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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 09:42:21 +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/t1292319674zhkwnjrr4ceprxg.htm/, Retrieved Thu, 02 May 2024 21:36:16 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=109325, Retrieved Thu, 02 May 2024 21:36:16 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

157

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]
- RMP         [Standard Deviation-Mean Plot] [Faillissementen V...] [2010-12-14 09:42:21] [8e16b01a5be2b3f7f3ad6418d9d6fd5b] [Current]

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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	2 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 & 2 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=109325&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]2 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=109325&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=109325&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	2 seconds
R Server	'Gwilym Jenkins' @ 72.249.127.135

Standard Deviation-Mean Plot
Section	Mean	Standard Deviation	Range
1	360.75	85.3539422320109	278
2	346.166666666667	77.645854930439	263
3	324.5	61.2290780593665	199
4	332.666666666667	62.8509540440113	207
5	356.083333333333	72.7879339817619	230
6	416.916666666667	92.7660383911476	333

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 360.75 & 85.3539422320109 & 278 \tabularnewline
2 & 346.166666666667 & 77.645854930439 & 263 \tabularnewline
3 & 324.5 & 61.2290780593665 & 199 \tabularnewline
4 & 332.666666666667 & 62.8509540440113 & 207 \tabularnewline
5 & 356.083333333333 & 72.7879339817619 & 230 \tabularnewline
6 & 416.916666666667 & 92.7660383911476 & 333 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=109325&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]360.75[/C][C]85.3539422320109[/C][C]278[/C][/ROW]
[ROW][C]2[/C][C]346.166666666667[/C][C]77.645854930439[/C][C]263[/C][/ROW]
[ROW][C]3[/C][C]324.5[/C][C]61.2290780593665[/C][C]199[/C][/ROW]
[ROW][C]4[/C][C]332.666666666667[/C][C]62.8509540440113[/C][C]207[/C][/ROW]
[ROW][C]5[/C][C]356.083333333333[/C][C]72.7879339817619[/C][C]230[/C][/ROW]
[ROW][C]6[/C][C]416.916666666667[/C][C]92.7660383911476[/C][C]333[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=109325&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=109325&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	360.75	85.3539422320109	278
2	346.166666666667	77.645854930439	263
3	324.5	61.2290780593665	199
4	332.666666666667	62.8509540440113	207
5	356.083333333333	72.7879339817619	230
6	416.916666666667	92.7660383911476	333

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	-45.4877605285805
beta	0.339509626739038
S.D.	0.084208647989754
T-STAT	4.03176674657391
p-value	0.0157105820923325

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -45.4877605285805 \tabularnewline
beta & 0.339509626739038 \tabularnewline
S.D. & 0.084208647989754 \tabularnewline
T-STAT & 4.03176674657391 \tabularnewline
p-value & 0.0157105820923325 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=109325&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-45.4877605285805[/C][/ROW]
[ROW][C]beta[/C][C]0.339509626739038[/C][/ROW]
[ROW][C]S.D.[/C][C]0.084208647989754[/C][/ROW]
[ROW][C]T-STAT[/C][C]4.03176674657391[/C][/ROW]
[ROW][C]p-value[/C][C]0.0157105820923325[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=109325&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=109325&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	-45.4877605285805
beta	0.339509626739038
S.D.	0.084208647989754
T-STAT	4.03176674657391
p-value	0.0157105820923325

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	-5.46421209015582
beta	1.66485823937865
S.D.	0.423516183589071
T-STAT	3.93103806629036
p-value	0.0170880761607991
Lambda	-0.664858239378654

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -5.46421209015582 \tabularnewline
beta & 1.66485823937865 \tabularnewline
S.D. & 0.423516183589071 \tabularnewline
T-STAT & 3.93103806629036 \tabularnewline
p-value & 0.0170880761607991 \tabularnewline
Lambda & -0.664858239378654 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=109325&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-5.46421209015582[/C][/ROW]
[ROW][C]beta[/C][C]1.66485823937865[/C][/ROW]
[ROW][C]S.D.[/C][C]0.423516183589071[/C][/ROW]
[ROW][C]T-STAT[/C][C]3.93103806629036[/C][/ROW]
[ROW][C]p-value[/C][C]0.0170880761607991[/C][/ROW]
[ROW][C]Lambda[/C][C]-0.664858239378654[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=109325&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=109325&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	-5.46421209015582
beta	1.66485823937865
S.D.	0.423516183589071
T-STAT	3.93103806629036
p-value	0.0170880761607991
Lambda	-0.664858239378654

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