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Author's title

Author

*Unverified author*

R Software Module

rwasp_smp.wasp

Title produced by software

Standard Deviation-Mean Plot

Date of computation

Wed, 16 Jan 2008 08:49:26 -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/Jan/16/t1200498462kl5viq6cr3j28qv.htm/, Retrieved Wed, 15 May 2024 21:08:17 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=7992, Retrieved Wed, 15 May 2024 21:08:17 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

301

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

-     [Hierarchical Clustering] [paper] [2007-12-05 22:51:14] [8d3192ea84fef628e5e980e3df2ac42d]
- RMPD    [Standard Deviation-Mean Plot] [] [2008-01-16 15:49:26] [d41d8cd98f00b204e9800998ecf8427e] [Current]

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Boxplots

Summary of compuational 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 compuational 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=7992&T=0

[TABLE]
[ROW][C]Summary of compuational 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=7992&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=7992&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 compuational 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	309.75	14.3281350686492	52
2	362.916666666667	21.6646269436162	79
3	408.583333333333	17.3857744007896	58
4	444.416666666667	27.7765706808432	89
5	603.583333333333	38.2300651161867	126

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 309.75 & 14.3281350686492 & 52 \tabularnewline
2 & 362.916666666667 & 21.6646269436162 & 79 \tabularnewline
3 & 408.583333333333 & 17.3857744007896 & 58 \tabularnewline
4 & 444.416666666667 & 27.7765706808432 & 89 \tabularnewline
5 & 603.583333333333 & 38.2300651161867 & 126 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=7992&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]309.75[/C][C]14.3281350686492[/C][C]52[/C][/ROW]
[ROW][C]2[/C][C]362.916666666667[/C][C]21.6646269436162[/C][C]79[/C][/ROW]
[ROW][C]3[/C][C]408.583333333333[/C][C]17.3857744007896[/C][C]58[/C][/ROW]
[ROW][C]4[/C][C]444.416666666667[/C][C]27.7765706808432[/C][C]89[/C][/ROW]
[ROW][C]5[/C][C]603.583333333333[/C][C]38.2300651161867[/C][C]126[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=7992&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=7992&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	309.75	14.3281350686492	52
2	362.916666666667	21.6646269436162	79
3	408.583333333333	17.3857744007896	58
4	444.416666666667	27.7765706808432	89
5	603.583333333333	38.2300651161867	126

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	-10.2733744731359
beta	0.0801935162971772
S.D.	0.0163815647430678
T-STAT	4.89535142429619
p-value	0.0163095728639274

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -10.2733744731359 \tabularnewline
beta & 0.0801935162971772 \tabularnewline
S.D. & 0.0163815647430678 \tabularnewline
T-STAT & 4.89535142429619 \tabularnewline
p-value & 0.0163095728639274 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=7992&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-10.2733744731359[/C][/ROW]
[ROW][C]beta[/C][C]0.0801935162971772[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0163815647430678[/C][/ROW]
[ROW][C]T-STAT[/C][C]4.89535142429619[/C][/ROW]
[ROW][C]p-value[/C][C]0.0163095728639274[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=7992&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=7992&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	-10.2733744731359
beta	0.0801935162971772
S.D.	0.0163815647430678
T-STAT	4.89535142429619
p-value	0.0163095728639274

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	-5.46751650823859
beta	1.42321529836292
S.D.	0.352982970292174
T-STAT	4.03196589678217
p-value	0.0274304264396786
Lambda	-0.42321529836292

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -5.46751650823859 \tabularnewline
beta & 1.42321529836292 \tabularnewline
S.D. & 0.352982970292174 \tabularnewline
T-STAT & 4.03196589678217 \tabularnewline
p-value & 0.0274304264396786 \tabularnewline
Lambda & -0.42321529836292 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=7992&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-5.46751650823859[/C][/ROW]
[ROW][C]beta[/C][C]1.42321529836292[/C][/ROW]
[ROW][C]S.D.[/C][C]0.352982970292174[/C][/ROW]
[ROW][C]T-STAT[/C][C]4.03196589678217[/C][/ROW]
[ROW][C]p-value[/C][C]0.0274304264396786[/C][/ROW]
[ROW][C]Lambda[/C][C]-0.42321529836292[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=7992&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=7992&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	-5.46751650823859
beta	1.42321529836292
S.D.	0.352982970292174
T-STAT	4.03196589678217
p-value	0.0274304264396786
Lambda	-0.42321529836292

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