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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

Sun, 11 May 2008 12:50:32 -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/11/t1210531896t4y6ph8iaflybm6.htm/, Retrieved Sun, 19 May 2024 18:04:31 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=12280, Retrieved Sun, 19 May 2024 18:04:31 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

194

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

-       [Standard Deviation-Mean Plot] [cijferreeks - oli...] [2008-05-11 18:50:32] [e744b461908af7c125bdbb2f3548f5e0] [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=12280&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=12280&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=12280&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	94.875	3.67276008836225	8.8
2	110.325	4.70203856499143	9.8
3	109.925	1.69582821457049	3.59999999999999
4	115.65	5.00033332222296	11
5	116.675	5.22198876546729	10.6
6	148.65	7.03064719638242	17
7	181.175	11.2594774893568	25.3
8	138.15	26.4162197648844	56.3
9	107.075	1.02102889283311	2.30000000000000
10	121.275	8.74809503072907	18.9
11	128.1	10.2055540434282	21.5
12	115.85	2.23532249723987	4.80000000000001
13	115.725	1.63579746097533	3.80000000000001
14	113.65	3.48950808376578	6.7
15	129.9	8.07589004382799	19.4
16	148.475	3.35099487714718	8.19999999999999
17	170.55	10.2086564574711	22.7
18	217.7	22.7628352071236	53.2

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 94.875 & 3.67276008836225 & 8.8 \tabularnewline
2 & 110.325 & 4.70203856499143 & 9.8 \tabularnewline
3 & 109.925 & 1.69582821457049 & 3.59999999999999 \tabularnewline
4 & 115.65 & 5.00033332222296 & 11 \tabularnewline
5 & 116.675 & 5.22198876546729 & 10.6 \tabularnewline
6 & 148.65 & 7.03064719638242 & 17 \tabularnewline
7 & 181.175 & 11.2594774893568 & 25.3 \tabularnewline
8 & 138.15 & 26.4162197648844 & 56.3 \tabularnewline
9 & 107.075 & 1.02102889283311 & 2.30000000000000 \tabularnewline
10 & 121.275 & 8.74809503072907 & 18.9 \tabularnewline
11 & 128.1 & 10.2055540434282 & 21.5 \tabularnewline
12 & 115.85 & 2.23532249723987 & 4.80000000000001 \tabularnewline
13 & 115.725 & 1.63579746097533 & 3.80000000000001 \tabularnewline
14 & 113.65 & 3.48950808376578 & 6.7 \tabularnewline
15 & 129.9 & 8.07589004382799 & 19.4 \tabularnewline
16 & 148.475 & 3.35099487714718 & 8.19999999999999 \tabularnewline
17 & 170.55 & 10.2086564574711 & 22.7 \tabularnewline
18 & 217.7 & 22.7628352071236 & 53.2 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=12280&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]94.875[/C][C]3.67276008836225[/C][C]8.8[/C][/ROW]
[ROW][C]2[/C][C]110.325[/C][C]4.70203856499143[/C][C]9.8[/C][/ROW]
[ROW][C]3[/C][C]109.925[/C][C]1.69582821457049[/C][C]3.59999999999999[/C][/ROW]
[ROW][C]4[/C][C]115.65[/C][C]5.00033332222296[/C][C]11[/C][/ROW]
[ROW][C]5[/C][C]116.675[/C][C]5.22198876546729[/C][C]10.6[/C][/ROW]
[ROW][C]6[/C][C]148.65[/C][C]7.03064719638242[/C][C]17[/C][/ROW]
[ROW][C]7[/C][C]181.175[/C][C]11.2594774893568[/C][C]25.3[/C][/ROW]
[ROW][C]8[/C][C]138.15[/C][C]26.4162197648844[/C][C]56.3[/C][/ROW]
[ROW][C]9[/C][C]107.075[/C][C]1.02102889283311[/C][C]2.30000000000000[/C][/ROW]
[ROW][C]10[/C][C]121.275[/C][C]8.74809503072907[/C][C]18.9[/C][/ROW]
[ROW][C]11[/C][C]128.1[/C][C]10.2055540434282[/C][C]21.5[/C][/ROW]
[ROW][C]12[/C][C]115.85[/C][C]2.23532249723987[/C][C]4.80000000000001[/C][/ROW]
[ROW][C]13[/C][C]115.725[/C][C]1.63579746097533[/C][C]3.80000000000001[/C][/ROW]
[ROW][C]14[/C][C]113.65[/C][C]3.48950808376578[/C][C]6.7[/C][/ROW]
[ROW][C]15[/C][C]129.9[/C][C]8.07589004382799[/C][C]19.4[/C][/ROW]
[ROW][C]16[/C][C]148.475[/C][C]3.35099487714718[/C][C]8.19999999999999[/C][/ROW]
[ROW][C]17[/C][C]170.55[/C][C]10.2086564574711[/C][C]22.7[/C][/ROW]
[ROW][C]18[/C][C]217.7[/C][C]22.7628352071236[/C][C]53.2[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=12280&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=12280&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	94.875	3.67276008836225	8.8
2	110.325	4.70203856499143	9.8
3	109.925	1.69582821457049	3.59999999999999
4	115.65	5.00033332222296	11
5	116.675	5.22198876546729	10.6
6	148.65	7.03064719638242	17
7	181.175	11.2594774893568	25.3
8	138.15	26.4162197648844	56.3
9	107.075	1.02102889283311	2.30000000000000
10	121.275	8.74809503072907	18.9
11	128.1	10.2055540434282	21.5
12	115.85	2.23532249723987	4.80000000000001
13	115.725	1.63579746097533	3.80000000000001
14	113.65	3.48950808376578	6.7
15	129.9	8.07589004382799	19.4
16	148.475	3.35099487714718	8.19999999999999
17	170.55	10.2086564574711	22.7
18	217.7	22.7628352071236	53.2

