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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 computationThu, 17 Dec 2009 10:46:22 -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/17/t1261072043vz7vxw1fbmjzobe.htm/, Retrieved Tue, 30 Apr 2024 07:38:39 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=69015, Retrieved Tue, 30 Apr 2024 07:38:39 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact102
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       [Standard Deviation-Mean Plot] [Identifying Integ...] [2009-11-22 12:50:05] [b98453cac15ba1066b407e146608df68]
-    D        [Standard Deviation-Mean Plot] [Standard deviatio...] [2009-11-25 14:27:00] [4395c69e961f9a13a0559fd2f0a72538]
-    D            [Standard Deviation-Mean Plot] [Paper SMP ] [2009-12-17 17:46:22] [d1081bd6cdf1fed9ed45c42dbd523bf1] [Current]
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Dataseries X:
7.6
8.3
8.4
8.4
8.4
8.4
8.6
8.9
8.8
8.3
7.5
7.2
7.4
8.8
9.3
9.3
8.7
8.2
8.3
8.5
8.6
8.5
8.2
8.1
7.9
8.6
8.7
8.7
8.5
8.4
8.5
8.7
8.7
8.6
8.5
8.3
8
8.2
8.1
8.1
8
7.9
7.9
8
8
7.9
8
7.7
7.2
7.5
7.3
7
7
7
7.2
7.3
7.1
6.8
6.4
6.1
6.5
7.7
7.9
7.5
6.9
6.6
6.9
7.7
8
8
7.7
7.3
7.4




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 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 & 2 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=69015&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]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=69015&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=69015&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 time2 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
18.233333333333330.5245488682206031.7
28.491666666666670.5230302152463151.9
38.508333333333330.2314316444667970.799999999999999
47.983333333333330.1267304464625840.499999999999999
56.991666666666670.396480730549381.4
67.391666666666670.5401318581998511.5

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 8.23333333333333 & 0.524548868220603 & 1.7 \tabularnewline
2 & 8.49166666666667 & 0.523030215246315 & 1.9 \tabularnewline
3 & 8.50833333333333 & 0.231431644466797 & 0.799999999999999 \tabularnewline
4 & 7.98333333333333 & 0.126730446462584 & 0.499999999999999 \tabularnewline
5 & 6.99166666666667 & 0.39648073054938 & 1.4 \tabularnewline
6 & 7.39166666666667 & 0.540131858199851 & 1.5 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=69015&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]8.23333333333333[/C][C]0.524548868220603[/C][C]1.7[/C][/ROW]
[ROW][C]2[/C][C]8.49166666666667[/C][C]0.523030215246315[/C][C]1.9[/C][/ROW]
[ROW][C]3[/C][C]8.50833333333333[/C][C]0.231431644466797[/C][C]0.799999999999999[/C][/ROW]
[ROW][C]4[/C][C]7.98333333333333[/C][C]0.126730446462584[/C][C]0.499999999999999[/C][/ROW]
[ROW][C]5[/C][C]6.99166666666667[/C][C]0.39648073054938[/C][C]1.4[/C][/ROW]
[ROW][C]6[/C][C]7.39166666666667[/C][C]0.540131858199851[/C][C]1.5[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=69015&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=69015&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
18.233333333333330.5245488682206031.7
28.491666666666670.5230302152463151.9
38.508333333333330.2314316444667970.799999999999999
47.983333333333330.1267304464625840.499999999999999
56.991666666666670.396480730549381.4
67.391666666666670.5401318581998511.5







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha0.709898611747424
beta-0.0402739056163659
S.D.0.139810465996463
T-STAT-0.288060735148289
p-value0.78760970718122

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 0.709898611747424 \tabularnewline
beta & -0.0402739056163659 \tabularnewline
S.D. & 0.139810465996463 \tabularnewline
T-STAT & -0.288060735148289 \tabularnewline
p-value & 0.78760970718122 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=69015&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]0.709898611747424[/C][/ROW]
[ROW][C]beta[/C][C]-0.0402739056163659[/C][/ROW]
[ROW][C]S.D.[/C][C]0.139810465996463[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.288060735148289[/C][/ROW]
[ROW][C]p-value[/C][C]0.78760970718122[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=69015&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=69015&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)
alpha0.709898611747424
beta-0.0402739056163659
S.D.0.139810465996463
T-STAT-0.288060735148289
p-value0.78760970718122







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha1.50975883743483
beta-1.24264194520357
S.D.3.63276388236312
T-STAT-0.342065156295054
p-value0.749518722091502
Lambda2.24264194520357

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 1.50975883743483 \tabularnewline
beta & -1.24264194520357 \tabularnewline
S.D. & 3.63276388236312 \tabularnewline
T-STAT & -0.342065156295054 \tabularnewline
p-value & 0.749518722091502 \tabularnewline
Lambda & 2.24264194520357 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=69015&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]1.50975883743483[/C][/ROW]
[ROW][C]beta[/C][C]-1.24264194520357[/C][/ROW]
[ROW][C]S.D.[/C][C]3.63276388236312[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.342065156295054[/C][/ROW]
[ROW][C]p-value[/C][C]0.749518722091502[/C][/ROW]
[ROW][C]Lambda[/C][C]2.24264194520357[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=69015&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=69015&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)
alpha1.50975883743483
beta-1.24264194520357
S.D.3.63276388236312
T-STAT-0.342065156295054
p-value0.749518722091502
Lambda2.24264194520357



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')