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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, 26 Nov 2012 05:07:40 -0500

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/2012/Nov/26/t13539244826r4l5qseoewodo8.htm/, Retrieved Tue, 30 Apr 2024 03:00:28 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=192929, Retrieved Tue, 30 Apr 2024 03:00:28 +0000

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Original text written by user:

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

-       [Standard Deviation-Mean Plot] [] [2012-11-26 10:07:40] [119350d3baf712453a84eb36ae72814b] [Current]

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Histogram

Boxplots

0.47
0.47
0.47
0.47
0.47
0.47
0.48
0.48
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0.49
0.5
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0.5
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0.51
0.51
0.5
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0.5
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0.55
0.54
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0.54
0.55
0.55
0.55
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0.56
0.56
0.56
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0.56
0.55
0.55
0.55
0.54
0.54
0.54
0.54
0.55
0.54
0.54
0.54

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' @ jenkins.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 & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=192929&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' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=192929&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=192929&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' @ jenkins.wessa.net

Standard Deviation-Mean Plot
Section	Mean	Standard Deviation	Range
1	0.475833333333333	0.00668557923421522	0.02
2	0.495	0.00522232967867094	0.01
3	0.510833333333333	0.0108362466945083	0.03
4	0.5425	0.00866025403784439	0.02
5	0.556666666666667	0.00492365963917331	0.01
6	0.545	0.00674199862463243	0.02

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 0.475833333333333 & 0.00668557923421522 & 0.02 \tabularnewline
2 & 0.495 & 0.00522232967867094 & 0.01 \tabularnewline
3 & 0.510833333333333 & 0.0108362466945083 & 0.03 \tabularnewline
4 & 0.5425 & 0.00866025403784439 & 0.02 \tabularnewline
5 & 0.556666666666667 & 0.00492365963917331 & 0.01 \tabularnewline
6 & 0.545 & 0.00674199862463243 & 0.02 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=192929&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]0.475833333333333[/C][C]0.00668557923421522[/C][C]0.02[/C][/ROW]
[ROW][C]2[/C][C]0.495[/C][C]0.00522232967867094[/C][C]0.01[/C][/ROW]
[ROW][C]3[/C][C]0.510833333333333[/C][C]0.0108362466945083[/C][C]0.03[/C][/ROW]
[ROW][C]4[/C][C]0.5425[/C][C]0.00866025403784439[/C][C]0.02[/C][/ROW]
[ROW][C]5[/C][C]0.556666666666667[/C][C]0.00492365963917331[/C][C]0.01[/C][/ROW]
[ROW][C]6[/C][C]0.545[/C][C]0.00674199862463243[/C][C]0.02[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=192929&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=192929&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	0.475833333333333	0.00668557923421522	0.02
2	0.495	0.00522232967867094	0.01
3	0.510833333333333	0.0108362466945083	0.03
4	0.5425	0.00866025403784439	0.02
5	0.556666666666667	0.00492365963917331	0.01
6	0.545	0.00674199862463243	0.02

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	0.00952477191417963
beta	-0.00450393929385226
S.D.	0.0347760097669949
T-STAT	-0.129512825767804
p-value	0.903203329160929

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 0.00952477191417963 \tabularnewline
beta & -0.00450393929385226 \tabularnewline
S.D. & 0.0347760097669949 \tabularnewline
T-STAT & -0.129512825767804 \tabularnewline
p-value & 0.903203329160929 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=192929&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]0.00952477191417963[/C][/ROW]
[ROW][C]beta[/C][C]-0.00450393929385226[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0347760097669949[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.129512825767804[/C][/ROW]
[ROW][C]p-value[/C][C]0.903203329160929[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=192929&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=192929&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	0.00952477191417963
beta	-0.00450393929385226
S.D.	0.0347760097669949
T-STAT	-0.129512825767804
p-value	0.903203329160929

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	-5.17713883568288
beta	-0.309350088885541
S.D.	2.40727788842017
T-STAT	-0.128506181348493
p-value	0.903950515812066
Lambda	1.30935008888554

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -5.17713883568288 \tabularnewline
beta & -0.309350088885541 \tabularnewline
S.D. & 2.40727788842017 \tabularnewline
T-STAT & -0.128506181348493 \tabularnewline
p-value & 0.903950515812066 \tabularnewline
Lambda & 1.30935008888554 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=192929&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-5.17713883568288[/C][/ROW]
[ROW][C]beta[/C][C]-0.309350088885541[/C][/ROW]
[ROW][C]S.D.[/C][C]2.40727788842017[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.128506181348493[/C][/ROW]
[ROW][C]p-value[/C][C]0.903950515812066[/C][/ROW]
[ROW][C]Lambda[/C][C]1.30935008888554[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=192929&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=192929&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	-5.17713883568288
beta	-0.309350088885541
S.D.	2.40727788842017
T-STAT	-0.128506181348493
p-value	0.903950515812066
Lambda	1.30935008888554

Figure 1

PNG link

Postscript link

PDF link

Figure 2

PNG link

Postscript link

PDF link

Parameters (Session):

par1 = 12 ;

Parameters (R input):

par1 = 12 ;

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')

Free Statistics

Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code