Quartile Variation (Weighted Average at X(n+1)p)0.029079396005845
Coefficient of Quartile Variation (Empirical Distribution Function)0.028089339705452
Coefficient of Quartile Variation (Empirical Distribution Function - Averaging)0.0286493860845839
Coefficient of Quartile Variation (Empirical Distribution Function - Interpolation)0.0282191246710206
Coefficient of Quartile Variation (Closest Observation)0.028089339705452
Coefficient of Quartile Variation (True Basic - Statistics Graphics Toolkit)0.0282191246710206
Coefficient of Quartile Variation (MS Excel (old versions))0.0295091546552395
Number of all Pairs of Observations1128
Squared Differences between all Pairs of Observations36.4739736702127
Mean Absolute Differences between all Pairs of Observations4.81995567375886
Gini Mean Difference4.81995567375887
Leik Measure of Dispersion0.510777698884263
Index of Diversity0.979131616628865
Index of Qualitative Variation0.999964204216714
Coefficient of Dispersion0.0328483525488866
Observations48

\begin{tabular}{lllllllll}
\hline
Variability - Ungrouped Data \tabularnewline
Absolute range & 18.26 \tabularnewline
Relative range (unbiased) & 4.27586742136544 \tabularnewline
Relative range (biased) & 4.32111595575438 \tabularnewline
Variance (unbiased) & 18.2369868351064 \tabularnewline
Variance (biased) & 17.857049609375 \tabularnewline
Standard Deviation (unbiased) & 4.27047852530678 \tabularnewline
Standard Deviation (biased) & 4.22576024040349 \tabularnewline
Coefficient of Variation (unbiased) & 0.0414511471222881 \tabularnewline
Coefficient of Variation (biased) & 0.0410170917358489 \tabularnewline
Mean Squared Error (MSE versus 0) & 10631.87889375 \tabularnewline
Mean Squared Error (MSE versus Mean) & 17.857049609375 \tabularnewline
Mean Absolute Deviation from Mean (MAD Mean) & 3.39044270833333 \tabularnewline
Mean Absolute Deviation from Median (MAD Median) & 3.385625 \tabularnewline
Median Absolute Deviation from Mean & 3.00062500000001 \tabularnewline
Median Absolute Deviation from Median & 3.04000000000001 \tabularnewline
Mean Squared Deviation from Mean & 17.857049609375 \tabularnewline
Mean Squared Deviation from Median & 17.8933875 \tabularnewline
Interquartile Difference (Weighted Average at Xnp) & 5.75999999999999 \tabularnewline
Interquartile Difference (Weighted Average at X(n+1)p) & 5.96999999999998 \tabularnewline
Interquartile Difference (Empirical Distribution Function) & 5.75999999999999 \tabularnewline
Interquartile Difference (Empirical Distribution Function - Averaging) & 5.88 \tabularnewline
Interquartile Difference (Empirical Distribution Function - Interpolation) & 5.79000000000001 \tabularnewline
Interquartile Difference (Closest Observation) & 5.75999999999999 \tabularnewline
Interquartile Difference (True Basic - Statistics Graphics Toolkit) & 5.79000000000001 \tabularnewline
Interquartile Difference (MS Excel (old versions)) & 6.05999999999999 \tabularnewline
Semi Interquartile Difference (Weighted Average at Xnp) & 2.88 \tabularnewline
Semi Interquartile Difference (Weighted Average at X(n+1)p) & 2.98499999999999 \tabularnewline
Semi Interquartile Difference (Empirical Distribution Function) & 2.88 \tabularnewline
Semi Interquartile Difference (Empirical Distribution Function - Averaging) & 2.94 \tabularnewline
Semi Interquartile Difference (Empirical Distribution Function - Interpolation) & 2.895 \tabularnewline
Semi Interquartile Difference (Closest Observation) & 2.88 \tabularnewline
Semi Interquartile Difference (True Basic - Statistics Graphics Toolkit) & 2.895 \tabularnewline
Semi Interquartile Difference (MS Excel (old versions)) & 3.02999999999999 \tabularnewline
Coefficient of Quartile Variation (Weighted Average at Xnp) & 0.028089339705452 \tabularnewline
Coefficient of Quartile Variation (Weighted Average at X(n+1)p) & 0.029079396005845 \tabularnewline
Coefficient of Quartile Variation (Empirical Distribution Function) & 0.028089339705452 \tabularnewline
Coefficient of Quartile Variation (Empirical Distribution Function - Averaging) & 0.0286493860845839 \tabularnewline
Coefficient of Quartile Variation (Empirical Distribution Function - Interpolation) & 0.0282191246710206 \tabularnewline
