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Author's title

Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationWed, 28 Nov 2007 12:42:18 -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/2007/Nov/28/t1196278432da8frbf7ri6zboq.htm/, Retrieved Wed, 01 May 2024 23:29:05 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=7257, Retrieved Wed, 01 May 2024 23:29:05 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsInducing stationarity time series
Estimated Impact190
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Standard Deviation-Mean Plot] [Case IV Question I.3] [2007-11-28 19:42:18] [fd802f308f037a9692de8c23f8b60e49] [Current]
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Dataseries X:
88,7
55,4
46,6
90,9
84,9
89
90,2
72,3
83
71,6
75,4
85,1
81,2
68,7
68,4
93,7
96,6
101,8
93,6
88,9
114,1
82,3
96,4
104
88,2
85,2
87,1
85,5
89,1
105,2
82,9
86,8
112
97,4
88,9
109,4
87,8
90,5
79,3
114,9
118,8
125
96,1
116,7
119,5
104,1
121
127,3
117,7
108
89,4
137,4
142
137,3
122,8
126,1
147,6
115,7
139,2
150,9




Summary of compuational 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 compuational 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=7257&T=0

[TABLE]
[ROW][C]Summary of compuational 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=7257&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=7257&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 compuational 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
177.758333333333314.30190440804899.7
290.808333333333313.742995461049458.7
393.141666666666710.203961648954565.4
4108.41666666666716.223990840353641.8
5127.84166666666718.046780540550466

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 77.7583333333333 & 14.3019044080489 & 9.7 \tabularnewline
2 & 90.8083333333333 & 13.7429954610494 & 58.7 \tabularnewline
3 & 93.1416666666667 & 10.2039616489545 & 65.4 \tabularnewline
4 & 108.416666666667 & 16.2239908403536 & 41.8 \tabularnewline
5 & 127.841666666667 & 18.0467805405504 & 66 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=7257&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]77.7583333333333[/C][C]14.3019044080489[/C][C]9.7[/C][/ROW]
[ROW][C]2[/C][C]90.8083333333333[/C][C]13.7429954610494[/C][C]58.7[/C][/ROW]
[ROW][C]3[/C][C]93.1416666666667[/C][C]10.2039616489545[/C][C]65.4[/C][/ROW]
[ROW][C]4[/C][C]108.416666666667[/C][C]16.2239908403536[/C][C]41.8[/C][/ROW]
[ROW][C]5[/C][C]127.841666666667[/C][C]18.0467805405504[/C][C]66[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=7257&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=7257&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
177.758333333333314.30190440804899.7
290.808333333333313.742995461049458.7
393.141666666666710.203961648954565.4
4108.41666666666716.223990840353641.8
5127.84166666666718.046780540550466







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha4.07379200334379
beta0.104727236526349
S.D.0.0647070339284107
T-STAT1.61848303296077
p-value0.203990927645998

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 4.07379200334379 \tabularnewline
beta & 0.104727236526349 \tabularnewline
S.D. & 0.0647070339284107 \tabularnewline
T-STAT & 1.61848303296077 \tabularnewline
p-value & 0.203990927645998 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=7257&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]4.07379200334379[/C][/ROW]
[ROW][C]beta[/C][C]0.104727236526349[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0647070339284107[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.61848303296077[/C][/ROW]
[ROW][C]p-value[/C][C]0.203990927645998[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=7257&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=7257&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)
alpha4.07379200334379
beta0.104727236526349
S.D.0.0647070339284107
T-STAT1.61848303296077
p-value0.203990927645998







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-0.388759389231183
beta0.663968321025102
S.D.0.534900958118038
T-STAT1.24129207650173
p-value0.302710289949818
Lambda0.336031678974898

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -0.388759389231183 \tabularnewline
beta & 0.663968321025102 \tabularnewline
S.D. & 0.534900958118038 \tabularnewline
T-STAT & 1.24129207650173 \tabularnewline
p-value & 0.302710289949818 \tabularnewline
Lambda & 0.336031678974898 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=7257&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-0.388759389231183[/C][/ROW]
[ROW][C]beta[/C][C]0.663968321025102[/C][/ROW]
[ROW][C]S.D.[/C][C]0.534900958118038[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.24129207650173[/C][/ROW]
[ROW][C]p-value[/C][C]0.302710289949818[/C][/ROW]
[ROW][C]Lambda[/C][C]0.336031678974898[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=7257&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=7257&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-0.388759389231183
beta0.663968321025102
S.D.0.534900958118038
T-STAT1.24129207650173
p-value0.302710289949818
Lambda0.336031678974898



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')