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Author's title

Author

*Unverified author*

R Software Module

rwasp_smp.wasp

Title produced by software

Standard Deviation-Mean Plot

Date of computation

Mon, 12 May 2008 08:14:00 -0600

Cite this page as follows

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2008/May/12/t1210601692exc4e4xn33gbzln.htm/, Retrieved Tue, 14 May 2024 21:18:26 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=12349, Retrieved Tue, 14 May 2024 21:18:26 +0000

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IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

160

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)

-       [Standard Deviation-Mean Plot] [werkloosheid voor...] [2008-05-12 14:14:00] [2fa459907c4dcce485bca7190e4cae85] [Current]

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Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	3 seconds
R Server	'Herman Ole Andreas Wold' @ 193.190.124.10:1001

\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 & 'Herman Ole Andreas Wold' @ 193.190.124.10:1001 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=12349&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]'Herman Ole Andreas Wold' @ 193.190.124.10:1001[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=12349&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=12349&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 Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	3 seconds
R Server	'Herman Ole Andreas Wold' @ 193.190.124.10:1001

Standard Deviation-Mean Plot
Section	Mean	Standard Deviation	Range
1	17.6	1.54272486205415	3.3
2	15.55	1.64418166068514	3.4
3	14.55	1.7	3.6
4	14.125	1.75380538639079	3.9
5	15.375	2.47302109439716	5.6
6	20.65	3.07083050655682	6.3
7	23.125	1.77270979012358	3.9
8	22.825	1.69975488428969	3.7
9	22.125	1.81911150473704	3.9
10	22.025	1.63375844807813	3.5
11	22.075	2.45950537032686	5.3
12	21.075	2.52636101933196	5.7
13	16.625	2.53952095220076	5.8
14	16.7	2.47251558808703	5.5
15	17.7	1.40712472794703	3.2
16	21.725	2.36273147014213	5.5
17	21.1	3.25883414736006	7.5
18	21.475	1.58403493227475	3.5
19	20.475	1.76139149538085	4.1
20	18.975	1.05316981853197	2.5

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 17.6 & 1.54272486205415 & 3.3 \tabularnewline
2 & 15.55 & 1.64418166068514 & 3.4 \tabularnewline
3 & 14.55 & 1.7 & 3.6 \tabularnewline
4 & 14.125 & 1.75380538639079 & 3.9 \tabularnewline
5 & 15.375 & 2.47302109439716 & 5.6 \tabularnewline
6 & 20.65 & 3.07083050655682 & 6.3 \tabularnewline
7 & 23.125 & 1.77270979012358 & 3.9 \tabularnewline
8 & 22.825 & 1.69975488428969 & 3.7 \tabularnewline
9 & 22.125 & 1.81911150473704 & 3.9 \tabularnewline
10 & 22.025 & 1.63375844807813 & 3.5 \tabularnewline
11 & 22.075 & 2.45950537032686 & 5.3 \tabularnewline
12 & 21.075 & 2.52636101933196 & 5.7 \tabularnewline
13 & 16.625 & 2.53952095220076 & 5.8 \tabularnewline
14 & 16.7 & 2.47251558808703 & 5.5 \tabularnewline
15 & 17.7 & 1.40712472794703 & 3.2 \tabularnewline
16 & 21.725 & 2.36273147014213 & 5.5 \tabularnewline
17 & 21.1 & 3.25883414736006 & 7.5 \tabularnewline
18 & 21.475 & 1.58403493227475 & 3.5 \tabularnewline
19 & 20.475 & 1.76139149538085 & 4.1 \tabularnewline
20 & 18.975 & 1.05316981853197 & 2.5 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=12349&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]17.6[/C][C]1.54272486205415[/C][C]3.3[/C][/ROW]
[ROW][C]2[/C][C]15.55[/C][C]1.64418166068514[/C][C]3.4[/C][/ROW]
[ROW][C]3[/C][C]14.55[/C][C]1.7[/C][C]3.6[/C][/ROW]
[ROW][C]4[/C][C]14.125[/C][C]1.75380538639079[/C][C]3.9[/C][/ROW]
[ROW][C]5[/C][C]15.375[/C][C]2.47302109439716[/C][C]5.6[/C][/ROW]
[ROW][C]6[/C][C]20.65[/C][C]3.07083050655682[/C][C]6.3[/C][/ROW]
[ROW][C]7[/C][C]23.125[/C][C]1.77270979012358[/C][C]3.9[/C][/ROW]
[ROW][C]8[/C][C]22.825[/C][C]1.69975488428969[/C][C]3.7[/C][/ROW]
[ROW][C]9[/C][C]22.125[/C][C]1.81911150473704[/C][C]3.9[/C][/ROW]
[ROW][C]10[/C][C]22.025[/C][C]1.63375844807813[/C][C]3.5[/C][/ROW]
[ROW][C]11[/C][C]22.075[/C][C]2.45950537032686[/C][C]5.3[/C][/ROW]
[ROW][C]12[/C][C]21.075[/C][C]2.52636101933196[/C][C]5.7[/C][/ROW]
[ROW][C]13[/C][C]16.625[/C][C]2.53952095220076[/C][C]5.8[/C][/ROW]
[ROW][C]14[/C][C]16.7[/C][C]2.47251558808703[/C][C]5.5[/C][/ROW]
[ROW][C]15[/C][C]17.7[/C][C]1.40712472794703[/C][C]3.2[/C][/ROW]
[ROW][C]16[/C][C]21.725[/C][C]2.36273147014213[/C][C]5.5[/C][/ROW]
[ROW][C]17[/C][C]21.1[/C][C]3.25883414736006[/C][C]7.5[/C][/ROW]
[ROW][C]18[/C][C]21.475[/C][C]1.58403493227475[/C][C]3.5[/C][/ROW]
[ROW][C]19[/C][C]20.475[/C][C]1.76139149538085[/C][C]4.1[/C][/ROW]
[ROW][C]20[/C][C]18.975[/C][C]1.05316981853197[/C][C]2.5[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=12349&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=12349&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
Section	Mean	Standard Deviation	Range
1	17.6	1.54272486205415	3.3
2	15.55	1.64418166068514	3.4
3	14.55	1.7	3.6
4	14.125	1.75380538639079	3.9
5	15.375	2.47302109439716	5.6
6	20.65	3.07083050655682	6.3
7	23.125	1.77270979012358	3.9
8	22.825	1.69975488428969	3.7
9	22.125	1.81911150473704	3.9
10	22.025	1.63375844807813	3.5
11	22.075	2.45950537032686	5.3
12	21.075	2.52636101933196	5.7
13	16.625	2.53952095220076	5.8
14	16.7	2.47251558808703	5.5
15	17.7	1.40712472794703	3.2
16	21.725	2.36273147014213	5.5
17	21.1	3.25883414736006	7.5
18	21.475	1.58403493227475	3.5
19	20.475	1.76139149538085	4.1
20	18.975	1.05316981853197	2.5

