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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 computationMon, 08 Dec 2008 13:23:27 -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/08/t1228767838534ecjqwjs5nyms.htm/, Retrieved Thu, 31 Oct 2024 23:34:28 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=30949, Retrieved Thu, 31 Oct 2024 23:34:28 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsARMA proces WS5 Q1: standard deviation: totaal
Estimated Impact202
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F     [Law of Averages] [Random Walk Simul...] [2008-11-25 18:31:28] [b98453cac15ba1066b407e146608df68]
F RM D  [(Partial) Autocorrelation Function] [non stationary ti...] [2008-12-02 20:37:52] [47f64d63202c1921bd27f3073f07a153]
F RMPD    [Standard Deviation-Mean Plot] [non stationary ti...] [2008-12-03 13:34:49] [47f64d63202c1921bd27f3073f07a153]
F   P         [Standard Deviation-Mean Plot] [ARMA proces WS5 Q...] [2008-12-08 20:23:27] [74c7506a1ea162af3aa8be25bcd05d28] [Current]
Feedback Forum
2008-12-11 11:06:48 [72e979bcc364082694890d2eccc1a66f] [reply
De p-waarde ligt veel te hoog, ze overschrijdt het 5% betrouwbaarheidsinterval waardoor we de lambda-waarde niet mogen gebruiken. De student heeft dit verkeerd geïnterpreteerd.
2008-12-15 19:19:14 [Bénédicte Soens] [reply
Hier werd er inderdaad een fout gemaakt. Er werd wel gezegd dat de p-waarde niet significant verschillend is van 0 aangezien deze waarde hoger is dan 5% maar de beoordeling van de lambda is foutief. De lambda moeten we gelijkstellen aan 1 want deze van 0,8 mogen we niet gebruiken.

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Dataseries X:
8.4
8.4
8.4
8.6
8.9
8.8
8.3
7.5
7.2
7.5
8.8
9.3
9.3
8.7
8.2
8.3
8.5
8.6
8.6
8.2
8.1
8
8.6
8.7
8.8
8.5
8.4
8.5
8.7
8.7
8.6
8.5
8.3
8.1
8.2
8.1
8.1
7.9
7.9
7.9
8
8
7.9
8
7.7
7.2
7.5
7.3
7
7
7
7.2
7.3
7.1
6.8
6.6
6.2
6.2
6.8
6.9
6.8




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24

\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 & 3 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=30949&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]3 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=30949&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=30949&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 time3 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24







Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
18.341666666666670.6359793211808832.1
28.483333333333330.3537676004830221.3
38.450.2354878881270660.700000000000001
47.783333333333330.2949062511539840.9
56.841666666666670.3528026317499591.1

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 8.34166666666667 & 0.635979321180883 & 2.1 \tabularnewline
2 & 8.48333333333333 & 0.353767600483022 & 1.3 \tabularnewline
3 & 8.45 & 0.235487888127066 & 0.700000000000001 \tabularnewline
4 & 7.78333333333333 & 0.294906251153984 & 0.9 \tabularnewline
5 & 6.84166666666667 & 0.352802631749959 & 1.1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=30949&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]8.34166666666667[/C][C]0.635979321180883[/C][C]2.1[/C][/ROW]
[ROW][C]2[/C][C]8.48333333333333[/C][C]0.353767600483022[/C][C]1.3[/C][/ROW]
[ROW][C]3[/C][C]8.45[/C][C]0.235487888127066[/C][C]0.700000000000001[/C][/ROW]
[ROW][C]4[/C][C]7.78333333333333[/C][C]0.294906251153984[/C][C]0.9[/C][/ROW]
[ROW][C]5[/C][C]6.84166666666667[/C][C]0.352802631749959[/C][C]1.1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=30949&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=30949&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
18.341666666666670.6359793211808832.1
28.483333333333330.3537676004830221.3
38.450.2354878881270660.700000000000001
47.783333333333330.2949062511539840.9
56.841666666666670.3528026317499591.1







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha0.131223294401891
beta0.0304969228241969
S.D.0.126511703473526
T-STAT0.241060091571517
p-value0.825044604880323

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 0.131223294401891 \tabularnewline
beta & 0.0304969228241969 \tabularnewline
S.D. & 0.126511703473526 \tabularnewline
T-STAT & 0.241060091571517 \tabularnewline
p-value & 0.825044604880323 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=30949&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]0.131223294401891[/C][/ROW]
[ROW][C]beta[/C][C]0.0304969228241969[/C][/ROW]
[ROW][C]S.D.[/C][C]0.126511703473526[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.241060091571517[/C][/ROW]
[ROW][C]p-value[/C][C]0.825044604880323[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=30949&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=30949&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)
alpha0.131223294401891
beta0.0304969228241969
S.D.0.126511703473526
T-STAT0.241060091571517
p-value0.825044604880323







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-1.51752280844731
beta0.230202864241768
S.D.2.32925403054982
T-STAT0.0988311541903518
p-value0.927505939811374
Lambda0.769797135758232

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -1.51752280844731 \tabularnewline
beta & 0.230202864241768 \tabularnewline
S.D. & 2.32925403054982 \tabularnewline
T-STAT & 0.0988311541903518 \tabularnewline
p-value & 0.927505939811374 \tabularnewline
Lambda & 0.769797135758232 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=30949&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-1.51752280844731[/C][/ROW]
[ROW][C]beta[/C][C]0.230202864241768[/C][/ROW]
[ROW][C]S.D.[/C][C]2.32925403054982[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.0988311541903518[/C][/ROW]
[ROW][C]p-value[/C][C]0.927505939811374[/C][/ROW]
[ROW][C]Lambda[/C][C]0.769797135758232[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=30949&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=30949&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-1.51752280844731
beta0.230202864241768
S.D.2.32925403054982
T-STAT0.0988311541903518
p-value0.927505939811374
Lambda0.769797135758232



Parameters (Session):
par1 = 1 ; par2 = 1 ; par3 = 1 ; par4 = 12 ;
Parameters (R input):
par1 = 12 ; par2 = ; par3 = ; par4 = ; par5 = ; par6 = ; par7 = ; par8 = ; par9 = ; par10 = ; par11 = ; par12 = ; par13 = ; par14 = ; par15 = ; par16 = ; par17 = ; par18 = ; par19 = ; par20 = ;
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')