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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 computationWed, 17 Dec 2014 14:51:27 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2014/Dec/17/t1418828019wrlq5qrt0eq613i.htm/, Retrieved Thu, 16 May 2024 21:35:59 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=270360, Retrieved Thu, 16 May 2024 21:35:59 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact71
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [] [2008-12-08 19:22:39] [d2d412c7f4d35ffbf5ee5ee89db327d4]
- RMP   [Standard Deviation-Mean Plot] [] [2011-12-06 19:52:37] [b98453cac15ba1066b407e146608df68]
- RMP     [Standard Deviation-Mean Plot] [] [2014-11-26 15:14:23] [bcf5edf18529a33bd1494456d2c6cb9a]
- R PD        [Standard Deviation-Mean Plot] [] [2014-12-17 14:51:27] [6fc1b517ba5ef695988bbc0a377c4b82] [Current]
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Dataseries X:
12.90
7.40
12.20
12.80
7.40
6.70
12.60
14.80
13.30
11.10
8.20
11.40
6.40
10.60
12.00
6.30
11.30
11.90
9.30
9.60
10.00
6.40
13.80
10.80
13.80
11.70
10.90
16.10
13.40
9.90
11.50
8.30
11.70
6.10
9.00
9.70
10.80
10.30
10.40
12.70
9.30
11.80
5.90
11.40
13.00
10.80
12.30
11.30
11.80
7.90
12.70
12.30
11.60
6.70
10.90
12.10
13.30
10.10
5.70
14.30
8.00
13.30
9.30
12.50
7.60
15.90
9.20
9.10
11.10
13.00
14.50
12.20
12.30
11.40
8.80
14.60
7.30
12.60
13.00
12.60
13.20
9.90
7.70
10.50
13.40
10.90
4.30
10.30
11.80
11.20
11.40
8.60
13.20
12.60
5.60
9.90
8.80
7.70
9.00
7.30
11.40
13.60
7.90
10.70
10.30
8.30
9.60
14.20
8.50
13.50
4.90
6.40
9.60
11.60
11.10
4.35
12.70
18.10
17.85
16.60
12.60
17.10
19.10
16.10
13.35
18.40
14.70
10.60
12.60
16.20
13.60
18.90
14.10
14.50
16.15
14.75
14.80
12.45
12.65
17.35
8.60
18.40
16.10
11.60
17.75
15.25
17.65
15.60
16.35
17.65
13.60
11.70
14.35
14.75
18.25
9.90
16.00
18.25
16.85
14.60
13.85
18.95
15.60
14.85
11.75
18.45
15.90
17.10
16.10
19.90
10.95
18.45
15.10
15.00
11.35
15.95
18.10
14.60
15.40
15.40
17.60
13.35
19.10
15.35
7.60
13.40
13.90
19.10
15.25
12.90
16.10
17.35
13.15
12.15
12.60
10.35
15.40
9.60
18.20
13.60
14.85
14.75
14.10
14.90
16.25
19.25
13.60
13.60
15.65
12.75
14.60
9.85
12.65
11.90
19.20
16.60
11.20
15.25
11.90
13.20
16.35
12.40
15.85
14.35
18.15
11.15
15.65
17.75
7.65
12.35
15.60
19.30
15.20
17.10
15.60
18.40
19.05
18.55
19.10
13.10
12.85
9.50
4.50
11.85
13.60
11.70
12.40
13.35
11.40
14.90
19.90
17.75
11.20
14.60
17.60
14.05
16.10
13.35
11.85
11.95
14.75
15.15
13.20
16.85
7.85
7.70
12.60
7.85
10.95
12.35
9.95
14.90
16.65
13.40
13.95
15.70
16.85
10.95
15.35
12.20
15.10
17.75
15.20
14.60
16.65
8.10




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Sir Ronald Aylmer Fisher' @ fisher.wessa.net

\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 & 2 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ fisher.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=270360&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]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Ronald Aylmer Fisher' @ fisher.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=270360&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=270360&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 time2 seconds
R Server'Sir Ronald Aylmer Fisher' @ fisher.wessa.net







Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
110.59166666666672.5980624648819710
210.9752.3833200132827910.2
310.44166666666672.472520402920310.3
413.60833333333333.8444672675714914.75
515.59027777777782.3856960483097210
614.45972222222222.8022903756046311.65
714.38611111111113.4799550717771215.4

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 10.5916666666667 & 2.59806246488197 & 10 \tabularnewline
2 & 10.975 & 2.38332001328279 & 10.2 \tabularnewline
3 & 10.4416666666667 & 2.4725204029203 & 10.3 \tabularnewline
4 & 13.6083333333333 & 3.84446726757149 & 14.75 \tabularnewline
5 & 15.5902777777778 & 2.38569604830972 & 10 \tabularnewline
6 & 14.4597222222222 & 2.80229037560463 & 11.65 \tabularnewline
7 & 14.3861111111111 & 3.47995507177712 & 15.4 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=270360&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]10.5916666666667[/C][C]2.59806246488197[/C][C]10[/C][/ROW]
[ROW][C]2[/C][C]10.975[/C][C]2.38332001328279[/C][C]10.2[/C][/ROW]
[ROW][C]3[/C][C]10.4416666666667[/C][C]2.4725204029203[/C][C]10.3[/C][/ROW]
[ROW][C]4[/C][C]13.6083333333333[/C][C]3.84446726757149[/C][C]14.75[/C][/ROW]
[ROW][C]5[/C][C]15.5902777777778[/C][C]2.38569604830972[/C][C]10[/C][/ROW]
[ROW][C]6[/C][C]14.4597222222222[/C][C]2.80229037560463[/C][C]11.65[/C][/ROW]
[ROW][C]7[/C][C]14.3861111111111[/C][C]3.47995507177712[/C][C]15.4[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=270360&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=270360&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
110.59166666666672.5980624648819710
210.9752.3833200132827910.2
310.44166666666672.472520402920310.3
413.60833333333333.8444672675714914.75
515.59027777777782.3856960483097210
614.45972222222222.8022903756046311.65
714.38611111111113.4799550717771215.4







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha1.57494961656858
beta0.099293598143449
S.D.0.113136936692298
T-STAT0.877640857587481
p-value0.420303053268287

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 1.57494961656858 \tabularnewline
beta & 0.099293598143449 \tabularnewline
S.D. & 0.113136936692298 \tabularnewline
T-STAT & 0.877640857587481 \tabularnewline
p-value & 0.420303053268287 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=270360&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]1.57494961656858[/C][/ROW]
[ROW][C]beta[/C][C]0.099293598143449[/C][/ROW]
[ROW][C]S.D.[/C][C]0.113136936692298[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.877640857587481[/C][/ROW]
[ROW][C]p-value[/C][C]0.420303053268287[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=270360&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=270360&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)
alpha1.57494961656858
beta0.099293598143449
S.D.0.113136936692298
T-STAT0.877640857587481
p-value0.420303053268287







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-0.118527952934449
beta0.452437186157491
S.D.0.464387612240324
T-STAT0.974266268591488
p-value0.374669708379468
Lambda0.547562813842509

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -0.118527952934449 \tabularnewline
beta & 0.452437186157491 \tabularnewline
S.D. & 0.464387612240324 \tabularnewline
T-STAT & 0.974266268591488 \tabularnewline
p-value & 0.374669708379468 \tabularnewline
Lambda & 0.547562813842509 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=270360&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-0.118527952934449[/C][/ROW]
[ROW][C]beta[/C][C]0.452437186157491[/C][/ROW]
[ROW][C]S.D.[/C][C]0.464387612240324[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.974266268591488[/C][/ROW]
[ROW][C]p-value[/C][C]0.374669708379468[/C][/ROW]
[ROW][C]Lambda[/C][C]0.547562813842509[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=270360&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=270360&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-0.118527952934449
beta0.452437186157491
S.D.0.464387612240324
T-STAT0.974266268591488
p-value0.374669708379468
Lambda0.547562813842509



Parameters (Session):
par1 = 1 ; par2 = 0 ; par3 = 0 ; par4 = 12 ;
Parameters (R input):
par1 = 36 ;
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')