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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

Mon, 15 Aug 2011 12:44:46 -0400

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/2011/Aug/15/t1313426867sqyepn9hozf90db.htm/, Retrieved Tue, 14 May 2024 07:20:54 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=123799, Retrieved Tue, 14 May 2024 07:20:54 +0000

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No (this computation is public)

User-defined keywords

Berns Sophie

Estimated Impact

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

-       [Standard Deviation-Mean Plot] [Tijdreeks B - Sta...] [2011-08-15 16:44:46] [adf65953347764930908a56f01d4e8ba] [Current]

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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' @ jenkins.wessa.net

\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' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=123799&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' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=123799&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=123799&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' @ jenkins.wessa.net

Standard Deviation-Mean Plot
Section	Mean	Standard Deviation	Range
1	863.333333333333	55.6504240502235	170
2	861.666666666667	86.4274086716533	310
3	850	84.7456086285194	280
4	849.166666666667	76.5694376881454	220
5	842.5	71.239034243875	230
6	829.166666666667	86.9125300447978	340
7	825.833333333333	79.1383521933505	270
8	828.333333333333	80.4344265205948	250
9	826.666666666667	102.720568298249	340

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 863.333333333333 & 55.6504240502235 & 170 \tabularnewline
2 & 861.666666666667 & 86.4274086716533 & 310 \tabularnewline
3 & 850 & 84.7456086285194 & 280 \tabularnewline
4 & 849.166666666667 & 76.5694376881454 & 220 \tabularnewline
5 & 842.5 & 71.239034243875 & 230 \tabularnewline
6 & 829.166666666667 & 86.9125300447978 & 340 \tabularnewline
7 & 825.833333333333 & 79.1383521933505 & 270 \tabularnewline
8 & 828.333333333333 & 80.4344265205948 & 250 \tabularnewline
9 & 826.666666666667 & 102.720568298249 & 340 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=123799&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]863.333333333333[/C][C]55.6504240502235[/C][C]170[/C][/ROW]
[ROW][C]2[/C][C]861.666666666667[/C][C]86.4274086716533[/C][C]310[/C][/ROW]
[ROW][C]3[/C][C]850[/C][C]84.7456086285194[/C][C]280[/C][/ROW]
[ROW][C]4[/C][C]849.166666666667[/C][C]76.5694376881454[/C][C]220[/C][/ROW]
[ROW][C]5[/C][C]842.5[/C][C]71.239034243875[/C][C]230[/C][/ROW]
[ROW][C]6[/C][C]829.166666666667[/C][C]86.9125300447978[/C][C]340[/C][/ROW]
[ROW][C]7[/C][C]825.833333333333[/C][C]79.1383521933505[/C][C]270[/C][/ROW]
[ROW][C]8[/C][C]828.333333333333[/C][C]80.4344265205948[/C][C]250[/C][/ROW]
[ROW][C]9[/C][C]826.666666666667[/C][C]102.720568298249[/C][C]340[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=123799&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=123799&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	863.333333333333	55.6504240502235	170
2	861.666666666667	86.4274086716533	310
3	850	84.7456086285194	280
4	849.166666666667	76.5694376881454	220
5	842.5	71.239034243875	230
6	829.166666666667	86.9125300447978	340
7	825.833333333333	79.1383521933505	270
8	828.333333333333	80.4344265205948	250
9	826.666666666667	102.720568298249	340

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	459.364024076604
beta	-0.450123857415314
S.D.	0.273143876965764
T-STAT	-1.64793683979134
p-value	0.14335661277268

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 459.364024076604 \tabularnewline
beta & -0.450123857415314 \tabularnewline
S.D. & 0.273143876965764 \tabularnewline
T-STAT & -1.64793683979134 \tabularnewline
p-value & 0.14335661277268 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=123799&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]459.364024076604[/C][/ROW]
[ROW][C]beta[/C][C]-0.450123857415314[/C][/ROW]
[ROW][C]S.D.[/C][C]0.273143876965764[/C][/ROW]
[ROW][C]T-STAT[/C][C]-1.64793683979134[/C][/ROW]
[ROW][C]p-value[/C][C]0.14335661277268[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=123799&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=123799&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	459.364024076604
beta	-0.450123857415314
S.D.	0.273143876965764
T-STAT	-1.64793683979134
p-value	0.14335661277268

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	38.7734350158236
beta	-5.10701635515207
S.D.	2.99511661696236
T-STAT	-1.7051143605659
p-value	0.131944086656216
Lambda	6.10701635515207

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 38.7734350158236 \tabularnewline
beta & -5.10701635515207 \tabularnewline
S.D. & 2.99511661696236 \tabularnewline
T-STAT & -1.7051143605659 \tabularnewline
p-value & 0.131944086656216 \tabularnewline
Lambda & 6.10701635515207 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=123799&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]38.7734350158236[/C][/ROW]
[ROW][C]beta[/C][C]-5.10701635515207[/C][/ROW]
[ROW][C]S.D.[/C][C]2.99511661696236[/C][/ROW]
[ROW][C]T-STAT[/C][C]-1.7051143605659[/C][/ROW]
[ROW][C]p-value[/C][C]0.131944086656216[/C][/ROW]
[ROW][C]Lambda[/C][C]6.10701635515207[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=123799&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=123799&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	38.7734350158236
beta	-5.10701635515207
S.D.	2.99511661696236
T-STAT	-1.7051143605659
p-value	0.131944086656216
Lambda	6.10701635515207

Figure 1

PNG link

Postscript link

PDF link

Figure 2

PNG link

Postscript link

PDF link

Parameters (Session):

par1 = 48 ; par2 = 1 ; par3 = 0 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;

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