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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, 04 Dec 2011 17:44:03 -0500

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/Dec/04/t1323038651aopvwnxt84ucnyl.htm/, Retrieved Sun, 05 May 2024 18:41:27 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=150794, Retrieved Sun, 05 May 2024 18:41:27 +0000

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Estimated Impact

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-     [Univariate Data Series] [data set] [2008-12-01 19:54:57] [b98453cac15ba1066b407e146608df68]
- RMP   [Standard Deviation-Mean Plot] [Unemployment] [2010-11-29 10:34:47] [b98453cac15ba1066b407e146608df68]
- R  D      [Standard Deviation-Mean Plot] [] [2011-12-04 22:44:03] [c092f3a3bdd85c7279ddab6c8c6c9261] [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	0 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 & 0 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=150794&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]0 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=150794&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=150794&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	0 seconds
R Server	'Gwilym Jenkins' @ jenkins.wessa.net

Standard Deviation-Mean Plot
Section	Mean	Standard Deviation	Range
1	570.083333333333	21.6142138979016	70
2	541.083333333333	23.9714160591065	79
3	507.666666666667	23.41069426695	77
4	474.416666666667	24.5707081088376	82
5	469.75	28.1784088846891	82

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 570.083333333333 & 21.6142138979016 & 70 \tabularnewline
2 & 541.083333333333 & 23.9714160591065 & 79 \tabularnewline
3 & 507.666666666667 & 23.41069426695 & 77 \tabularnewline
4 & 474.416666666667 & 24.5707081088376 & 82 \tabularnewline
5 & 469.75 & 28.1784088846891 & 82 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=150794&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]570.083333333333[/C][C]21.6142138979016[/C][C]70[/C][/ROW]
[ROW][C]2[/C][C]541.083333333333[/C][C]23.9714160591065[/C][C]79[/C][/ROW]
[ROW][C]3[/C][C]507.666666666667[/C][C]23.41069426695[/C][C]77[/C][/ROW]
[ROW][C]4[/C][C]474.416666666667[/C][C]24.5707081088376[/C][C]82[/C][/ROW]
[ROW][C]5[/C][C]469.75[/C][C]28.1784088846891[/C][C]82[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=150794&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=150794&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	570.083333333333	21.6142138979016	70
2	541.083333333333	23.9714160591065	79
3	507.666666666667	23.41069426695	77
4	474.416666666667	24.5707081088376	82
5	469.75	28.1784088846891	82

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	47.5094139624741
beta	-0.0451820634392842
S.D.	0.0189863646754239
T-STAT	-2.37971113542174
p-value	0.0976432992831444

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 47.5094139624741 \tabularnewline
beta & -0.0451820634392842 \tabularnewline
S.D. & 0.0189863646754239 \tabularnewline
T-STAT & -2.37971113542174 \tabularnewline
p-value & 0.0976432992831444 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=150794&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]47.5094139624741[/C][/ROW]
[ROW][C]beta[/C][C]-0.0451820634392842[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0189863646754239[/C][/ROW]
[ROW][C]T-STAT[/C][C]-2.37971113542174[/C][/ROW]
[ROW][C]p-value[/C][C]0.0976432992831444[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=150794&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=150794&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	47.5094139624741
beta	-0.0451820634392842
S.D.	0.0189863646754239
T-STAT	-2.37971113542174
p-value	0.0976432992831444

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	9.14482117722121
beta	-0.955012094011864
S.D.	0.377027545506256
T-STAT	-2.53300350437132
p-value	0.0851996382770161
Lambda	1.95501209401186

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 9.14482117722121 \tabularnewline
beta & -0.955012094011864 \tabularnewline
S.D. & 0.377027545506256 \tabularnewline
T-STAT & -2.53300350437132 \tabularnewline
p-value & 0.0851996382770161 \tabularnewline
Lambda & 1.95501209401186 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=150794&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]9.14482117722121[/C][/ROW]
[ROW][C]beta[/C][C]-0.955012094011864[/C][/ROW]
[ROW][C]S.D.[/C][C]0.377027545506256[/C][/ROW]
[ROW][C]T-STAT[/C][C]-2.53300350437132[/C][/ROW]
[ROW][C]p-value[/C][C]0.0851996382770161[/C][/ROW]
[ROW][C]Lambda[/C][C]1.95501209401186[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=150794&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=150794&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	9.14482117722121
beta	-0.955012094011864
S.D.	0.377027545506256
T-STAT	-2.53300350437132
p-value	0.0851996382770161
Lambda	1.95501209401186

Figure 1

PNG link

Postscript link

PDF link

Figure 2

PNG link

Postscript link

PDF link

Parameters (Session):

par1 = 1 ; par2 = 0 ; par3 = 0 ; par4 = 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')

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Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code