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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, 06 Jan 2015 12:01:28 +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/2015/Jan/06/t1420545705t7l7hllg6pxi066.htm/, Retrieved Wed, 15 May 2024 21:27:17 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=272000, Retrieved Wed, 15 May 2024 21:27:17 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

144

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

-     [Harrell-Davis Quantiles] [] [2015-01-05 16:01:40] [a8f6a7eeade7f89f597831d453788737]
-    D  [Harrell-Davis Quantiles] [] [2015-01-05 16:10:43] [a8f6a7eeade7f89f597831d453788737]
- RM      [(Partial) Autocorrelation Function] [] [2015-01-06 09:12:41] [a8f6a7eeade7f89f597831d453788737]
- RM D      [Bootstrap Plot - Central Tendency] [] [2015-01-06 09:27:21] [a8f6a7eeade7f89f597831d453788737]
- RM D        [Blocked Bootstrap Plot - Central Tendency] [] [2015-01-06 10:19:09] [a8f6a7eeade7f89f597831d453788737]
- RM              [Standard Deviation-Mean Plot] [] [2015-01-06 12:01:28] [12470bd120139be5e23c611c04d9c0dc] [Current]

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Dataseries X:

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Boxplots

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	1 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 & 1 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=272000&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]1 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=272000&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=272000&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	1 seconds
R Server	'Gwilym Jenkins' @ jenkins.wessa.net

Standard Deviation-Mean Plot
Section	Mean	Standard Deviation	Range
1	385.083333333333	58.3865774321669	202
2	668.416666666667	78.7128940960101	231
3	599	90.6351326623803	283
4	595	66.558245169175	234
5	718	78.2710906808103	242
6	788	86.8373610419344	229

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 385.083333333333 & 58.3865774321669 & 202 \tabularnewline
2 & 668.416666666667 & 78.7128940960101 & 231 \tabularnewline
3 & 599 & 90.6351326623803 & 283 \tabularnewline
4 & 595 & 66.558245169175 & 234 \tabularnewline
5 & 718 & 78.2710906808103 & 242 \tabularnewline
6 & 788 & 86.8373610419344 & 229 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=272000&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]385.083333333333[/C][C]58.3865774321669[/C][C]202[/C][/ROW]
[ROW][C]2[/C][C]668.416666666667[/C][C]78.7128940960101[/C][C]231[/C][/ROW]
[ROW][C]3[/C][C]599[/C][C]90.6351326623803[/C][C]283[/C][/ROW]
[ROW][C]4[/C][C]595[/C][C]66.558245169175[/C][C]234[/C][/ROW]
[ROW][C]5[/C][C]718[/C][C]78.2710906808103[/C][C]242[/C][/ROW]
[ROW][C]6[/C][C]788[/C][C]86.8373610419344[/C][C]229[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=272000&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=272000&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	385.083333333333	58.3865774321669	202
2	668.416666666667	78.7128940960101	231
3	599	90.6351326623803	283
4	595	66.558245169175	234
5	718	78.2710906808103	242
6	788	86.8373610419344	229

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	36.1211361072191
beta	0.0646528531874684
S.D.	0.0296902019198974
T-STAT	2.17758213170454
p-value	0.0950009418254679

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 36.1211361072191 \tabularnewline
beta & 0.0646528531874684 \tabularnewline
S.D. & 0.0296902019198974 \tabularnewline
T-STAT & 2.17758213170454 \tabularnewline
p-value & 0.0950009418254679 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=272000&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]36.1211361072191[/C][/ROW]
[ROW][C]beta[/C][C]0.0646528531874684[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0296902019198974[/C][/ROW]
[ROW][C]T-STAT[/C][C]2.17758213170454[/C][/ROW]
[ROW][C]p-value[/C][C]0.0950009418254679[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=272000&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=272000&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	36.1211361072191
beta	0.0646528531874684
S.D.	0.0296902019198974
T-STAT	2.17758213170454
p-value	0.0950009418254679

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	0.975700767122466
beta	0.522441756173962
S.D.	0.204694840401989
T-STAT	2.55229567656893
p-value	0.0631515011947506
Lambda	0.477558243826038

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 0.975700767122466 \tabularnewline
beta & 0.522441756173962 \tabularnewline
S.D. & 0.204694840401989 \tabularnewline
T-STAT & 2.55229567656893 \tabularnewline
p-value & 0.0631515011947506 \tabularnewline
Lambda & 0.477558243826038 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=272000&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]0.975700767122466[/C][/ROW]
[ROW][C]beta[/C][C]0.522441756173962[/C][/ROW]
[ROW][C]S.D.[/C][C]0.204694840401989[/C][/ROW]
[ROW][C]T-STAT[/C][C]2.55229567656893[/C][/ROW]
[ROW][C]p-value[/C][C]0.0631515011947506[/C][/ROW]
[ROW][C]Lambda[/C][C]0.477558243826038[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=272000&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=272000&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	0.975700767122466
beta	0.522441756173962
S.D.	0.204694840401989
T-STAT	2.55229567656893
p-value	0.0631515011947506
Lambda	0.477558243826038

Figure 1

PNG link

Postscript link

PDF link

Figure 2

PNG link

Postscript link

PDF link

Parameters (Session):

par1 = 0.1 ; par2 = 0.9 ; par3 = 0.1 ;

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