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	-12.1917065960636
beta	0.149423148530104
S.D.	0.042142511515581
T-STAT	3.54566311205395
p-value	0.00269105283925149

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -12.1917065960636 \tabularnewline
beta & 0.149423148530104 \tabularnewline
S.D. & 0.042142511515581 \tabularnewline
T-STAT & 3.54566311205395 \tabularnewline
p-value & 0.00269105283925149 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=12280&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-12.1917065960636[/C][/ROW]
[ROW][C]beta[/C][C]0.149423148530104[/C][/ROW]
[ROW][C]S.D.[/C][C]0.042142511515581[/C][/ROW]
[ROW][C]T-STAT[/C][C]3.54566311205395[/C][/ROW]
[ROW][C]p-value[/C][C]0.00269105283925149[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=12280&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=12280&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	-12.1917065960636
beta	0.149423148530104
S.D.	0.042142511515581
T-STAT	3.54566311205395
p-value	0.00269105283925149

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	-12.2008319494622
beta	2.8522911866427
S.D.	0.769610431352819
T-STAT	3.70614933275911
p-value	0.00191730569613470
Lambda	-1.8522911866427

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -12.2008319494622 \tabularnewline
beta & 2.8522911866427 \tabularnewline
S.D. & 0.769610431352819 \tabularnewline
T-STAT & 3.70614933275911 \tabularnewline
p-value & 0.00191730569613470 \tabularnewline
Lambda & -1.8522911866427 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=12280&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-12.2008319494622[/C][/ROW]
[ROW][C]beta[/C][C]2.8522911866427[/C][/ROW]
[ROW][C]S.D.[/C][C]0.769610431352819[/C][/ROW]
[ROW][C]T-STAT[/C][C]3.70614933275911[/C][/ROW]
[ROW][C]p-value[/C][C]0.00191730569613470[/C][/ROW]
[ROW][C]Lambda[/C][C]-1.8522911866427[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=12280&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=12280&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	-12.2008319494622
beta	2.8522911866427
S.D.	0.769610431352819
T-STAT	3.70614933275911
p-value	0.00191730569613470
Lambda	-1.8522911866427

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