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Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationFri, 09 Dec 2011 06:06:30 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2011/Dec/09/t1323428805t7g5sxahdqvf5pe.htm/, Retrieved Thu, 02 May 2024 22:39:58 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=153254, Retrieved Thu, 02 May 2024 22:39:58 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact156
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [] [2010-10-06 14:13:06] [3d53bd477a917086cfdff0f854c5e476]
-   PD  [Univariate Data Series] [rozen] [2010-12-07 20:04:29] [b98453cac15ba1066b407e146608df68]
- RMPD    [(Partial) Autocorrelation Function] [Times Series - Rozen] [2011-12-09 10:44:11] [586787d3e7267c593af3e1f6b16aa21a]
- RMP       [Spectral Analysis] [Times Series] [2011-12-09 10:52:19] [586787d3e7267c593af3e1f6b16aa21a]
- RMP           [Standard Deviation-Mean Plot] [Times Series] [2011-12-09 11:06:30] [a0aae37dd27f4b65e222573f53b5a13b] [Current]
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Dataseries X:
1.35
1.91
1.31
1.19
1.3
1.14
1.1
1.02
1.11
1.18
1.24
1.36
1.29
1.73
1.41
1.15
1.31
1.15
1.08
1.1
1.14
1.24
1.33
1.49
1.38
1.96
1.36
1.24
1.35
1.23
1.09
1.08
1.33
1.35
1.38
1.5
1.47
2.09
1.52
1.29
1.52
1.27
1.35
1.29
1.41
1.39
1.45
1.53
1.45
2.11
1.53
1.38
1.54
1.35
1.29
1.33
1.47
1.47
1.54
1.59
1.5
2
1.51
1.4
1.62
1.44
1.29
1.28
1.4
1.39
1.46
1.49




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Herman Ole Andreas Wold' @ wold.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 & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=153254&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]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=153254&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=153254&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 Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Herman Ole Andreas Wold' @ wold.wessa.net







Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
11.26750.2287962571213250.89
21.2850.1892809359847760.65
31.354166666666670.2263729157158540.88
41.4650.2179032312330820.82
51.504166666666670.2128361868297830.82
61.481666666666670.1883822677108410.72

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 1.2675 & 0.228796257121325 & 0.89 \tabularnewline
2 & 1.285 & 0.189280935984776 & 0.65 \tabularnewline
3 & 1.35416666666667 & 0.226372915715854 & 0.88 \tabularnewline
4 & 1.465 & 0.217903231233082 & 0.82 \tabularnewline
5 & 1.50416666666667 & 0.212836186829783 & 0.82 \tabularnewline
6 & 1.48166666666667 & 0.188382267710841 & 0.72 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=153254&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]1.2675[/C][C]0.228796257121325[/C][C]0.89[/C][/ROW]
[ROW][C]2[/C][C]1.285[/C][C]0.189280935984776[/C][C]0.65[/C][/ROW]
[ROW][C]3[/C][C]1.35416666666667[/C][C]0.226372915715854[/C][C]0.88[/C][/ROW]
[ROW][C]4[/C][C]1.465[/C][C]0.217903231233082[/C][C]0.82[/C][/ROW]
[ROW][C]5[/C][C]1.50416666666667[/C][C]0.212836186829783[/C][C]0.82[/C][/ROW]
[ROW][C]6[/C][C]1.48166666666667[/C][C]0.188382267710841[/C][C]0.72[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=153254&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=153254&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
SectionMeanStandard DeviationRange
11.26750.2287962571213250.89
21.2850.1892809359847760.65
31.354166666666670.2263729157158540.88
41.4650.2179032312330820.82
51.504166666666670.2128361868297830.82
61.481666666666670.1883822677108410.72







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha0.256471281175055
beta-0.0329351950289766
S.D.0.0838390337464427
T-STAT-0.39283843762541
p-value0.714475122566237

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 0.256471281175055 \tabularnewline
beta & -0.0329351950289766 \tabularnewline
S.D. & 0.0838390337464427 \tabularnewline
T-STAT & -0.39283843762541 \tabularnewline
p-value & 0.714475122566237 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=153254&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]0.256471281175055[/C][/ROW]
[ROW][C]beta[/C][C]-0.0329351950289766[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0838390337464427[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.39283843762541[/C][/ROW]
[ROW][C]p-value[/C][C]0.714475122566237[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=153254&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=153254&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)
alpha0.256471281175055
beta-0.0329351950289766
S.D.0.0838390337464427
T-STAT-0.39283843762541
p-value0.714475122566237







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-1.49550748611395
beta-0.198653183010638
S.D.0.56260058430297
T-STAT-0.353098074465668
p-value0.741837288987506
Lambda1.19865318301064

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -1.49550748611395 \tabularnewline
beta & -0.198653183010638 \tabularnewline
S.D. & 0.56260058430297 \tabularnewline
T-STAT & -0.353098074465668 \tabularnewline
p-value & 0.741837288987506 \tabularnewline
Lambda & 1.19865318301064 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=153254&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-1.49550748611395[/C][/ROW]
[ROW][C]beta[/C][C]-0.198653183010638[/C][/ROW]
[ROW][C]S.D.[/C][C]0.56260058430297[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.353098074465668[/C][/ROW]
[ROW][C]p-value[/C][C]0.741837288987506[/C][/ROW]
[ROW][C]Lambda[/C][C]1.19865318301064[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=153254&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=153254&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-1.49550748611395
beta-0.198653183010638
S.D.0.56260058430297
T-STAT-0.353098074465668
p-value0.741837288987506
Lambda1.19865318301064



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')