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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

Tue, 17 Aug 2010 16:24:17 +0000

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/2010/Aug/17/t128206221332gbyr0vcw0izcb.htm/, Retrieved Sat, 27 Apr 2024 07:12:11 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=79149, Retrieved Sat, 27 Apr 2024 07:12:11 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Magali De Reu

Estimated Impact

121

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

-       [Standard Deviation-Mean Plot] [tijdreeks 2 stap 21] [2010-08-17 16:24:17] [07915b1f88a41fb8d82e27c5eaa7bbed] [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	2 seconds
R Server	'RServer@AstonUniversity' @ vre.aston.ac.uk

\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 & 'RServer@AstonUniversity' @ vre.aston.ac.uk \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=79149&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]'RServer@AstonUniversity' @ vre.aston.ac.uk[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=79149&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=79149&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	2 seconds
R Server	'RServer@AstonUniversity' @ vre.aston.ac.uk

Standard Deviation-Mean Plot
Section	Mean	Standard Deviation	Range
1	118.25	1.70782512765993	4
2	114.25	1.25830573921179	3
3	118	1.4142135623731	3
4	121	3.91578004149024	9
5	111	2.16024689946929	5
6	123	3.46410161513775	8
7	115.75	6.13052471924984	14
8	104	2.44948974278318	6
9	128.25	5.1234753829798	11
10	122.75	4.19324854180304	10
11	119.25	5.5	12
12	149.5	4.43471156521669	10
13	135.5	7.72442015083764	18
14	122.75	2.75378527364305	6
15	140.75	1.5	3
16	120.5	8.10349718742881	19
17	102.75	4.11298755975102	10
18	126.75	1.5	3
19	105.25	5.37742193496723	13
20	94.5	4.65474668125631	9
21	118.75	3.30403793359983	8

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 118.25 & 1.70782512765993 & 4 \tabularnewline
2 & 114.25 & 1.25830573921179 & 3 \tabularnewline
3 & 118 & 1.4142135623731 & 3 \tabularnewline
4 & 121 & 3.91578004149024 & 9 \tabularnewline
5 & 111 & 2.16024689946929 & 5 \tabularnewline
6 & 123 & 3.46410161513775 & 8 \tabularnewline
7 & 115.75 & 6.13052471924984 & 14 \tabularnewline
8 & 104 & 2.44948974278318 & 6 \tabularnewline
9 & 128.25 & 5.1234753829798 & 11 \tabularnewline
10 & 122.75 & 4.19324854180304 & 10 \tabularnewline
11 & 119.25 & 5.5 & 12 \tabularnewline
12 & 149.5 & 4.43471156521669 & 10 \tabularnewline
13 & 135.5 & 7.72442015083764 & 18 \tabularnewline
14 & 122.75 & 2.75378527364305 & 6 \tabularnewline
15 & 140.75 & 1.5 & 3 \tabularnewline
16 & 120.5 & 8.10349718742881 & 19 \tabularnewline
17 & 102.75 & 4.11298755975102 & 10 \tabularnewline
18 & 126.75 & 1.5 & 3 \tabularnewline
19 & 105.25 & 5.37742193496723 & 13 \tabularnewline
20 & 94.5 & 4.65474668125631 & 9 \tabularnewline
21 & 118.75 & 3.30403793359983 & 8 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=79149&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]118.25[/C][C]1.70782512765993[/C][C]4[/C][/ROW]
[ROW][C]2[/C][C]114.25[/C][C]1.25830573921179[/C][C]3[/C][/ROW]
[ROW][C]3[/C][C]118[/C][C]1.4142135623731[/C][C]3[/C][/ROW]
[ROW][C]4[/C][C]121[/C][C]3.91578004149024[/C][C]9[/C][/ROW]
[ROW][C]5[/C][C]111[/C][C]2.16024689946929[/C][C]5[/C][/ROW]
[ROW][C]6[/C][C]123[/C][C]3.46410161513775[/C][C]8[/C][/ROW]
[ROW][C]7[/C][C]115.75[/C][C]6.13052471924984[/C][C]14[/C][/ROW]
[ROW][C]8[/C][C]104[/C][C]2.44948974278318[/C][C]6[/C][/ROW]
[ROW][C]9[/C][C]128.25[/C][C]5.1234753829798[/C][C]11[/C][/ROW]
[ROW][C]10[/C][C]122.75[/C][C]4.19324854180304[/C][C]10[/C][/ROW]
[ROW][C]11[/C][C]119.25[/C][C]5.5[/C][C]12[/C][/ROW]
[ROW][C]12[/C][C]149.5[/C][C]4.43471156521669[/C][C]10[/C][/ROW]
[ROW][C]13[/C][C]135.5[/C][C]7.72442015083764[/C][C]18[/C][/ROW]
[ROW][C]14[/C][C]122.75[/C][C]2.75378527364305[/C][C]6[/C][/ROW]
[ROW][C]15[/C][C]140.75[/C][C]1.5[/C][C]3[/C][/ROW]
[ROW][C]16[/C][C]120.5[/C][C]8.10349718742881[/C][C]19[/C][/ROW]
[ROW][C]17[/C][C]102.75[/C][C]4.11298755975102[/C][C]10[/C][/ROW]
[ROW][C]18[/C][C]126.75[/C][C]1.5[/C][C]3[/C][/ROW]
[ROW][C]19[/C][C]105.25[/C][C]5.37742193496723[/C][C]13[/C][/ROW]
[ROW][C]20[/C][C]94.5[/C][C]4.65474668125631[/C][C]9[/C][/ROW]
[ROW][C]21[/C][C]118.75[/C][C]3.30403793359983[/C][C]8[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=79149&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=79149&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	118.25	1.70782512765993	4
2	114.25	1.25830573921179	3
3	118	1.4142135623731	3
4	121	3.91578004149024	9
5	111	2.16024689946929	5
6	123	3.46410161513775	8
7	115.75	6.13052471924984	14
8	104	2.44948974278318	6
9	128.25	5.1234753829798	11
10	122.75	4.19324854180304	10
11	119.25	5.5	12
12	149.5	4.43471156521669	10
13	135.5	7.72442015083764	18
14	122.75	2.75378527364305	6
15	140.75	1.5	3
16	120.5	8.10349718742881	19
17	102.75	4.11298755975102	10
18	126.75	1.5	3
19	105.25	5.37742193496723	13
20	94.5	4.65474668125631	9
21	118.75	3.30403793359983	8

