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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, 27 Nov 2007 13:21:40 -0700

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/2007/Nov/27/t1196194325dr78dh1yuu6pgms.htm/, Retrieved Sun, 05 May 2024 17:59:57 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=6945, Retrieved Sun, 05 May 2024 17:59:57 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

180

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

-       [Standard Deviation-Mean Plot] [Standard deviatio...] [2007-11-27 20:21:40] [bebbf4ab6ac77d61a56e6916ab0650f9] [Current]

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Dataseries X:

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Histogram

Boxplots

1.48
1.48
1.48
1.48
1.48
1.48
1.48
1.48
1.48
1.48
1.48
1.57
1.58
1.58
1.58
1.58
1.59
1.60
1.60
1.61
1.61
1.61
1.62
1.63
1.63
1.64
1.64
1.64
1.64
1.64
1.65
1.65
1.65
1.65
1.65
1.66
1.66
1.67
1.68
1.68
1.68
1.68
1.69
1.70
1.70
1.71
1.72
1.73
1.74
1.74
1.75
1.75
1.75

Summary of compuational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	2 seconds
R Server	'Herman Ole Andreas Wold' @ 193.190.124.10:1001

\begin{tabular}{lllllllll}
\hline
Summary of compuational 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 & 'Herman Ole Andreas Wold' @ 193.190.124.10:1001 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=6945&T=0

[TABLE]
[ROW][C]Summary of compuational 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]'Herman Ole Andreas Wold' @ 193.190.124.10:1001[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=6945&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6945&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 compuational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	2 seconds
R Server	'Herman Ole Andreas Wold' @ 193.190.124.10:1001

Standard Deviation-Mean Plot
Section	Mean	Standard Deviation	Range
1	1.4875	0.0259807621135332	0.09
2	1.59916666666667	0.0172986249234563	0.15
3	1.645	0.00797724035217466	0.18
4	1.69166666666667	0.0208166599946613	0.25

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 1.4875 & 0.0259807621135332 & 0.09 \tabularnewline
2 & 1.59916666666667 & 0.0172986249234563 & 0.15 \tabularnewline
3 & 1.645 & 0.00797724035217466 & 0.18 \tabularnewline
4 & 1.69166666666667 & 0.0208166599946613 & 0.25 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=6945&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]1.4875[/C][C]0.0259807621135332[/C][C]0.09[/C][/ROW]
[ROW][C]2[/C][C]1.59916666666667[/C][C]0.0172986249234563[/C][C]0.15[/C][/ROW]
[ROW][C]3[/C][C]1.645[/C][C]0.00797724035217466[/C][C]0.18[/C][/ROW]
[ROW][C]4[/C][C]1.69166666666667[/C][C]0.0208166599946613[/C][C]0.25[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=6945&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6945&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	1.4875	0.0259807621135332	0.09
2	1.59916666666667	0.0172986249234563	0.15
3	1.645	0.00797724035217466	0.18
4	1.69166666666667	0.0208166599946613	0.25

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	0.0943269004375577
beta	-0.0475196130305768
S.D.	0.0512924821266721
T-STAT	-0.926444014021826
p-value	0.452019141987865

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 0.0943269004375577 \tabularnewline
beta & -0.0475196130305768 \tabularnewline
S.D. & 0.0512924821266721 \tabularnewline
T-STAT & -0.926444014021826 \tabularnewline
p-value & 0.452019141987865 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=6945&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]0.0943269004375577[/C][/ROW]
[ROW][C]beta[/C][C]-0.0475196130305768[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0512924821266721[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.926444014021826[/C][/ROW]
[ROW][C]p-value[/C][C]0.452019141987865[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=6945&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6945&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	0.0943269004375577
beta	-0.0475196130305768
S.D.	0.0512924821266721
T-STAT	-0.926444014021826
p-value	0.452019141987865

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	-2.02193559497214
beta	-4.40359729253263
S.D.	5.78262101536419
T-STAT	-0.761522721415161
p-value	0.525889022651221
Lambda	5.40359729253263

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -2.02193559497214 \tabularnewline
beta & -4.40359729253263 \tabularnewline
S.D. & 5.78262101536419 \tabularnewline
T-STAT & -0.761522721415161 \tabularnewline
p-value & 0.525889022651221 \tabularnewline
Lambda & 5.40359729253263 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=6945&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-2.02193559497214[/C][/ROW]
[ROW][C]beta[/C][C]-4.40359729253263[/C][/ROW]
[ROW][C]S.D.[/C][C]5.78262101536419[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.761522721415161[/C][/ROW]
[ROW][C]p-value[/C][C]0.525889022651221[/C][/ROW]
[ROW][C]Lambda[/C][C]5.40359729253263[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=6945&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6945&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	-2.02193559497214
beta	-4.40359729253263
S.D.	5.78262101536419
T-STAT	-0.761522721415161
p-value	0.525889022651221
Lambda	5.40359729253263

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