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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

Wed, 14 May 2008 06:43:30 -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/14/t1210769151t5qc1vnn9goz841.htm/, Retrieved Tue, 14 May 2024 08:01:32 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=12531, Retrieved Tue, 14 May 2024 08:01:32 +0000

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IsPrivate?

No (this computation is public)

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Estimated Impact

225

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

-       [Standard Deviation-Mean Plot] [Standard Deviatio...] [2008-05-14 12:43:30] [d210e4b078ace379de89aa3420a86154] [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	'Gwilym Jenkins' @ 72.249.127.135

\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 & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=12531&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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=12531&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=12531&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	'Gwilym Jenkins' @ 72.249.127.135

Standard Deviation-Mean Plot
Section	Mean	Standard Deviation	Range
1	103.775	0.170782512765995	0.400000000000006
2	104.15	0.129099444873581	0.299999999999997
3	104.575	0.149999999999999	0.299999999999997
4	105.1	0.182574185835053	0.399999999999991
5	105.6	0.182574185835053	0.399999999999991
6	106.05	0.129099444873579	0.299999999999997
7	106.875	0.221735578260835	0.5
8	107.5	0.182574185835055	0.400000000000006
9	108.225	0.249999999999997	0.599999999999994
10	109.3025	0.307611768305441	0.730000000000004
11	110.1525	0.255130685466617	0.579999999999998
12	110.83	0.23050668826161	0.52000000000001
13	111.5175	0.213911975666007	0.480000000000004
14	112.0875	0.170758113521240	0.409999999999997
15	112.6425	0.140326999065280	0.310000000000002
16	113.2	0.185652004208592	0.390000000000001
17	113.755	0.108474267301815	0.22999999999999
18	114.2325	0.152178623115513	0.359999999999999
19	115.01	0.230940107675851	0.560000000000002
20	115.6475	0.241850504788942	0.549999999999997
21	116.25	0.201825006709612	0.490000000000009

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 103.775 & 0.170782512765995 & 0.400000000000006 \tabularnewline
2 & 104.15 & 0.129099444873581 & 0.299999999999997 \tabularnewline
3 & 104.575 & 0.149999999999999 & 0.299999999999997 \tabularnewline
4 & 105.1 & 0.182574185835053 & 0.399999999999991 \tabularnewline
5 & 105.6 & 0.182574185835053 & 0.399999999999991 \tabularnewline
6 & 106.05 & 0.129099444873579 & 0.299999999999997 \tabularnewline
7 & 106.875 & 0.221735578260835 & 0.5 \tabularnewline
8 & 107.5 & 0.182574185835055 & 0.400000000000006 \tabularnewline
9 & 108.225 & 0.249999999999997 & 0.599999999999994 \tabularnewline
10 & 109.3025 & 0.307611768305441 & 0.730000000000004 \tabularnewline
11 & 110.1525 & 0.255130685466617 & 0.579999999999998 \tabularnewline
12 & 110.83 & 0.23050668826161 & 0.52000000000001 \tabularnewline
13 & 111.5175 & 0.213911975666007 & 0.480000000000004 \tabularnewline
14 & 112.0875 & 0.170758113521240 & 0.409999999999997 \tabularnewline
15 & 112.6425 & 0.140326999065280 & 0.310000000000002 \tabularnewline
16 & 113.2 & 0.185652004208592 & 0.390000000000001 \tabularnewline
17 & 113.755 & 0.108474267301815 & 0.22999999999999 \tabularnewline
18 & 114.2325 & 0.152178623115513 & 0.359999999999999 \tabularnewline
19 & 115.01 & 0.230940107675851 & 0.560000000000002 \tabularnewline
20 & 115.6475 & 0.241850504788942 & 0.549999999999997 \tabularnewline
21 & 116.25 & 0.201825006709612 & 0.490000000000009 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=12531&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]103.775[/C][C]0.170782512765995[/C][C]0.400000000000006[/C][/ROW]
[ROW][C]2[/C][C]104.15[/C][C]0.129099444873581[/C][C]0.299999999999997[/C][/ROW]
[ROW][C]3[/C][C]104.575[/C][C]0.149999999999999[/C][C]0.299999999999997[/C][/ROW]
[ROW][C]4[/C][C]105.1[/C][C]0.182574185835053[/C][C]0.399999999999991[/C][/ROW]
[ROW][C]5[/C][C]105.6[/C][C]0.182574185835053[/C][C]0.399999999999991[/C][/ROW]
[ROW][C]6[/C][C]106.05[/C][C]0.129099444873579[/C][C]0.299999999999997[/C][/ROW]
[ROW][C]7[/C][C]106.875[/C][C]0.221735578260835[/C][C]0.5[/C][/ROW]
[ROW][C]8[/C][C]107.5[/C][C]0.182574185835055[/C][C]0.400000000000006[/C][/ROW]
[ROW][C]9[/C][C]108.225[/C][C]0.249999999999997[/C][C]0.599999999999994[/C][/ROW]
[ROW][C]10[/C][C]109.3025[/C][C]0.307611768305441[/C][C]0.730000000000004[/C][/ROW]
[ROW][C]11[/C][C]110.1525[/C][C]0.255130685466617[/C][C]0.579999999999998[/C][/ROW]
[ROW][C]12[/C][C]110.83[/C][C]0.23050668826161[/C][C]0.52000000000001[/C][/ROW]
[ROW][C]13[/C][C]111.5175[/C][C]0.213911975666007[/C][C]0.480000000000004[/C][/ROW]
[ROW][C]14[/C][C]112.0875[/C][C]0.170758113521240[/C][C]0.409999999999997[/C][/ROW]
[ROW][C]15[/C][C]112.6425[/C][C]0.140326999065280[/C][C]0.310000000000002[/C][/ROW]
[ROW][C]16[/C][C]113.2[/C][C]0.185652004208592[/C][C]0.390000000000001[/C][/ROW]
[ROW][C]17[/C][C]113.755[/C][C]0.108474267301815[/C][C]0.22999999999999[/C][/ROW]
[ROW][C]18[/C][C]114.2325[/C][C]0.152178623115513[/C][C]0.359999999999999[/C][/ROW]
[ROW][C]19[/C][C]115.01[/C][C]0.230940107675851[/C][C]0.560000000000002[/C][/ROW]
[ROW][C]20[/C][C]115.6475[/C][C]0.241850504788942[/C][C]0.549999999999997[/C][/ROW]
[ROW][C]21[/C][C]116.25[/C][C]0.201825006709612[/C][C]0.490000000000009[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=12531&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=12531&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	103.775	0.170782512765995	0.400000000000006
2	104.15	0.129099444873581	0.299999999999997
3	104.575	0.149999999999999	0.299999999999997
4	105.1	0.182574185835053	0.399999999999991
5	105.6	0.182574185835053	0.399999999999991
6	106.05	0.129099444873579	0.299999999999997
7	106.875	0.221735578260835	0.5
8	107.5	0.182574185835055	0.400000000000006
9	108.225	0.249999999999997	0.599999999999994
10	109.3025	0.307611768305441	0.730000000000004
11	110.1525	0.255130685466617	0.579999999999998
12	110.83	0.23050668826161	0.52000000000001
13	111.5175	0.213911975666007	0.480000000000004
14	112.0875	0.170758113521240	0.409999999999997
15	112.6425	0.140326999065280	0.310000000000002
16	113.2	0.185652004208592	0.390000000000001
17	113.755	0.108474267301815	0.22999999999999
18	114.2325	0.152178623115513	0.359999999999999
19	115.01	0.230940107675851	0.560000000000002
20	115.6475	0.241850504788942	0.549999999999997
21	116.25	0.201825006709612	0.490000000000009

