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Author's title

Author

*The author of this computation has been verified*

R Software Module

rwasp_smp.wasp

Title produced by software

Standard Deviation-Mean Plot

Date of computation

Tue, 14 Dec 2010 10:34:22 +0000

Cite this page as follows

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Dec/14/t1292322759t82aw0xo6nszd8d.htm/, Retrieved Thu, 02 May 2024 14:15:50 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=109363, Retrieved Thu, 02 May 2024 14:15:50 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

145

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)

-     [(Partial) Autocorrelation Function] [Faillissementen V...] [2010-12-14 08:51:21] [13c73ac943380855a1c72833078e44d2]
-   P   [(Partial) Autocorrelation Function] [Faillissementen V...] [2010-12-14 09:09:28] [13c73ac943380855a1c72833078e44d2]
- RMP     [Spectral Analysis] [Faillissementen V...] [2010-12-14 09:27:52] [13c73ac943380855a1c72833078e44d2]
- RMPD      [(Partial) Autocorrelation Function] [Faillissementen W...] [2010-12-14 10:11:32] [049b50ae610f671f7417ed8e2d1295c1]
- RM          [Spectral Analysis] [Faillissementen W...] [2010-12-14 10:17:19] [049b50ae610f671f7417ed8e2d1295c1]
- RM              [Standard Deviation-Mean Plot] [Faillissementen W...] [2010-12-14 10:34:22] [9003764b6a75599accb6eea9154ba195] [Current]

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Boxplots

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	1 seconds
R Server	'Gwilym Jenkins' @ 72.249.127.135

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 1 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=109363&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' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=109363&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=109363&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 Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	1 seconds
R Server	'Gwilym Jenkins' @ 72.249.127.135

Standard Deviation-Mean Plot
Section	Mean	Standard Deviation	Range
1	192.916666666667	43.1223593833626	130
2	194.666666666667	50.1023195495221	158
3	185.166666666667	40.210431331668	135
4	183.416666666667	50.4443137318646	168
5	199.166666666667	57.7893247979768	218
6	220.75	56.9515344194278	224

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 192.916666666667 & 43.1223593833626 & 130 \tabularnewline
2 & 194.666666666667 & 50.1023195495221 & 158 \tabularnewline
3 & 185.166666666667 & 40.210431331668 & 135 \tabularnewline
4 & 183.416666666667 & 50.4443137318646 & 168 \tabularnewline
5 & 199.166666666667 & 57.7893247979768 & 218 \tabularnewline
6 & 220.75 & 56.9515344194278 & 224 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=109363&T=1

[TABLE]
[ROW][C]Standard Deviation-Mean Plot[/C][/ROW]
[ROW][C]Section[/C][C]Mean[/C][C]Standard Deviation[/C][C]Range[/C][/ROW]
[ROW][C]1[/C][C]192.916666666667[/C][C]43.1223593833626[/C][C]130[/C][/ROW]
[ROW][C]2[/C][C]194.666666666667[/C][C]50.1023195495221[/C][C]158[/C][/ROW]
[ROW][C]3[/C][C]185.166666666667[/C][C]40.210431331668[/C][C]135[/C][/ROW]
[ROW][C]4[/C][C]183.416666666667[/C][C]50.4443137318646[/C][C]168[/C][/ROW]
[ROW][C]5[/C][C]199.166666666667[/C][C]57.7893247979768[/C][C]218[/C][/ROW]
[ROW][C]6[/C][C]220.75[/C][C]56.9515344194278[/C][C]224[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=109363&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=109363&T=1

As an alternative you can also use a QR Code:

The GUIDs for individual cells are displayed in the table below:

Standard Deviation-Mean Plot
Section	Mean	Standard Deviation	Range
1	192.916666666667	43.1223593833626	130
2	194.666666666667	50.1023195495221	158
3	185.166666666667	40.210431331668	135
4	183.416666666667	50.4443137318646	168
5	199.166666666667	57.7893247979768	218
6	220.75	56.9515344194278	224

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	-18.8168948448242
beta	0.349908582682152
S.D.	0.196624356906031
T-STAT	1.77957903175433
p-value	0.149757734532485

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -18.8168948448242 \tabularnewline
beta & 0.349908582682152 \tabularnewline
S.D. & 0.196624356906031 \tabularnewline
T-STAT & 1.77957903175433 \tabularnewline
p-value & 0.149757734532485 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=109363&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-18.8168948448242[/C][/ROW]
[ROW][C]beta[/C][C]0.349908582682152[/C][/ROW]
[ROW][C]S.D.[/C][C]0.196624356906031[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.77957903175433[/C][/ROW]
[ROW][C]p-value[/C][C]0.149757734532485[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=109363&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=109363&T=2

As an alternative you can also use a QR Code:

