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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, 11 Dec 2009 07:42:09 -0700
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2009/Dec/11/t126054261706q2r4imztv2kut.htm/, Retrieved Sun, 28 Apr 2024 21:36:56 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=66263, Retrieved Sun, 28 Apr 2024 21:36:56 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact128
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Explorative Data Analysis] [Run Sequence gebo...] [2008-12-12 13:32:37] [76963dc1903f0f612b6153510a3818cf]
- R  D  [Univariate Explorative Data Analysis] [Run Sequence gebo...] [2008-12-17 12:14:40] [76963dc1903f0f612b6153510a3818cf]
-         [Univariate Explorative Data Analysis] [Run Sequence Plot...] [2008-12-22 18:19:51] [1ce0d16c8f4225c977b42c8fa93bc163]
- RMP       [(Partial) Autocorrelation Function] [Identifying Integ...] [2009-11-22 12:16:10] [b98453cac15ba1066b407e146608df68]
-   PD        [(Partial) Autocorrelation Function] [WS8 d=1 D=1] [2009-11-25 16:19:15] [445b292c553470d9fed8bc2796fd3a00]
F   P           [(Partial) Autocorrelation Function] [WS8 autocorrelati...] [2009-12-02 16:14:44] [445b292c553470d9fed8bc2796fd3a00]
- RMP               [Standard Deviation-Mean Plot] [ws 9: Review 3] [2009-12-11 14:42:09] [17b3de9cda9f51722106e41c76160a49] [Current]
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Dataseries X:
7.55
7.55
7.59
7.59
7.59
7.57
7.57
7.59
7.6
7.64
7.64
7.76
7.76
7.76
7.77
7.83
7.94
7.94
7.94
8.09
8.18
8.26
8.28
8.28
8.28
8.29
8.3
8.3
8.31
8.33
8.33
8.34
8.48
8.59
8.67
8.67
8.67
8.71
8.72
8.72
8.72
8.74
8.74
8.74
8.74
8.79
8.85
8.86
8.87
8.92
8.96
8.97
8.99
8.98
8.98
9.01
9.01
9.03
9.05
9.05




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 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=66263&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=66263&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=66263&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'Gwilym Jenkins' @ 72.249.127.135







Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
17.603333333333330.05710171679210750.21
28.00250.2072821967533850.52
38.40750.1524422394339450.390000000000001
48.750.05624621199366520.190000000000000
58.9850.05231026320296680.180000000000001

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 7.60333333333333 & 0.0571017167921075 & 0.21 \tabularnewline
2 & 8.0025 & 0.207282196753385 & 0.52 \tabularnewline
3 & 8.4075 & 0.152442239433945 & 0.390000000000001 \tabularnewline
4 & 8.75 & 0.0562462119936652 & 0.190000000000000 \tabularnewline
5 & 8.985 & 0.0523102632029668 & 0.180000000000001 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=66263&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]7.60333333333333[/C][C]0.0571017167921075[/C][C]0.21[/C][/ROW]
[ROW][C]2[/C][C]8.0025[/C][C]0.207282196753385[/C][C]0.52[/C][/ROW]
[ROW][C]3[/C][C]8.4075[/C][C]0.152442239433945[/C][C]0.390000000000001[/C][/ROW]
[ROW][C]4[/C][C]8.75[/C][C]0.0562462119936652[/C][C]0.190000000000000[/C][/ROW]
[ROW][C]5[/C][C]8.985[/C][C]0.0523102632029668[/C][C]0.180000000000001[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=66263&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=66263&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
17.603333333333330.05710171679210750.21
28.00250.2072821967533850.52
38.40750.1524422394339450.390000000000001
48.750.05624621199366520.190000000000000
58.9850.05231026320296680.180000000000001







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha0.440529024228166
beta-0.0401755557419001
S.D.0.0697164214408109
T-STAT-0.576271055105849
p-value0.604824145829302

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 0.440529024228166 \tabularnewline
beta & -0.0401755557419001 \tabularnewline
S.D. & 0.0697164214408109 \tabularnewline
T-STAT & -0.576271055105849 \tabularnewline
p-value & 0.604824145829302 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=66263&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]0.440529024228166[/C][/ROW]
[ROW][C]beta[/C][C]-0.0401755557419001[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0697164214408109[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.576271055105849[/C][/ROW]
[ROW][C]p-value[/C][C]0.604824145829302[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=66263&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=66263&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)
alpha0.440529024228166
beta-0.0401755557419001
S.D.0.0697164214408109
T-STAT-0.576271055105849
p-value0.604824145829302







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha3.54339313684672
beta-2.81672308074071
S.D.5.33135852422723
T-STAT-0.528331206378394
p-value0.633858600062179
Lambda3.81672308074071

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 3.54339313684672 \tabularnewline
beta & -2.81672308074071 \tabularnewline
S.D. & 5.33135852422723 \tabularnewline
T-STAT & -0.528331206378394 \tabularnewline
p-value & 0.633858600062179 \tabularnewline
Lambda & 3.81672308074071 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=66263&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]3.54339313684672[/C][/ROW]
[ROW][C]beta[/C][C]-2.81672308074071[/C][/ROW]
[ROW][C]S.D.[/C][C]5.33135852422723[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.528331206378394[/C][/ROW]
[ROW][C]p-value[/C][C]0.633858600062179[/C][/ROW]
[ROW][C]Lambda[/C][C]3.81672308074071[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=66263&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=66263&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)
alpha3.54339313684672
beta-2.81672308074071
S.D.5.33135852422723
T-STAT-0.528331206378394
p-value0.633858600062179
Lambda3.81672308074071



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')