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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

Sun, 30 Nov 2008 15:58:55 -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/01/t1228086025k6afs664sd4q0qk.htm/, Retrieved Sun, 05 May 2024 13:44:24 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=26784, Retrieved Sun, 05 May 2024 13:44:24 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Lambda reeks2 Lambda reeks2 Lambda reeks2

Estimated Impact

255

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

F     [Law of Averages] [Random Walk Simul...] [2008-11-25 18:05:16] [b98453cac15ba1066b407e146608df68]
- RMPD  [Variance Reduction Matrix] [variance reductio...] [2008-11-30 19:32:42] [b635de6fc42b001d22cbe6e730fec936]
- RM        [Standard Deviation-Mean Plot] [Lambda reeks2 q8] [2008-11-30 22:58:55] [f4b2017b314c03698059f43b95818e67] [Current]

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Dataseries X:

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Histogram

Boxplots

9.5
9.1
9
9.3
9.9
9.8
9.4
8.3
8
8.5
10.4
11.1
10.9
9.9
9.2
9.2
9.5
9.6
9.5
9.1
8.9
9
10.1
10.3
10.2
9.6
9.2
9.3
9.4
9.4
9.2
9
9
9
9.8
10
9.9
9.3
9
9
9.1
9.1
9.1
9.2
8.8
8.3
8.4
8.1
7.8
7.9
7.9
8
7.9
7.5
7.2
6.9
6.6
6.7
7.3
7.5

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=26784&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=26784&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=26784&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	9.35833333333333	0.88055595386028	3.1
2	9.6	0.6	2
3	9.425	0.400283990096122	1.2
4	8.94166666666667	0.488891758485609	1.8
5	7.43333333333333	0.496044963748858	1.4

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 9.35833333333333 & 0.88055595386028 & 3.1 \tabularnewline
2 & 9.6 & 0.6 & 2 \tabularnewline
3 & 9.425 & 0.400283990096122 & 1.2 \tabularnewline
4 & 8.94166666666667 & 0.488891758485609 & 1.8 \tabularnewline
5 & 7.43333333333333 & 0.496044963748858 & 1.4 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=26784&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]9.35833333333333[/C][C]0.88055595386028[/C][C]3.1[/C][/ROW]
[ROW][C]2[/C][C]9.6[/C][C]0.6[/C][C]2[/C][/ROW]
[ROW][C]3[/C][C]9.425[/C][C]0.400283990096122[/C][C]1.2[/C][/ROW]
[ROW][C]4[/C][C]8.94166666666667[/C][C]0.488891758485609[/C][C]1.8[/C][/ROW]
[ROW][C]5[/C][C]7.43333333333333[/C][C]0.496044963748858[/C][C]1.4[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=26784&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=26784&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	9.35833333333333	0.88055595386028	3.1
2	9.6	0.6	2
3	9.425	0.400283990096122	1.2
4	8.94166666666667	0.488891758485609	1.8
5	7.43333333333333	0.496044963748858	1.4

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	0.0601979731946947
beta	0.0573030005634124
S.D.	0.116993501862069
T-STAT	0.489796438702815
p-value	0.657859077122676

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 0.0601979731946947 \tabularnewline
beta & 0.0573030005634124 \tabularnewline
S.D. & 0.116993501862069 \tabularnewline
T-STAT & 0.489796438702815 \tabularnewline
p-value & 0.657859077122676 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=26784&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]0.0601979731946947[/C][/ROW]
[ROW][C]beta[/C][C]0.0573030005634124[/C][/ROW]
[ROW][C]S.D.[/C][C]0.116993501862069[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.489796438702815[/C][/ROW]
[ROW][C]p-value[/C][C]0.657859077122676[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=26784&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=26784&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	0.0601979731946947
beta	0.0573030005634124
S.D.	0.116993501862069
T-STAT	0.489796438702815
p-value	0.657859077122676

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	-2.08759607159602
beta	0.682721333307735
S.D.	1.59110892315731
T-STAT	0.429085226895076
p-value	0.69680901282602
Lambda	0.317278666692265

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -2.08759607159602 \tabularnewline
beta & 0.682721333307735 \tabularnewline
S.D. & 1.59110892315731 \tabularnewline
T-STAT & 0.429085226895076 \tabularnewline
p-value & 0.69680901282602 \tabularnewline
Lambda & 0.317278666692265 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=26784&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-2.08759607159602[/C][/ROW]
[ROW][C]beta[/C][C]0.682721333307735[/C][/ROW]
[ROW][C]S.D.[/C][C]1.59110892315731[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.429085226895076[/C][/ROW]
[ROW][C]p-value[/C][C]0.69680901282602[/C][/ROW]
[ROW][C]Lambda[/C][C]0.317278666692265[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=26784&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=26784&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	-2.08759607159602
beta	0.682721333307735
S.D.	1.59110892315731
T-STAT	0.429085226895076
p-value	0.69680901282602
Lambda	0.317278666692265

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