The GUIDs for individual cells are displayed in the table below:

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	-18.8168948448242
beta	0.349908582682152
S.D.	0.196624356906031
T-STAT	1.77957903175433
p-value	0.149757734532485

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	-3.61886957216169
beta	1.42478055617392
S.D.	0.826789335473743
T-STAT	1.72326915097125
p-value	0.159936992696661
Lambda	-0.42478055617392

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -3.61886957216169 \tabularnewline
beta & 1.42478055617392 \tabularnewline
S.D. & 0.826789335473743 \tabularnewline
T-STAT & 1.72326915097125 \tabularnewline
p-value & 0.159936992696661 \tabularnewline
Lambda & -0.42478055617392 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=109363&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-3.61886957216169[/C][/ROW]
[ROW][C]beta[/C][C]1.42478055617392[/C][/ROW]
[ROW][C]S.D.[/C][C]0.826789335473743[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.72326915097125[/C][/ROW]
[ROW][C]p-value[/C][C]0.159936992696661[/C][/ROW]
[ROW][C]Lambda[/C][C]-0.42478055617392[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=109363&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=109363&T=3

As an alternative you can also use a QR Code:

The GUIDs for individual cells are displayed in the table below:

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	-3.61886957216169
beta	1.42478055617392
S.D.	0.826789335473743
T-STAT	1.72326915097125
p-value	0.159936992696661
Lambda	-0.42478055617392

Figure 1

PNG link

Postscript link

PDF link

Figure 2

PNG link

Postscript link

PDF link

Parameters (Session):

par1 = 12 ;

Parameters (R input):

par1 = 12 ;

R code (references can be found in the software module):

par1 <- as.numeric(par1)
(n <- length(x))
(np <- floor(n / par1))
arr <- array(NA,dim=c(par1,np))
j <- 0
k <- 1
for (i in 1:(np*par1))
{
j = j + 1
arr[j,k] <- x[i]
if (j == par1) {
j = 0
k=k+1
}
}
arr
arr.mean <- array(NA,dim=np)
arr.sd <- array(NA,dim=np)
arr.range <- array(NA,dim=np)
for (j in 1:np)
{
arr.mean[j] <- mean(arr[,j],na.rm=TRUE)
arr.sd[j] <- sd(arr[,j],na.rm=TRUE)
arr.range[j] <- max(arr[,j],na.rm=TRUE) - min(arr[,j],na.rm=TRUE)
}
arr.mean
arr.sd
arr.range
(lm1 <- lm(arr.sd~arr.mean))
(lnlm1 <- lm(log(arr.sd)~log(arr.mean)))
(lm2 <- lm(arr.range~arr.mean))
bitmap(file='test1.png')
plot(arr.mean,arr.sd,main='Standard Deviation-Mean Plot',xlab='mean',ylab='standard deviation')
dev.off()
bitmap(file='test2.png')
plot(arr.mean,arr.range,main='Range-Mean Plot',xlab='mean',ylab='range')
dev.off()
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Standard Deviation-Mean Plot',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Section',header=TRUE)
a<-table.element(a,'Mean',header=TRUE)
a<-table.element(a,'Standard Deviation',header=TRUE)
a<-table.element(a,'Range',header=TRUE)
a<-table.row.end(a)
for (j in 1:np) {
a<-table.row.start(a)
a<-table.element(a,j,header=TRUE)
a<-table.element(a,arr.mean[j])
a<-table.element(a,arr.sd[j] )
a<-table.element(a,arr.range[j] )
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Regression: S.E.(k) = alpha + beta * Mean(k)',2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'alpha',header=TRUE)
a<-table.element(a,lm1$coefficients[[1]])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'beta',header=TRUE)
a<-table.element(a,lm1$coefficients[[2]])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'S.D.',header=TRUE)
a<-table.element(a,summary(lm1)$coefficients[2,2])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'T-STAT',header=TRUE)
a<-table.element(a,summary(lm1)$coefficients[2,3])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'p-value',header=TRUE)
a<-table.element(a,summary(lm1)$coefficients[2,4])
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable1.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'alpha',header=TRUE)
a<-table.element(a,lnlm1$coefficients[[1]])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'beta',header=TRUE)
a<-table.element(a,lnlm1$coefficients[[2]])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'S.D.',header=TRUE)
a<-table.element(a,summary(lnlm1)$coefficients[2,2])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'T-STAT',header=TRUE)
a<-table.element(a,summary(lnlm1)$coefficients[2,3])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'p-value',header=TRUE)
a<-table.element(a,summary(lnlm1)$coefficients[2,4])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Lambda',header=TRUE)
a<-table.element(a,1-lnlm1$coefficients[[2]])
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable2.tab')

Free Statistics

Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code