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	1.60109603685062
beta	0.0220619810090925
S.D.	0.0454315108323302
T-STAT	0.485609670576763
p-value	0.63310224671847

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 1.60109603685062 \tabularnewline
beta & 0.0220619810090925 \tabularnewline
S.D. & 0.0454315108323302 \tabularnewline
T-STAT & 0.485609670576763 \tabularnewline
p-value & 0.63310224671847 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=12349&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]1.60109603685062[/C][/ROW]
[ROW][C]beta[/C][C]0.0220619810090925[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0454315108323302[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.485609670576763[/C][/ROW]
[ROW][C]p-value[/C][C]0.63310224671847[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=12349&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=12349&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	1.60109603685062
beta	0.0220619810090925
S.D.	0.0454315108323302
T-STAT	0.485609670576763
p-value	0.63310224671847

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	0.114654872967423
beta	0.187843286094656
S.D.	0.411235761099703
T-STAT	0.456777605119594
p-value	0.653295042695329
Lambda	0.812156713905344

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 0.114654872967423 \tabularnewline
beta & 0.187843286094656 \tabularnewline
S.D. & 0.411235761099703 \tabularnewline
T-STAT & 0.456777605119594 \tabularnewline
p-value & 0.653295042695329 \tabularnewline
Lambda & 0.812156713905344 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=12349&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]0.114654872967423[/C][/ROW]
[ROW][C]beta[/C][C]0.187843286094656[/C][/ROW]
[ROW][C]S.D.[/C][C]0.411235761099703[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.456777605119594[/C][/ROW]
[ROW][C]p-value[/C][C]0.653295042695329[/C][/ROW]
[ROW][C]Lambda[/C][C]0.812156713905344[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=12349&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=12349&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	0.114654872967423
beta	0.187843286094656
S.D.	0.411235761099703
T-STAT	0.456777605119594
p-value	0.653295042695329
Lambda	0.812156713905344

Figure 1

PNG link

Postscript link

PDF link

Figure 2

PNG link

Postscript link

PDF link

Parameters (Session):

par1 = 4 ;

Parameters (R input):

par1 = 4 ;

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')

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Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code