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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

Mon, 28 Dec 2009 10:28:28 -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/2009/Dec/28/t1262021448n09txshhr82ig95.htm/, Retrieved Sun, 05 May 2024 06:25:51 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=71022, Retrieved Sun, 05 May 2024 06:25:51 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

102

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

-       [Standard Deviation-Mean Plot] [Paper(14) - Heter...] [2009-12-28 17:28:28] [a53416c107f5e7e1e12bb9940270d09d] [Current]

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Dataseries X:

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Histogram

Boxplots

2,3
2,3
2,6
3,1
2,8
2,5
2,9
3,1
3,1
3,2
2,5
2,6
2,9
2,6
2,4
1,7
2
2,2
1,9
1,6
1,6
1,2
1,2
1,5
1,6
1,7
1,8
1,8
1,8
1,3
1,3
1,4
1,1
1,5
2,2
2,9
3,1
3,5
3,6
4,4
4,2
5,2
5,8
5,9
5,4
5,5
4,7
3,1
2,6
2,3
1,9
0,6
0,6
-0,4
-1,1
-1,7
-0,8
-1,2
-1
-0,1

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=71022&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=71022&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=71022&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	2.75	0.326134383902765	0.9
2	1.9	0.539359889970594	1.7
3	1.7	0.480530010414637	1.8
4	4.53333333333333	1.03601801786134	2.8
5	0.141666666666667	1.4612935324153	4.3

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 2.75 & 0.326134383902765 & 0.9 \tabularnewline
2 & 1.9 & 0.539359889970594 & 1.7 \tabularnewline
3 & 1.7 & 0.480530010414637 & 1.8 \tabularnewline
4 & 4.53333333333333 & 1.03601801786134 & 2.8 \tabularnewline
5 & 0.141666666666667 & 1.4612935324153 & 4.3 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=71022&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]2.75[/C][C]0.326134383902765[/C][C]0.9[/C][/ROW]
[ROW][C]2[/C][C]1.9[/C][C]0.539359889970594[/C][C]1.7[/C][/ROW]
[ROW][C]3[/C][C]1.7[/C][C]0.480530010414637[/C][C]1.8[/C][/ROW]
[ROW][C]4[/C][C]4.53333333333333[/C][C]1.03601801786134[/C][C]2.8[/C][/ROW]
[ROW][C]5[/C][C]0.141666666666667[/C][C]1.4612935324153[/C][C]4.3[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=71022&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=71022&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	2.75	0.326134383902765	0.9
2	1.9	0.539359889970594	1.7
3	1.7	0.480530010414637	1.8
4	4.53333333333333	1.03601801786134	2.8
5	0.141666666666667	1.4612935324153	4.3

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	0.946452316029483
beta	-0.0806281855403883
S.D.	0.162272952602097
T-STAT	-0.496867680334218
p-value	0.653411819092139

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 0.946452316029483 \tabularnewline
beta & -0.0806281855403883 \tabularnewline
S.D. & 0.162272952602097 \tabularnewline
T-STAT & -0.496867680334218 \tabularnewline
p-value & 0.653411819092139 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=71022&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]0.946452316029483[/C][/ROW]
[ROW][C]beta[/C][C]-0.0806281855403883[/C][/ROW]
[ROW][C]S.D.[/C][C]0.162272952602097[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.496867680334218[/C][/ROW]
[ROW][C]p-value[/C][C]0.653411819092139[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=71022&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=71022&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	0.946452316029483
beta	-0.0806281855403883
S.D.	0.162272952602097
T-STAT	-0.496867680334218
p-value	0.653411819092139

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	-0.319939355969644
beta	-0.262039950956688
S.D.	0.212577097778472
T-STAT	-1.23268194784445
p-value	0.305486039069502
Lambda	1.26203995095669

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -0.319939355969644 \tabularnewline
beta & -0.262039950956688 \tabularnewline
S.D. & 0.212577097778472 \tabularnewline
T-STAT & -1.23268194784445 \tabularnewline
p-value & 0.305486039069502 \tabularnewline
Lambda & 1.26203995095669 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=71022&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-0.319939355969644[/C][/ROW]
[ROW][C]beta[/C][C]-0.262039950956688[/C][/ROW]
[ROW][C]S.D.[/C][C]0.212577097778472[/C][/ROW]
[ROW][C]T-STAT[/C][C]-1.23268194784445[/C][/ROW]
[ROW][C]p-value[/C][C]0.305486039069502[/C][/ROW]
[ROW][C]Lambda[/C][C]1.26203995095669[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=71022&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=71022&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	-0.319939355969644
beta	-0.262039950956688
S.D.	0.212577097778472
T-STAT	-1.23268194784445
p-value	0.305486039069502
Lambda	1.26203995095669

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