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Author's title

Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationTue, 27 Nov 2007 11:46:56 -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/27/t1196188753nqlvlttcr3zzl7z.htm/, Retrieved Sun, 05 May 2024 19:19:20 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=6916, Retrieved Sun, 05 May 2024 19:19:20 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsInducing stationarity in time series
Estimated Impact193
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] [2007-11-27 18:46:56] [fd802f308f037a9692de8c23f8b60e49] [Current]
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Dataseries X:
113,2
105,5
77,8
102,1
97
95,5
99,3
86,4
92,4
85,7
61,9
104,9
107,9
95,6
79,8
94,8
93,7
108,1
96,9
88,8
106,7
86,8
69,8
110,9
105,4
99,2
84,4
87,2
91,9
97,9
94,5
85
100,3
78,7
65,8
104,8
96
103,3
82,9
91,4
94,5
109,3
92,1
99,3
109,6
87,5
73,1
110,7
111,6
110,7
84
101,6
102,1
113,9
99
100,4
109,5
93
76,8
105,3




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=6916&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=6916&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6916&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
193.47513.959039104726117.2
294.983333333333312.450544590742215.3
391.258333333333311.64524548578727.6
495.808333333333311.475543824177023.5
5100.65833333333311.308762357597122

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 93.475 & 13.9590391047261 & 17.2 \tabularnewline
2 & 94.9833333333333 & 12.4505445907422 & 15.3 \tabularnewline
3 & 91.2583333333333 & 11.645245485787 & 27.6 \tabularnewline
4 & 95.8083333333333 & 11.4755438241770 & 23.5 \tabularnewline
5 & 100.658333333333 & 11.3087623575971 & 22 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=6916&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]93.475[/C][C]13.9590391047261[/C][C]17.2[/C][/ROW]
[ROW][C]2[/C][C]94.9833333333333[/C][C]12.4505445907422[/C][C]15.3[/C][/ROW]
[ROW][C]3[/C][C]91.2583333333333[/C][C]11.645245485787[/C][C]27.6[/C][/ROW]
[ROW][C]4[/C][C]95.8083333333333[/C][C]11.4755438241770[/C][C]23.5[/C][/ROW]
[ROW][C]5[/C][C]100.658333333333[/C][C]11.3087623575971[/C][C]22[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=6916&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6916&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
193.47513.959039104726117.2
294.983333333333312.450544590742215.3
391.258333333333311.64524548578727.6
495.808333333333311.475543824177023.5
5100.65833333333311.308762357597122







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha24.2912601639635
beta-0.127297956928609
S.D.0.165215357436677
T-STAT-0.770497119055045
p-value0.49712181627101

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 24.2912601639635 \tabularnewline
beta & -0.127297956928609 \tabularnewline
S.D. & 0.165215357436677 \tabularnewline
T-STAT & -0.770497119055045 \tabularnewline
p-value & 0.49712181627101 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=6916&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]24.2912601639635[/C][/ROW]
[ROW][C]beta[/C][C]-0.127297956928609[/C][/ROW]
[ROW][C]S.D.[/C][C]0.165215357436677[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.770497119055045[/C][/ROW]
[ROW][C]p-value[/C][C]0.49712181627101[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=6916&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6916&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)
alpha24.2912601639635
beta-0.127297956928609
S.D.0.165215357436677
T-STAT-0.770497119055045
p-value0.49712181627101







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha6.95513862033024
beta-0.978837514058933
S.D.1.25682420090410
T-STAT-0.778818161963147
p-value0.492874232328485
Lambda1.97883751405893

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 6.95513862033024 \tabularnewline
beta & -0.978837514058933 \tabularnewline
S.D. & 1.25682420090410 \tabularnewline
T-STAT & -0.778818161963147 \tabularnewline
p-value & 0.492874232328485 \tabularnewline
Lambda & 1.97883751405893 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=6916&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]6.95513862033024[/C][/ROW]
[ROW][C]beta[/C][C]-0.978837514058933[/C][/ROW]
[ROW][C]S.D.[/C][C]1.25682420090410[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.778818161963147[/C][/ROW]
[ROW][C]p-value[/C][C]0.492874232328485[/C][/ROW]
[ROW][C]Lambda[/C][C]1.97883751405893[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=6916&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6916&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)
alpha6.95513862033024
beta-0.978837514058933
S.D.1.25682420090410
T-STAT-0.778818161963147
p-value0.492874232328485
Lambda1.97883751405893



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')