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	-0.0522186888503682
beta	0.00222599125646073
S.D.	0.0027575505533354
T-STAT	0.807234976623828
p-value	0.429521343860915

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -0.0522186888503682 \tabularnewline
beta & 0.00222599125646073 \tabularnewline
S.D. & 0.0027575505533354 \tabularnewline
T-STAT & 0.807234976623828 \tabularnewline
p-value & 0.429521343860915 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=12531&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-0.0522186888503682[/C][/ROW]
[ROW][C]beta[/C][C]0.00222599125646073[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0027575505533354[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.807234976623828[/C][/ROW]
[ROW][C]p-value[/C][C]0.429521343860915[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=12531&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=12531&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	-0.0522186888503682
beta	0.00222599125646073
S.D.	0.0027575505533354
T-STAT	0.807234976623828
p-value	0.429521343860915

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	-7.68965952232052
beta	1.27878783849894
S.D.	1.60447609777903
T-STAT	0.797012707306192
p-value	0.435290919743064
Lambda	-0.278787838498938

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -7.68965952232052 \tabularnewline
beta & 1.27878783849894 \tabularnewline
S.D. & 1.60447609777903 \tabularnewline
T-STAT & 0.797012707306192 \tabularnewline
p-value & 0.435290919743064 \tabularnewline
Lambda & -0.278787838498938 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=12531&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-7.68965952232052[/C][/ROW]
[ROW][C]beta[/C][C]1.27878783849894[/C][/ROW]
[ROW][C]S.D.[/C][C]1.60447609777903[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.797012707306192[/C][/ROW]
[ROW][C]p-value[/C][C]0.435290919743064[/C][/ROW]
[ROW][C]Lambda[/C][C]-0.278787838498938[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=12531&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=12531&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	-7.68965952232052
beta	1.27878783849894
S.D.	1.60447609777903
T-STAT	0.797012707306192
p-value	0.435290919743064
Lambda	-0.278787838498938

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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Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code