Coefficient of Quartile Variation (Closest Observation) & 0.028089339705452 \tabularnewline
Coefficient of Quartile Variation (True Basic - Statistics Graphics Toolkit) & 0.0282191246710206 \tabularnewline
Coefficient of Quartile Variation (MS Excel (old versions)) & 0.0295091546552395 \tabularnewline
Number of all Pairs of Observations & 1128 \tabularnewline
Squared Differences between all Pairs of Observations & 36.4739736702127 \tabularnewline
Mean Absolute Differences between all Pairs of Observations & 4.81995567375886 \tabularnewline
Gini Mean Difference & 4.81995567375887 \tabularnewline
Leik Measure of Dispersion & 0.510777698884263 \tabularnewline
Index of Diversity & 0.979131616628865 \tabularnewline
Index of Qualitative Variation & 0.999964204216714 \tabularnewline
Coefficient of Dispersion & 0.0328483525488866 \tabularnewline
Observations & 48 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=&T=1

[TABLE]
[ROW][C]Variability - Ungrouped Data[/C][/ROW]
[ROW][C]Absolute range[/C][C]18.26[/C][/ROW]
[ROW][C]Relative range (unbiased)[/C][C]4.27586742136544[/C][/ROW]
[ROW][C]Relative range (biased)[/C][C]4.32111595575438[/C][/ROW]
[ROW][C]Variance (unbiased)[/C][C]18.2369868351064[/C][/ROW]
[ROW][C]Variance (biased)[/C][C]17.857049609375[/C][/ROW]
[ROW][C]Standard Deviation (unbiased)[/C][C]4.27047852530678[/C][/ROW]
[ROW][C]Standard Deviation (biased)[/C][C]4.22576024040349[/C][/ROW]
[ROW][C]Coefficient of Variation (unbiased)[/C][C]0.0414511471222881[/C][/ROW]
[ROW][C]Coefficient of Variation (biased)[/C][C]0.0410170917358489[/C][/ROW]
[ROW][C]Mean Squared Error (MSE versus 0)[/C][C]10631.87889375[/C][/ROW]
[ROW][C]Mean Squared Error (MSE versus Mean)[/C][C]17.857049609375[/C][/ROW]
[ROW][C]Mean Absolute Deviation from Mean (MAD Mean)[/C][C]3.39044270833333[/C][/ROW]
[ROW][C]Mean Absolute Deviation from Median (MAD Median)[/C][C]3.385625[/C][/ROW]
[ROW][C]Median Absolute Deviation from Mean[/C][C]3.00062500000001[/C][/ROW]
[ROW][C]Median Absolute Deviation from Median[/C][C]3.04000000000001[/C][/ROW]
[ROW][C]Mean Squared Deviation from Mean[/C][C]17.857049609375[/C][/ROW]
[ROW][C]Mean Squared Deviation from Median[/C][C]17.8933875[/C][/ROW]
[ROW][C]Interquartile Difference (Weighted Average at Xnp)[/C][C]5.75999999999999[/C][/ROW]
[ROW][C]Interquartile Difference (Weighted Average at X(n+1)p)[/C][C]5.96999999999998[/C][/ROW]
[ROW][C]Interquartile Difference (Empirical Distribution Function)[/C][C]5.75999999999999[/C][/ROW]
[ROW][C]Interquartile Difference (Empirical Distribution Function - Averaging)[/C][C]5.88[/C][/ROW]
[ROW][C]Interquartile Difference (Empirical Distribution Function - Interpolation)[/C][C]5.79000000000001[/C][/ROW]
[ROW][C]Interquartile Difference (Closest Observation)[/C][C]5.75999999999999[/C][/ROW]
[ROW][C]Interquartile Difference (True Basic - Statistics Graphics Toolkit)[/C][C]5.79000000000001[/C][/ROW]
[ROW][C]Interquartile Difference (MS Excel (old versions))[/C][C]6.05999999999999[/C][/ROW]
[ROW][C]Semi Interquartile Difference (Weighted Average at Xnp)[/C][C]2.88[/C][/ROW]
[ROW][C]Semi Interquartile Difference (Weighted Average at X(n+1)p)[/C][C]2.98499999999999[/C][/ROW]
[ROW][C]Semi Interquartile Difference (Empirical Distribution Function)[/C][C]2.88[/C][/ROW]
[ROW][C]Semi Interquartile Difference (Empirical Distribution Function - Averaging)[/C][C]2.94[/C][/ROW]
[ROW][C]Semi Interquartile Difference (Empirical Distribution Function - Interpolation)[/C][C]2.895[/C][/ROW]
[ROW][C]Semi Interquartile Difference (Closest Observation)[/C][C]2.88[/C][/ROW]
[ROW][C]Semi Interquartile Difference (True Basic - Statistics Graphics Toolkit)[/C][C]2.895[/C][/ROW]
[ROW][C]Semi Interquartile Difference (MS Excel (old versions))[/C][C]3.02999999999999[/C][/ROW]
[ROW][C]Coefficient of Quartile Variation (Weighted Average at Xnp)[/C][C]0.028089339705452[/C][/ROW]
[ROW][C]Coefficient of Quartile Variation (Weighted Average at X(n+1)p)[/C][C]0.029079396005845[/C][/ROW]
[ROW][C]Coefficient of Quartile Variation (Empirical Distribution Function)[/C][C]0.028089339705452[/C][/ROW]
[ROW][C]Coefficient of Quartile Variation (Empirical Distribution Function - Averaging)[/C][C]0.0286493860845839[/C][/ROW]
