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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

Fri, 04 Dec 2009 14:50:37 -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/2009/Dec/04/t1259963500be8qhc9nj9pfzry.htm/, Retrieved Sat, 27 Apr 2024 13:49:10 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=64175, Retrieved Sat, 27 Apr 2024 13:49:10 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

WS 9-2

Estimated Impact

133

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

-     [Univariate Data Series] [data set] [2008-12-01 19:54:57] [b98453cac15ba1066b407e146608df68]
- RMP   [Standard Deviation-Mean Plot] [] [2009-11-27 14:40:44] [b98453cac15ba1066b407e146608df68]
-    D    [Standard Deviation-Mean Plot] [smp] [2009-12-02 20:03:12] [ed603017d2bee8fbd82b6d5ec04e12c3]
-             [Standard Deviation-Mean Plot] [Workshop 9-2] [2009-12-04 21:50:37] [a53416c107f5e7e1e12bb9940270d09d] [Current]

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Dataseries X:

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Histogram

Boxplots

5.7
6.1
6
5.9
5.8
5.7
5.6
5.4
5.4
5.5
5.6
5.7
5.9
6.1
6
5.8
5.8
5.7
5.5
5.3
5.2
5.2
5
5.1
5.1
5.2
4.9
4.8
4.5
4.5
4.4
4.4
4.2
4.1
3.9
3.8
3.9
4.2
4.1
3.8
3.6
3.7
3.5
3.4
3.1
3.1
3.1
3.2
3.3
3.5
3.6
3.5
3.3
3.2
3.1
3.2
3
3
3.1
3.4

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' @ 72.249.127.135

\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' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=64175&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' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=64175&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=64175&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' @ 72.249.127.135

Standard Deviation-Mean Plot
Section	Mean	Standard Deviation	Range
1	5.7	0.221564683762799	0.700
2	5.55	0.380191339387754	1.1
3	4.48333333333333	0.448904390171394	1.4
4	3.55833333333333	0.391868097783688	1.1
5	3.26666666666667	0.201509455376319	0.6

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 5.7 & 0.221564683762799 & 0.700 \tabularnewline
2 & 5.55 & 0.380191339387754 & 1.1 \tabularnewline
3 & 4.48333333333333 & 0.448904390171394 & 1.4 \tabularnewline
4 & 3.55833333333333 & 0.391868097783688 & 1.1 \tabularnewline
5 & 3.26666666666667 & 0.201509455376319 & 0.6 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=64175&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]5.7[/C][C]0.221564683762799[/C][C]0.700[/C][/ROW]
[ROW][C]2[/C][C]5.55[/C][C]0.380191339387754[/C][C]1.1[/C][/ROW]
[ROW][C]3[/C][C]4.48333333333333[/C][C]0.448904390171394[/C][C]1.4[/C][/ROW]
[ROW][C]4[/C][C]3.55833333333333[/C][C]0.391868097783688[/C][C]1.1[/C][/ROW]
[ROW][C]5[/C][C]3.26666666666667[/C][C]0.201509455376319[/C][C]0.6[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=64175&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=64175&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	5.7	0.221564683762799	0.700
2	5.55	0.380191339387754	1.1
3	4.48333333333333	0.448904390171394	1.4
4	3.55833333333333	0.391868097783688	1.1
5	3.26666666666667	0.201509455376319	0.6

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	0.309777360767953
beta	0.00421800499337361
S.D.	0.0572421718397918
T-STAT	0.0736870188150596
p-value	0.945897543145964

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 0.309777360767953 \tabularnewline
beta & 0.00421800499337361 \tabularnewline
S.D. & 0.0572421718397918 \tabularnewline
T-STAT & 0.0736870188150596 \tabularnewline
p-value & 0.945897543145964 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=64175&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]0.309777360767953[/C][/ROW]
[ROW][C]beta[/C][C]0.00421800499337361[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0572421718397918[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.0736870188150596[/C][/ROW]
[ROW][C]p-value[/C][C]0.945897543145964[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=64175&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=64175&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	0.309777360767953
beta	0.00421800499337361
S.D.	0.0572421718397918
T-STAT	0.0736870188150596
p-value	0.945897543145964

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	-1.42956528577274
beta	0.180084505998657
S.D.	0.827031803424656
T-STAT	0.217747981701484
p-value	0.841595244064713
Lambda	0.819915494001343

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -1.42956528577274 \tabularnewline
beta & 0.180084505998657 \tabularnewline
S.D. & 0.827031803424656 \tabularnewline
T-STAT & 0.217747981701484 \tabularnewline
p-value & 0.841595244064713 \tabularnewline
Lambda & 0.819915494001343 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=64175&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-1.42956528577274[/C][/ROW]
[ROW][C]beta[/C][C]0.180084505998657[/C][/ROW]
[ROW][C]S.D.[/C][C]0.827031803424656[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.217747981701484[/C][/ROW]
[ROW][C]p-value[/C][C]0.841595244064713[/C][/ROW]
[ROW][C]Lambda[/C][C]0.819915494001343[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=64175&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=64175&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	-1.42956528577274
beta	0.180084505998657
S.D.	0.827031803424656
T-STAT	0.217747981701484
p-value	0.841595244064713
Lambda	0.819915494001343

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