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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

Thu, 20 Nov 2014 17:07:48 +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/2014/Nov/20/t1416503288dx9wpghpl72x8yn.htm/, Retrieved Sun, 19 May 2024 13:08:24 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=257322, Retrieved Sun, 19 May 2024 13:08:24 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

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

-       [Standard Deviation-Mean Plot] [Standard Deviatio...] [2014-11-20 17:07:48] [8ab2f7883acfec92c4c89513940c9803] [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	1 seconds
R Server	'Sir Ronald Aylmer Fisher' @ fisher.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 & 'Sir Ronald Aylmer Fisher' @ fisher.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=257322&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]'Sir Ronald Aylmer Fisher' @ fisher.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=257322&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=257322&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	'Sir Ronald Aylmer Fisher' @ fisher.wessa.net

Standard Deviation-Mean Plot
Section	Mean	Standard Deviation	Range
1	711.916666666667	103.520273230401	313
2	634.416666666667	105.514719639518	320
3	636.583333333333	98.2810980932969	290
4	571.5	58.9290791005287	204
5	523.666666666667	55.8005104788206	188
6	460.083333333333	81.2431349081076	223

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 711.916666666667 & 103.520273230401 & 313 \tabularnewline
2 & 634.416666666667 & 105.514719639518 & 320 \tabularnewline
3 & 636.583333333333 & 98.2810980932969 & 290 \tabularnewline
4 & 571.5 & 58.9290791005287 & 204 \tabularnewline
5 & 523.666666666667 & 55.8005104788206 & 188 \tabularnewline
6 & 460.083333333333 & 81.2431349081076 & 223 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=257322&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]711.916666666667[/C][C]103.520273230401[/C][C]313[/C][/ROW]
[ROW][C]2[/C][C]634.416666666667[/C][C]105.514719639518[/C][C]320[/C][/ROW]
[ROW][C]3[/C][C]636.583333333333[/C][C]98.2810980932969[/C][C]290[/C][/ROW]
[ROW][C]4[/C][C]571.5[/C][C]58.9290791005287[/C][C]204[/C][/ROW]
[ROW][C]5[/C][C]523.666666666667[/C][C]55.8005104788206[/C][C]188[/C][/ROW]
[ROW][C]6[/C][C]460.083333333333[/C][C]81.2431349081076[/C][C]223[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=257322&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=257322&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	711.916666666667	103.520273230401	313
2	634.416666666667	105.514719639518	320
3	636.583333333333	98.2810980932969	290
4	571.5	58.9290791005287	204
5	523.666666666667	55.8005104788206	188
6	460.083333333333	81.2431349081076	223

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	-13.2678012664162
beta	0.164745100489661
S.D.	0.092035105097142
T-STAT	1.7900245815526
p-value	0.147946393154017

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -13.2678012664162 \tabularnewline
beta & 0.164745100489661 \tabularnewline
S.D. & 0.092035105097142 \tabularnewline
T-STAT & 1.7900245815526 \tabularnewline
p-value & 0.147946393154017 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=257322&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-13.2678012664162[/C][/ROW]
[ROW][C]beta[/C][C]0.164745100489661[/C][/ROW]
[ROW][C]S.D.[/C][C]0.092035105097142[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.7900245815526[/C][/ROW]
[ROW][C]p-value[/C][C]0.147946393154017[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=257322&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=257322&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	-13.2678012664162
beta	0.164745100489661
S.D.	0.092035105097142
T-STAT	1.7900245815526
p-value	0.147946393154017

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	-2.55422543302815
beta	1.09132135937086
S.D.	0.729539548568608
T-STAT	1.4959043159649
p-value	0.209009032250837
Lambda	-0.0913213593708633

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -2.55422543302815 \tabularnewline
beta & 1.09132135937086 \tabularnewline
S.D. & 0.729539548568608 \tabularnewline
T-STAT & 1.4959043159649 \tabularnewline
p-value & 0.209009032250837 \tabularnewline
Lambda & -0.0913213593708633 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=257322&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-2.55422543302815[/C][/ROW]
[ROW][C]beta[/C][C]1.09132135937086[/C][/ROW]
[ROW][C]S.D.[/C][C]0.729539548568608[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.4959043159649[/C][/ROW]
[ROW][C]p-value[/C][C]0.209009032250837[/C][/ROW]
[ROW][C]Lambda[/C][C]-0.0913213593708633[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=257322&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=257322&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	-2.55422543302815
beta	1.09132135937086
S.D.	0.729539548568608
T-STAT	1.4959043159649
p-value	0.209009032250837
Lambda	-0.0913213593708633

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