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	2.90784325883232
beta	0.00784800446701681
S.D.	0.0362087975286237
T-STAT	0.21674302939259
p-value	0.830718879965459

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 2.90784325883232 \tabularnewline
beta & 0.00784800446701681 \tabularnewline
S.D. & 0.0362087975286237 \tabularnewline
T-STAT & 0.21674302939259 \tabularnewline
p-value & 0.830718879965459 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=79149&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]2.90784325883232[/C][/ROW]
[ROW][C]beta[/C][C]0.00784800446701681[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0362087975286237[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.21674302939259[/C][/ROW]
[ROW][C]p-value[/C][C]0.830718879965459[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=79149&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=79149&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	2.90784325883232
beta	0.00784800446701681
S.D.	0.0362087975286237
T-STAT	0.21674302939259
p-value	0.830718879965459

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	1.65193965634226
beta	-0.094067613959715
S.D.	1.23867155187979
T-STAT	-0.0759423382388652
p-value	0.940258922003047
Lambda	1.09406761395971

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 1.65193965634226 \tabularnewline
beta & -0.094067613959715 \tabularnewline
S.D. & 1.23867155187979 \tabularnewline
T-STAT & -0.0759423382388652 \tabularnewline
p-value & 0.940258922003047 \tabularnewline
Lambda & 1.09406761395971 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=79149&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]1.65193965634226[/C][/ROW]
[ROW][C]beta[/C][C]-0.094067613959715[/C][/ROW]
[ROW][C]S.D.[/C][C]1.23867155187979[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.0759423382388652[/C][/ROW]
[ROW][C]p-value[/C][C]0.940258922003047[/C][/ROW]
[ROW][C]Lambda[/C][C]1.09406761395971[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=79149&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=79149&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	1.65193965634226
beta	-0.094067613959715
S.D.	1.23867155187979
T-STAT	-0.0759423382388652
p-value	0.940258922003047
Lambda	1.09406761395971

Figure 1

PNG link

Postscript link

PDF link

Figure 2

PNG link

Postscript link

PDF link

Parameters (Session):

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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Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code