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Author's title

Author

*The author of this computation has been verified*

R Software Module

rwasp_smp.wasp

Title produced by software

Standard Deviation-Mean Plot

Date of computation

Thu, 11 Dec 2008 06:40:20 -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/2008/Dec/11/t12290028860qx2n228zt4o8bj.htm/, Retrieved Sun, 19 May 2024 04:01:25 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=32226, Retrieved Sun, 19 May 2024 04:01:25 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

paper vrouw

Estimated Impact

178

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

F     [Law of Averages] [Random Walk Simul...] [2008-11-25 17:50:19] [b98453cac15ba1066b407e146608df68]
F       [Law of Averages] [Law of Averages] [2008-11-30 14:45:18] [415d0222c17b651a9576eaac006f530d]
- RMPD      [Standard Deviation-Mean Plot] [standard deviatio...] [2008-12-11 13:40:20] [bb7e3816cefc365f4d7adcd50784b783] [Current]

Feedback Forum

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Dataseries X:

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Histogram

Boxplots

9,9
9,8
9,4
8,3
8
8,5
10,4
11,1
10,9
9,9
9,2
9,2
9,5
9,6
9,5
9,1
8,9
9
10,1
10,3
10,2
9,6
9,2
9,3
9,4
9,4
9,2
9
9
9
9,8
10
9,9
9,3
9
9
9,1
9,1
9,1
9,2
8,8
8,3
8,4
8,1
7,8
7,9
7,9
8

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	3 seconds
R Server	'Sir Ronald Aylmer Fisher' @ 193.190.124.24

\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 & 3 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=32226&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]3 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=32226&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=32226&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	3 seconds
R Server	'Sir Ronald Aylmer Fisher' @ 193.190.124.24

Standard Deviation-Mean Plot
Section	Mean	Standard Deviation	Range
1	9.55	0.981186665587783	3.1
2	9.525	0.467342584095534	1.4
3	9.33333333333333	0.377391365063170	1
4	8.475	0.549586621512437	1.4

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 9.55 & 0.981186665587783 & 3.1 \tabularnewline
2 & 9.525 & 0.467342584095534 & 1.4 \tabularnewline
3 & 9.33333333333333 & 0.377391365063170 & 1 \tabularnewline
4 & 8.475 & 0.549586621512437 & 1.4 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=32226&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]9.55[/C][C]0.981186665587783[/C][C]3.1[/C][/ROW]
[ROW][C]2[/C][C]9.525[/C][C]0.467342584095534[/C][C]1.4[/C][/ROW]
[ROW][C]3[/C][C]9.33333333333333[/C][C]0.377391365063170[/C][C]1[/C][/ROW]
[ROW][C]4[/C][C]8.475[/C][C]0.549586621512437[/C][C]1.4[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=32226&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=32226&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	9.55	0.981186665587783	3.1
2	9.525	0.467342584095534	1.4
3	9.33333333333333	0.377391365063170	1
4	8.475	0.549586621512437	1.4

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	-0.576174163799435
beta	0.126892107314686
S.D.	0.362626880038769
T-STAT	0.349924714078338
p-value	0.759809316475172

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -0.576174163799435 \tabularnewline
beta & 0.126892107314686 \tabularnewline
S.D. & 0.362626880038769 \tabularnewline
T-STAT & 0.349924714078338 \tabularnewline
p-value & 0.759809316475172 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=32226&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-0.576174163799435[/C][/ROW]
[ROW][C]beta[/C][C]0.126892107314686[/C][/ROW]
[ROW][C]S.D.[/C][C]0.362626880038769[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.349924714078338[/C][/ROW]
[ROW][C]p-value[/C][C]0.759809316475172[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=32226&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=32226&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	-0.576174163799435
beta	0.126892107314686
S.D.	0.362626880038769
T-STAT	0.349924714078338
p-value	0.759809316475172

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	-3.04590310647212
beta	1.10693313878255
S.D.	5.07500185768903
T-STAT	0.218114824353307
p-value	0.847571781973149
Lambda	-0.106933138782549

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -3.04590310647212 \tabularnewline
beta & 1.10693313878255 \tabularnewline
S.D. & 5.07500185768903 \tabularnewline
T-STAT & 0.218114824353307 \tabularnewline
p-value & 0.847571781973149 \tabularnewline
Lambda & -0.106933138782549 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=32226&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-3.04590310647212[/C][/ROW]
[ROW][C]beta[/C][C]1.10693313878255[/C][/ROW]
[ROW][C]S.D.[/C][C]5.07500185768903[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.218114824353307[/C][/ROW]
[ROW][C]p-value[/C][C]0.847571781973149[/C][/ROW]
[ROW][C]Lambda[/C][C]-0.106933138782549[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=32226&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=32226&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	-3.04590310647212
beta	1.10693313878255
S.D.	5.07500185768903
T-STAT	0.218114824353307
p-value	0.847571781973149
Lambda	-0.106933138782549

Figure 1

PNG link

Postscript link

PDF link

Figure 2

PNG link

Postscript link

PDF link

Parameters (Session):

par1 = 1 ; par2 = 1 ; par3 = 1 ; par4 = 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