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Author's title

Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationSun, 27 May 2012 11:07:52 -0400
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2012/May/27/t1338131714cik40lz5pf69fnv.htm/, Retrieved Wed, 08 May 2024 19:03:13 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=167719, Retrieved Wed, 08 May 2024 19:03:13 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact126
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Standard Deviation-Mean Plot] [] [2012-05-02 21:37:37] [e49862d1db32b11dcd040131c6263e24]
- R  D  [Standard Deviation-Mean Plot] [] [2012-05-27 15:00:48] [74be16979710d4c4e7c6647856088456]
-    D      [Standard Deviation-Mean Plot] [] [2012-05-27 15:07:52] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataseries X:
100,17
102,01
100,3
99,94
100,16
100,18
99,98
100,04
100,05
100,11
100,11
101,03
100,84
102,68
101,27
100,28
100,82
100,87
101,23
101,09
101,22
101,33
101,3
102,39
101,69
103,75
102,99
100,8
102,21
102,45
102,49
102,4
102,99
103,19
103,35
104,44
103,42
105,81
104,25
103,78
104,53
105,01
104,83
104,55
105,16
105,06
105,2
105,87
105,41
107,89
106,06
105,5
106,71
106,34
106,11
106,15
106,61
106,63
106,27
105,59
107,09
108,53
108,01
106,52
107,27
107,58
107,36
107,23
107,54
107,64
108,23
108,42




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=167719&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=167719&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=167719&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
1100.340.5971903914467862.07000000000001
2101.2766666666670.6612980806831012.40000000000001
3102.7291666666670.9542961074038083.64
4104.7891666666670.7353719940934462.45
5106.27250.6706187780360352.48
6107.6183333333330.5903594180024952.01000000000001

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 100.34 & 0.597190391446786 & 2.07000000000001 \tabularnewline
2 & 101.276666666667 & 0.661298080683101 & 2.40000000000001 \tabularnewline
3 & 102.729166666667 & 0.954296107403808 & 3.64 \tabularnewline
4 & 104.789166666667 & 0.735371994093446 & 2.45 \tabularnewline
5 & 106.2725 & 0.670618778036035 & 2.48 \tabularnewline
6 & 107.618333333333 & 0.590359418002495 & 2.01000000000001 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=167719&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]100.34[/C][C]0.597190391446786[/C][C]2.07000000000001[/C][/ROW]
[ROW][C]2[/C][C]101.276666666667[/C][C]0.661298080683101[/C][C]2.40000000000001[/C][/ROW]
[ROW][C]3[/C][C]102.729166666667[/C][C]0.954296107403808[/C][C]3.64[/C][/ROW]
[ROW][C]4[/C][C]104.789166666667[/C][C]0.735371994093446[/C][C]2.45[/C][/ROW]
[ROW][C]5[/C][C]106.2725[/C][C]0.670618778036035[/C][C]2.48[/C][/ROW]
[ROW][C]6[/C][C]107.618333333333[/C][C]0.590359418002495[/C][C]2.01000000000001[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=167719&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=167719&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
1100.340.5971903914467862.07000000000001
2101.2766666666670.6612980806831012.40000000000001
3102.7291666666670.9542961074038083.64
4104.7891666666670.7353719940934462.45
5106.27250.6706187780360352.48
6107.6183333333330.5903594180024952.01000000000001







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha1.39693171329283
beta-0.00669708266793321
S.D.0.023254852142545
T-STAT-0.287986465228081
p-value0.787662623183387

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 1.39693171329283 \tabularnewline
beta & -0.00669708266793321 \tabularnewline
S.D. & 0.023254852142545 \tabularnewline
T-STAT & -0.287986465228081 \tabularnewline
p-value & 0.787662623183387 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=167719&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]1.39693171329283[/C][/ROW]
[ROW][C]beta[/C][C]-0.00669708266793321[/C][/ROW]
[ROW][C]S.D.[/C][C]0.023254852142545[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.287986465228081[/C][/ROW]
[ROW][C]p-value[/C][C]0.787662623183387[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=167719&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=167719&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)
alpha1.39693171329283
beta-0.00669708266793321
S.D.0.023254852142545
T-STAT-0.287986465228081
p-value0.787662623183387







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha3.4335144204363
beta-0.818913726149894
S.D.3.18249782636153
T-STAT-0.257317921591839
p-value0.809628230489809
Lambda1.81891372614989

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 3.4335144204363 \tabularnewline
beta & -0.818913726149894 \tabularnewline
S.D. & 3.18249782636153 \tabularnewline
T-STAT & -0.257317921591839 \tabularnewline
p-value & 0.809628230489809 \tabularnewline
Lambda & 1.81891372614989 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=167719&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]3.4335144204363[/C][/ROW]
[ROW][C]beta[/C][C]-0.818913726149894[/C][/ROW]
[ROW][C]S.D.[/C][C]3.18249782636153[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.257317921591839[/C][/ROW]
[ROW][C]p-value[/C][C]0.809628230489809[/C][/ROW]
[ROW][C]Lambda[/C][C]1.81891372614989[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=167719&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=167719&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)
alpha3.4335144204363
beta-0.818913726149894
S.D.3.18249782636153
T-STAT-0.257317921591839
p-value0.809628230489809
Lambda1.81891372614989



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')