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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, 04 Dec 2009 02:49:19 -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/04/t1259920498snk992e6imgq5a0.htm/, Retrieved Sat, 27 Apr 2024 14:56:37 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=63220, Retrieved Sat, 27 Apr 2024 14:56:37 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact115
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]
- RMP   [Standard Deviation-Mean Plot] [] [2009-11-27 14:40:44] [b98453cac15ba1066b407e146608df68]
-    D      [Standard Deviation-Mean Plot] [WS 9 SMP Producti...] [2009-12-04 09:49:19] [eba9f01697e64705b70041e6f338cb22] [Current]
-    D        [Standard Deviation-Mean Plot] [WS 9 Review 2 SMP] [2009-12-10 16:46:08] [83058a88a37d754675a5cd22dab372fc]
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Dataseries X:
98,8
100,5
110,4
96,4
101,9
106,2
81
94,7
101
109,4
102,3
90,7
96,2
96,1
106
103,1
102
104,7
86
92,1
106,9
112,6
101,7
92
97,4
97
105,4
102,7
98,1
104,5
87,4
89,9
109,8
111,7
98,6
96,9
95,1
97
112,7
102,9
97,4
111,4
87,4
96,8
114,1
110,3
103,9
101,6
94,6
95,9
104,7
102,8
98,1
113,9
80,9
95,7
113,2
105,9
108,8
102,3
99
100,7
115,5
100,7
109,9
114,6
85,4
100,5
114,8
116,5
112,9
102
106
105,3
118,8
106,1
109,3
117,2
92,5
104,2
112,5
122,4
113,3
100
110,7
112,8
109,8
117,3
109,1
115,9
96
99,8
116,8
115,7
99,4
94,3




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=63220&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=63220&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=63220&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
199.44166666666678.153912427711529.4
299.957.5858121156897526.6
399.957.2695504425214424.3
4102.558.2741107734250926.7
5101.49.1665399440276633
6106.0416666666679.4891764498806631.1
7108.9666666666678.4264015109797929.9
8108.1333333333338.4911005104631723

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 99.4416666666667 & 8.1539124277115 & 29.4 \tabularnewline
2 & 99.95 & 7.58581211568975 & 26.6 \tabularnewline
3 & 99.95 & 7.26955044252144 & 24.3 \tabularnewline
4 & 102.55 & 8.27411077342509 & 26.7 \tabularnewline
5 & 101.4 & 9.16653994402766 & 33 \tabularnewline
6 & 106.041666666667 & 9.48917644988066 & 31.1 \tabularnewline
7 & 108.966666666667 & 8.42640151097979 & 29.9 \tabularnewline
8 & 108.133333333333 & 8.49110051046317 & 23 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=63220&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]99.4416666666667[/C][C]8.1539124277115[/C][C]29.4[/C][/ROW]
[ROW][C]2[/C][C]99.95[/C][C]7.58581211568975[/C][C]26.6[/C][/ROW]
[ROW][C]3[/C][C]99.95[/C][C]7.26955044252144[/C][C]24.3[/C][/ROW]
[ROW][C]4[/C][C]102.55[/C][C]8.27411077342509[/C][C]26.7[/C][/ROW]
[ROW][C]5[/C][C]101.4[/C][C]9.16653994402766[/C][C]33[/C][/ROW]
[ROW][C]6[/C][C]106.041666666667[/C][C]9.48917644988066[/C][C]31.1[/C][/ROW]
[ROW][C]7[/C][C]108.966666666667[/C][C]8.42640151097979[/C][C]29.9[/C][/ROW]
[ROW][C]8[/C][C]108.133333333333[/C][C]8.49110051046317[/C][C]23[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=63220&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=63220&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
199.44166666666678.153912427711529.4
299.957.5858121156897526.6
399.957.2695504425214424.3
4102.558.2741107734250926.7
5101.49.1665399440276633
6106.0416666666679.4891764498806631.1
7108.9666666666678.4264015109797929.9
8108.1333333333338.4911005104631723







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-1.21232545148444
beta0.0926332526760471
S.D.0.0678787250765325
T-STAT1.36468757437038
p-value0.221312586647143

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -1.21232545148444 \tabularnewline
beta & 0.0926332526760471 \tabularnewline
S.D. & 0.0678787250765325 \tabularnewline
T-STAT & 1.36468757437038 \tabularnewline
p-value & 0.221312586647143 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=63220&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-1.21232545148444[/C][/ROW]
[ROW][C]beta[/C][C]0.0926332526760471[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0678787250765325[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.36468757437038[/C][/ROW]
[ROW][C]p-value[/C][C]0.221312586647143[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=63220&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=63220&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)
alpha-1.21232545148444
beta0.0926332526760471
S.D.0.0678787250765325
T-STAT1.36468757437038
p-value0.221312586647143







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-3.43814013772246
beta1.19856956670259
S.D.0.837248415940214
T-STAT1.43155787921870
p-value0.202232416702700
Lambda-0.198569566702590

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -3.43814013772246 \tabularnewline
beta & 1.19856956670259 \tabularnewline
S.D. & 0.837248415940214 \tabularnewline
T-STAT & 1.43155787921870 \tabularnewline
p-value & 0.202232416702700 \tabularnewline
Lambda & -0.198569566702590 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=63220&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-3.43814013772246[/C][/ROW]
[ROW][C]beta[/C][C]1.19856956670259[/C][/ROW]
[ROW][C]S.D.[/C][C]0.837248415940214[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.43155787921870[/C][/ROW]
[ROW][C]p-value[/C][C]0.202232416702700[/C][/ROW]
[ROW][C]Lambda[/C][C]-0.198569566702590[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=63220&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=63220&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-3.43814013772246
beta1.19856956670259
S.D.0.837248415940214
T-STAT1.43155787921870
p-value0.202232416702700
Lambda-0.198569566702590



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')