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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 computationSun, 21 Dec 2008 08:14:27 -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/2008/Dec/21/t1229872534v62lqxsec33idrf.htm/, Retrieved Sun, 19 May 2024 12:18:36 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=35624, Retrieved Sun, 19 May 2024 12:18:36 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact154
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Standard Deviation-Mean Plot] [inv] [2008-12-05 14:59:18] [fad8a251ac01c156a8ae23a83577546f]
-   PD    [Standard Deviation-Mean Plot] [SDMP cons] [2008-12-21 15:14:27] [fa8b44cd657c07c6ee11bb2476ca3f8d] [Current]
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Dataseries X:
99,3
98,7
107,9
101,0
97,6
103,0
94,1
94,1
115,1
116,5
103,4
112,5
95,6
97,5
119,3
100,9
97,7
115,3
92,8
99,2
118,7
110,1
110,3
112,9
102,2
99,4
116,1
103,8
101,8
113,7
89,7
99,5
122,9
108,6
114,4
110,5
104,1
103,6
121,6
101,1
116,0
120,1
96,0
105,0
124,7
123,9
123,6
114,8
108,8
106,1
123,2
106,2
115,2
120,6
109,5
114,4
121,4
129,5
124,3
112,6




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'George Udny Yule' @ 72.249.76.132

\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 & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=35624&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]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=35624&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=35624&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'George Udny Yule' @ 72.249.76.132







Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
1103.67.7607403583093122.4
2105.8583333333339.5495319574343926.5
3106.8833333333339.1628532012620833.2
4112.87510.298554620563428.7
5115.9833333333337.7236158905167223.4

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 103.6 & 7.76074035830931 & 22.4 \tabularnewline
2 & 105.858333333333 & 9.54953195743439 & 26.5 \tabularnewline
3 & 106.883333333333 & 9.16285320126208 & 33.2 \tabularnewline
4 & 112.875 & 10.2985546205634 & 28.7 \tabularnewline
5 & 115.983333333333 & 7.72361589051672 & 23.4 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=35624&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]103.6[/C][C]7.76074035830931[/C][C]22.4[/C][/ROW]
[ROW][C]2[/C][C]105.858333333333[/C][C]9.54953195743439[/C][C]26.5[/C][/ROW]
[ROW][C]3[/C][C]106.883333333333[/C][C]9.16285320126208[/C][C]33.2[/C][/ROW]
[ROW][C]4[/C][C]112.875[/C][C]10.2985546205634[/C][C]28.7[/C][/ROW]
[ROW][C]5[/C][C]115.983333333333[/C][C]7.72361589051672[/C][C]23.4[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=35624&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=35624&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
1103.67.7607403583093122.4
2105.8583333333339.5495319574343926.5
3106.8833333333339.1628532012620833.2
4112.87510.298554620563428.7
5115.9833333333337.7236158905167223.4







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha8.12711262171035
beta0.00707948077684179
S.D.0.126167361191834
T-STAT0.0561118240879878
p-value0.95878073969421

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 8.12711262171035 \tabularnewline
beta & 0.00707948077684179 \tabularnewline
S.D. & 0.126167361191834 \tabularnewline
T-STAT & 0.0561118240879878 \tabularnewline
p-value & 0.95878073969421 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=35624&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]8.12711262171035[/C][/ROW]
[ROW][C]beta[/C][C]0.00707948077684179[/C][/ROW]
[ROW][C]S.D.[/C][C]0.126167361191834[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.0561118240879878[/C][/ROW]
[ROW][C]p-value[/C][C]0.95878073969421[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=35624&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=35624&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)
alpha8.12711262171035
beta0.00707948077684179
S.D.0.126167361191834
T-STAT0.0561118240879878
p-value0.95878073969421







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha1.85977574931770
beta0.0681388173425551
S.D.1.56904461203796
T-STAT0.0434269470860058
p-value0.968089996806885
Lambda0.931861182657445

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 1.85977574931770 \tabularnewline
beta & 0.0681388173425551 \tabularnewline
S.D. & 1.56904461203796 \tabularnewline
T-STAT & 0.0434269470860058 \tabularnewline
p-value & 0.968089996806885 \tabularnewline
Lambda & 0.931861182657445 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=35624&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]1.85977574931770[/C][/ROW]
[ROW][C]beta[/C][C]0.0681388173425551[/C][/ROW]
[ROW][C]S.D.[/C][C]1.56904461203796[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.0434269470860058[/C][/ROW]
[ROW][C]p-value[/C][C]0.968089996806885[/C][/ROW]
[ROW][C]Lambda[/C][C]0.931861182657445[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=35624&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=35624&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)
alpha1.85977574931770
beta0.0681388173425551
S.D.1.56904461203796
T-STAT0.0434269470860058
p-value0.968089996806885
Lambda0.931861182657445



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')