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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, 16 Dec 2008 11:45:42 -0700

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/2008/Dec/16/t1229453185iv234uutj4n0zb1.htm/, Retrieved Wed, 15 May 2024 13:51:48 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=34099, Retrieved Wed, 15 May 2024 13:51:48 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

180

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

-       [Standard Deviation-Mean Plot] [Paper SDM ] [2008-12-16 18:45:42] [c5d6d05aee6be5527ac4a30a8c3b8fe5] [Current]
- RMP     [Spectral Analysis] [Paper spectraal a...] [2008-12-16 18:52:51] [7849b5cbaea5f05923be73656f726e58] 
- RMP     [Spectral Analysis] [paper Spectraal a...] [2008-12-16 18:55:02] [7849b5cbaea5f05923be73656f726e58] 
-   P       [Spectral Analysis] [Spectraal 1 0] [2008-12-24 14:30:31] [7849b5cbaea5f05923be73656f726e58] 
- RMP     [ARIMA Backward Selection] [Paper Backward] [2008-12-16 18:59:29] [7849b5cbaea5f05923be73656f726e58] 
-   P       [ARIMA Backward Selection] [Paper backward ok] [2008-12-24 13:51:37] [7849b5cbaea5f05923be73656f726e58] 
F RMP     [ARIMA Forecasting] [paper armina fore...] [2008-12-16 19:04:44] [7849b5cbaea5f05923be73656f726e58] 
-   PD      [ARIMA Forecasting] [Paper Armina fore...] [2008-12-24 14:03:19] [7849b5cbaea5f05923be73656f726e58] 

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Dataseries X:

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Histogram

Boxplots

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	3 seconds
R Server	'Herman Ole Andreas Wold' @ 193.190.124.10:1001

\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 & 3 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ 193.190.124.10:1001 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=34099&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]3 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ 193.190.124.10:1001[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=34099&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=34099&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	3 seconds
R Server	'Herman Ole Andreas Wold' @ 193.190.124.10:1001

Standard Deviation-Mean Plot
Section	Mean	Standard Deviation	Range
1	102.16	0.72362722698663	1.59999999999999
2	105.475	1.13066754216661	2.5
3	107.88	0.95880607575729	2.12000000000000

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 102.16 & 0.72362722698663 & 1.59999999999999 \tabularnewline
2 & 105.475 & 1.13066754216661 & 2.5 \tabularnewline
3 & 107.88 & 0.95880607575729 & 2.12000000000000 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=34099&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]102.16[/C][C]0.72362722698663[/C][C]1.59999999999999[/C][/ROW]
[ROW][C]2[/C][C]105.475[/C][C]1.13066754216661[/C][C]2.5[/C][/ROW]
[ROW][C]3[/C][C]107.88[/C][C]0.95880607575729[/C][C]2.12000000000000[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=34099&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=34099&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	102.16	0.72362722698663	1.59999999999999
2	105.475	1.13066754216661	2.5
3	107.88	0.95880607575729	2.12000000000000

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	-3.91001179610951
beta	0.0460933275224286
S.D.	0.054197934254683
T-STAT	0.850462811106973
p-value	0.551334137623024

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -3.91001179610951 \tabularnewline
beta & 0.0460933275224286 \tabularnewline
S.D. & 0.054197934254683 \tabularnewline
T-STAT & 0.850462811106973 \tabularnewline
p-value & 0.551334137623024 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=34099&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-3.91001179610951[/C][/ROW]
[ROW][C]beta[/C][C]0.0460933275224286[/C][/ROW]
[ROW][C]S.D.[/C][C]0.054197934254683[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.850462811106973[/C][/ROW]
[ROW][C]p-value[/C][C]0.551334137623024[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=34099&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=34099&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	-3.91001179610951
beta	0.0460933275224286
S.D.	0.054197934254683
T-STAT	0.850462811106973
p-value	0.551334137623024

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	-26.862859439069
beta	5.75294626177196
S.D.	5.90447893951324
T-STAT	0.974335977942575
p-value	0.508274834647014
Lambda	-4.75294626177196

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -26.862859439069 \tabularnewline
beta & 5.75294626177196 \tabularnewline
S.D. & 5.90447893951324 \tabularnewline
T-STAT & 0.974335977942575 \tabularnewline
p-value & 0.508274834647014 \tabularnewline
Lambda & -4.75294626177196 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=34099&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-26.862859439069[/C][/ROW]
[ROW][C]beta[/C][C]5.75294626177196[/C][/ROW]
[ROW][C]S.D.[/C][C]5.90447893951324[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.974335977942575[/C][/ROW]
[ROW][C]p-value[/C][C]0.508274834647014[/C][/ROW]
[ROW][C]Lambda[/C][C]-4.75294626177196[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=34099&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=34099&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	-26.862859439069
beta	5.75294626177196
S.D.	5.90447893951324
T-STAT	0.974335977942575
p-value	0.508274834647014
Lambda	-4.75294626177196

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