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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, 07 Dec 2008 10:52:46 -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/07/t1228672414vs56w7kmddhf2k9.htm/, Retrieved Sun, 19 May 2024 12:40:09 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=30196, Retrieved Sun, 19 May 2024 12:40:09 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact134
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [data set] [2008-12-01 19:54:57] [b98453cac15ba1066b407e146608df68]
- RMPD    [Standard Deviation-Mean Plot] [jasmientje_14@hot...] [2008-12-07 17:52:46] [e7b1048c2c3a353441b9143db4404b91] [Current]
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Dataseries X:
97,8
107,4
117,5
105,6
97,4
99,5
98,0
104,3
100,6
101,1
103,9
96,9
95,5
108,4
117,0
103,8
100,8
110,6
104,0
112,6
107,3
98,9
109,8
104,9
102,2
123,9
124,9
112,7
121,9
100,6
104,3
120,4
107,5
102,9
125,6
107,5
108,8
128,4
121,1
119,5
128,7
108,7
105,5
119,8
111,3
110,6
120,1
97,5
107,7
127,3
117,2
119,8
116,2
111,0
112,4
130,6
109,1
118,8
123,9
101,6
112,8
128,0
129,6
125,8
119,5
115,7
113,6
129,7
112,0
116,8
127,0
112,1
114,2
121,1
131,6
125,0
120,4
117,7
117,5
120,6
127,5
112,3
124,5
115,2
105,4




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=30196&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=30196&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=30196&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
1102.55.8628258777425120.6
2106.1333333333336.0688973587889221.5
3112.8666666666679.8240274404907525
41159.4457301560979531.2
5116.38.4625377668017229
6120.2166666666677.2645882487751817.7
7120.6333333333335.7246410500148519.3

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 102.5 & 5.86282587774251 & 20.6 \tabularnewline
2 & 106.133333333333 & 6.06889735878892 & 21.5 \tabularnewline
3 & 112.866666666667 & 9.82402744049075 & 25 \tabularnewline
4 & 115 & 9.44573015609795 & 31.2 \tabularnewline
5 & 116.3 & 8.46253776680172 & 29 \tabularnewline
6 & 120.216666666667 & 7.26458824877518 & 17.7 \tabularnewline
7 & 120.633333333333 & 5.72464105001485 & 19.3 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=30196&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]102.5[/C][C]5.86282587774251[/C][C]20.6[/C][/ROW]
[ROW][C]2[/C][C]106.133333333333[/C][C]6.06889735878892[/C][C]21.5[/C][/ROW]
[ROW][C]3[/C][C]112.866666666667[/C][C]9.82402744049075[/C][C]25[/C][/ROW]
[ROW][C]4[/C][C]115[/C][C]9.44573015609795[/C][C]31.2[/C][/ROW]
[ROW][C]5[/C][C]116.3[/C][C]8.46253776680172[/C][C]29[/C][/ROW]
[ROW][C]6[/C][C]120.216666666667[/C][C]7.26458824877518[/C][C]17.7[/C][/ROW]
[ROW][C]7[/C][C]120.633333333333[/C][C]5.72464105001485[/C][C]19.3[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=30196&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=30196&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
1102.55.8628258777425120.6
2106.1333333333336.0688973587889221.5
3112.8666666666679.8240274404907525
41159.4457301560979531.2
5116.38.4625377668017229
6120.2166666666677.2645882487751817.7
7120.6333333333335.7246410500148519.3







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha0.0883228019571733
beta0.0655641508032655
S.D.0.109336391638342
T-STAT0.599655337265344
p-value0.57487272141009

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 0.0883228019571733 \tabularnewline
beta & 0.0655641508032655 \tabularnewline
S.D. & 0.109336391638342 \tabularnewline
T-STAT & 0.599655337265344 \tabularnewline
p-value & 0.57487272141009 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=30196&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]0.0883228019571733[/C][/ROW]
[ROW][C]beta[/C][C]0.0655641508032655[/C][/ROW]
[ROW][C]S.D.[/C][C]0.109336391638342[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.599655337265344[/C][/ROW]
[ROW][C]p-value[/C][C]0.57487272141009[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=30196&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=30196&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)
alpha0.0883228019571733
beta0.0655641508032655
S.D.0.109336391638342
T-STAT0.599655337265344
p-value0.57487272141009







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-3.24352702691584
beta1.10773375025661
S.D.1.59850245769463
T-STAT0.69298220026148
p-value0.519184667485418
Lambda-0.107733750256608

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -3.24352702691584 \tabularnewline
beta & 1.10773375025661 \tabularnewline
S.D. & 1.59850245769463 \tabularnewline
T-STAT & 0.69298220026148 \tabularnewline
p-value & 0.519184667485418 \tabularnewline
Lambda & -0.107733750256608 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=30196&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-3.24352702691584[/C][/ROW]
[ROW][C]beta[/C][C]1.10773375025661[/C][/ROW]
[ROW][C]S.D.[/C][C]1.59850245769463[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.69298220026148[/C][/ROW]
[ROW][C]p-value[/C][C]0.519184667485418[/C][/ROW]
[ROW][C]Lambda[/C][C]-0.107733750256608[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=30196&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=30196&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-3.24352702691584
beta1.10773375025661
S.D.1.59850245769463
T-STAT0.69298220026148
p-value0.519184667485418
Lambda-0.107733750256608



Parameters (Session):
par1 = 60 ; par2 = 1 ; par3 = 1 ; par4 = 0 ; par5 = 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')