[ROW][C]Coefficient of Quartile Variation (Empirical Distribution Function - Interpolation)[/C][C]0.0282191246710206[/C][/ROW]
[ROW][C]Coefficient of Quartile Variation (Closest Observation)[/C][C]0.028089339705452[/C][/ROW]
[ROW][C]Coefficient of Quartile Variation (True Basic - Statistics Graphics Toolkit)[/C][C]0.0282191246710206[/C][/ROW]
[ROW][C]Coefficient of Quartile Variation (MS Excel (old versions))[/C][C]0.0295091546552395[/C][/ROW]
[ROW][C]Number of all Pairs of Observations[/C][C]1128[/C][/ROW]
[ROW][C]Squared Differences between all Pairs of Observations[/C][C]36.4739736702127[/C][/ROW]
[ROW][C]Mean Absolute Differences between all Pairs of Observations[/C][C]4.81995567375886[/C][/ROW]
[ROW][C]Gini Mean Difference[/C][C]4.81995567375887[/C][/ROW]
[ROW][C]Leik Measure of Dispersion[/C][C]0.510777698884263[/C][/ROW]
[ROW][C]Index of Diversity[/C][C]0.979131616628865[/C][/ROW]
[ROW][C]Index of Qualitative Variation[/C][C]0.999964204216714[/C][/ROW]
[ROW][C]Coefficient of Dispersion[/C][C]0.0328483525488866[/C][/ROW]
[ROW][C]Observations[/C][C]48[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=&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 range18.26
Relative range (unbiased)4.27586742136544
Relative range (biased)4.32111595575438
Variance (unbiased)18.2369868351064
Variance (biased)17.857049609375
Standard Deviation (unbiased)4.27047852530678
Standard Deviation (biased)4.22576024040349
Coefficient of Variation (unbiased)0.0414511471222881
Coefficient of Variation (biased)0.0410170917358489
Mean Squared Error (MSE versus 0)10631.87889375
Mean Squared Error (MSE versus Mean)17.857049609375
Mean Absolute Deviation from Mean (MAD Mean)3.39044270833333
Mean Absolute Deviation from Median (MAD Median)3.385625
Median Absolute Deviation from Mean3.00062500000001
Median Absolute Deviation from Median3.04000000000001
Mean Squared Deviation from Mean17.857049609375
Mean Squared Deviation from Median17.8933875
Interquartile Difference (Weighted Average at Xnp)5.75999999999999
Interquartile Difference (Weighted Average at X(n+1)p)5.96999999999998
Interquartile Difference (Empirical Distribution Function)5.75999999999999
Interquartile Difference (Empirical Distribution Function - Averaging)5.88
Interquartile Difference (Empirical Distribution Function - Interpolation)5.79000000000001
Interquartile Difference (Closest Observation)5.75999999999999
Interquartile Difference (True Basic - Statistics Graphics Toolkit)5.79000000000001
Interquartile Difference (MS Excel (old versions))6.05999999999999
Semi Interquartile Difference (Weighted Average at Xnp)2.88
Semi Interquartile Difference (Weighted Average at X(n+1)p)2.98499999999999
Semi Interquartile Difference (Empirical Distribution Function)2.88
Semi Interquartile Difference (Empirical Distribution Function - Averaging)2.94
Semi Interquartile Difference (Empirical Distribution Function - Interpolation)2.895
Semi Interquartile Difference (Closest Observation)2.88
Semi Interquartile Difference (True Basic - Statistics Graphics Toolkit)2.895
Semi Interquartile Difference (MS Excel (old versions))3.02999999999999
Coefficient of Quartile Variation (Weighted Average at Xnp)0.028089339705452
Coefficient of Quartile Variation (Weighted Average at X(n+1)p)0.029079396005845
Coefficient of Quartile Variation (Empirical Distribution Function)0.028089339705452
Coefficient of Quartile Variation (Empirical Distribution Function - Averaging)0.0286493860845839
Coefficient of Quartile Variation (Empirical Distribution Function - Interpolation)0.0282191246710206
Coefficient of Quartile Variation (Closest Observation)0.028089339705452
Coefficient of Quartile Variation (True Basic - Statistics Graphics Toolkit)0.0282191246710206
Coefficient of Quartile Variation (MS Excel (old versions))0.0295091546552395
Number of all Pairs of Observations1128
Squared Differences between all Pairs of Observations36.4739736702127
Mean Absolute Differences between all Pairs of Observations4.81995567375886
Gini Mean Difference4.81995567375887
Leik Measure of Dispersion0.510777698884263
Index of Diversity0.979131616628865
Index of Qualitative Variation0.999964204216714
Coefficient of Dispersion0.0328483525488866
Observations48



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')