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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, 27 Nov 2009 13:26:31 -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/Nov/27/t1259353641ijnxog4y37ef4x6.htm/, Retrieved Sun, 28 Apr 2024 21:18:37 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=61257, Retrieved Sun, 28 Apr 2024 21:18:37 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

101

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

-       [Standard Deviation-Mean Plot] [Mean plot] [2009-11-27 20:26:31] [4c76f32a7a0cc9034048c3cdcdaf547e] [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	0 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 & 0 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=61257&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]0 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=61257&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=61257&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	0 seconds
R Server	'Gwilym Jenkins' @ 72.249.127.135

Standard Deviation-Mean Plot
Section	Mean	Standard Deviation	Range
1	101.375	9.32251673003691	33.2
2	104.708333333333	8.4883297782451	30.1
3	108.8	7.64781608755669	26.3
4	109.966666666667	7.79397591772393	26.4
5	97.8166666666667	10.3226875758147	34.2

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 101.375 & 9.32251673003691 & 33.2 \tabularnewline
2 & 104.708333333333 & 8.4883297782451 & 30.1 \tabularnewline
3 & 108.8 & 7.64781608755669 & 26.3 \tabularnewline
4 & 109.966666666667 & 7.79397591772393 & 26.4 \tabularnewline
5 & 97.8166666666667 & 10.3226875758147 & 34.2 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=61257&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]101.375[/C][C]9.32251673003691[/C][C]33.2[/C][/ROW]
[ROW][C]2[/C][C]104.708333333333[/C][C]8.4883297782451[/C][C]30.1[/C][/ROW]
[ROW][C]3[/C][C]108.8[/C][C]7.64781608755669[/C][C]26.3[/C][/ROW]
[ROW][C]4[/C][C]109.966666666667[/C][C]7.79397591772393[/C][C]26.4[/C][/ROW]
[ROW][C]5[/C][C]97.8166666666667[/C][C]10.3226875758147[/C][C]34.2[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=61257&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=61257&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	101.375	9.32251673003691	33.2
2	104.708333333333	8.4883297782451	30.1
3	108.8	7.64781608755669	26.3
4	109.966666666667	7.79397591772393	26.4
5	97.8166666666667	10.3226875758147	34.2

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	31.3956712282742
beta	-0.216970083007641
S.D.	0.0221047183652757
T-STAT	-9.81555518700833
p-value	0.00224766689764873

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 31.3956712282742 \tabularnewline
beta & -0.216970083007641 \tabularnewline
S.D. & 0.0221047183652757 \tabularnewline
T-STAT & -9.81555518700833 \tabularnewline
p-value & 0.00224766689764873 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=61257&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]31.3956712282742[/C][/ROW]
[ROW][C]beta[/C][C]-0.216970083007641[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0221047183652757[/C][/ROW]
[ROW][C]T-STAT[/C][C]-9.81555518700833[/C][/ROW]
[ROW][C]p-value[/C][C]0.00224766689764873[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=61257&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=61257&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	31.3956712282742
beta	-0.216970083007641
S.D.	0.0221047183652757
T-STAT	-9.81555518700833
p-value	0.00224766689764873

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	14.0123312548997
beta	-2.54997007684601
S.D.	0.216827233212426
T-STAT	-11.7603773246869
p-value	0.00132134631474521
Lambda	3.54997007684601

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 14.0123312548997 \tabularnewline
beta & -2.54997007684601 \tabularnewline
S.D. & 0.216827233212426 \tabularnewline
T-STAT & -11.7603773246869 \tabularnewline
p-value & 0.00132134631474521 \tabularnewline
Lambda & 3.54997007684601 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=61257&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]14.0123312548997[/C][/ROW]
[ROW][C]beta[/C][C]-2.54997007684601[/C][/ROW]
[ROW][C]S.D.[/C][C]0.216827233212426[/C][/ROW]
[ROW][C]T-STAT[/C][C]-11.7603773246869[/C][/ROW]
[ROW][C]p-value[/C][C]0.00132134631474521[/C][/ROW]
[ROW][C]Lambda[/C][C]3.54997007684601[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=61257&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=61257&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	14.0123312548997
beta	-2.54997007684601
S.D.	0.216827233212426
T-STAT	-11.7603773246869
p-value	0.00132134631474521
Lambda	3.54997007684601

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

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Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code