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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

Sat, 26 Dec 2009 06:47:50 -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/26/t1261835354486ph31voenmlzk.htm/, Retrieved Sun, 28 Apr 2024 21:47:44 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=70744, Retrieved Sun, 28 Apr 2024 21:47:44 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

176

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

-     [Univariate Data Series] [Paper] [2009-12-21 20:42:12] [0df1a6455bedfaf424729b1e006090d0]
- RMPD    [Standard Deviation-Mean Plot] [paper SD-MP] [2009-12-26 13:47:50] [e2f800c9186517d2e5c4a809848912a7] [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	4 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 & 4 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=70744&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]4 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=70744&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=70744&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	4 seconds
R Server	'Gwilym Jenkins' @ 72.249.127.135

Standard Deviation-Mean Plot
Section	Mean	Standard Deviation	Range
1	1.23765	0.031355222850428	0.0661
2	1.214675	0.0107521703235517	0.0258999999999998
3	1.277675	0.0528774290222208	0.119
4	1.3068	0.0115622950432285	0.0263
5	1.2297	0.0284404641312339	0.0657000000000001
6	1.197825	0.0208487209839517	0.0469999999999999
7	1.2083	0.0142288439446078	0.0333000000000001
8	1.272875	0.00745447293017196	0.0161
9	1.2858	0.0261230421913936	0.0601999999999998
10	1.320775	0.0229242775240573	0.0516999999999999
11	1.3567	0.0129442393879800	0.0296999999999998
12	1.434425	0.0356402745032452	0.0788
13	1.5186	0.0531154089381477	0.1033
14	1.546375	0.0341236355038556	0.0794999999999999
15	1.346825	0.0677489667817894	0.1638

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 1.23765 & 0.031355222850428 & 0.0661 \tabularnewline
2 & 1.214675 & 0.0107521703235517 & 0.0258999999999998 \tabularnewline
3 & 1.277675 & 0.0528774290222208 & 0.119 \tabularnewline
4 & 1.3068 & 0.0115622950432285 & 0.0263 \tabularnewline
5 & 1.2297 & 0.0284404641312339 & 0.0657000000000001 \tabularnewline
6 & 1.197825 & 0.0208487209839517 & 0.0469999999999999 \tabularnewline
7 & 1.2083 & 0.0142288439446078 & 0.0333000000000001 \tabularnewline
8 & 1.272875 & 0.00745447293017196 & 0.0161 \tabularnewline
9 & 1.2858 & 0.0261230421913936 & 0.0601999999999998 \tabularnewline
10 & 1.320775 & 0.0229242775240573 & 0.0516999999999999 \tabularnewline
11 & 1.3567 & 0.0129442393879800 & 0.0296999999999998 \tabularnewline
12 & 1.434425 & 0.0356402745032452 & 0.0788 \tabularnewline
13 & 1.5186 & 0.0531154089381477 & 0.1033 \tabularnewline
14 & 1.546375 & 0.0341236355038556 & 0.0794999999999999 \tabularnewline
15 & 1.346825 & 0.0677489667817894 & 0.1638 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=70744&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]1.23765[/C][C]0.031355222850428[/C][C]0.0661[/C][/ROW]
[ROW][C]2[/C][C]1.214675[/C][C]0.0107521703235517[/C][C]0.0258999999999998[/C][/ROW]
[ROW][C]3[/C][C]1.277675[/C][C]0.0528774290222208[/C][C]0.119[/C][/ROW]
[ROW][C]4[/C][C]1.3068[/C][C]0.0115622950432285[/C][C]0.0263[/C][/ROW]
[ROW][C]5[/C][C]1.2297[/C][C]0.0284404641312339[/C][C]0.0657000000000001[/C][/ROW]
[ROW][C]6[/C][C]1.197825[/C][C]0.0208487209839517[/C][C]0.0469999999999999[/C][/ROW]
[ROW][C]7[/C][C]1.2083[/C][C]0.0142288439446078[/C][C]0.0333000000000001[/C][/ROW]
[ROW][C]8[/C][C]1.272875[/C][C]0.00745447293017196[/C][C]0.0161[/C][/ROW]
[ROW][C]9[/C][C]1.2858[/C][C]0.0261230421913936[/C][C]0.0601999999999998[/C][/ROW]
[ROW][C]10[/C][C]1.320775[/C][C]0.0229242775240573[/C][C]0.0516999999999999[/C][/ROW]
[ROW][C]11[/C][C]1.3567[/C][C]0.0129442393879800[/C][C]0.0296999999999998[/C][/ROW]
[ROW][C]12[/C][C]1.434425[/C][C]0.0356402745032452[/C][C]0.0788[/C][/ROW]
[ROW][C]13[/C][C]1.5186[/C][C]0.0531154089381477[/C][C]0.1033[/C][/ROW]
[ROW][C]14[/C][C]1.546375[/C][C]0.0341236355038556[/C][C]0.0794999999999999[/C][/ROW]
[ROW][C]15[/C][C]1.346825[/C][C]0.0677489667817894[/C][C]0.1638[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=70744&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=70744&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	1.23765	0.031355222850428	0.0661
2	1.214675	0.0107521703235517	0.0258999999999998
3	1.277675	0.0528774290222208	0.119
4	1.3068	0.0115622950432285	0.0263
5	1.2297	0.0284404641312339	0.0657000000000001
6	1.197825	0.0208487209839517	0.0469999999999999
7	1.2083	0.0142288439446078	0.0333000000000001
8	1.272875	0.00745447293017196	0.0161
9	1.2858	0.0261230421913936	0.0601999999999998
10	1.320775	0.0229242775240573	0.0516999999999999
11	1.3567	0.0129442393879800	0.0296999999999998
12	1.434425	0.0356402745032452	0.0788
13	1.5186	0.0531154089381477	0.1033
14	1.546375	0.0341236355038556	0.0794999999999999
15	1.346825	0.0677489667817894	0.1638

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	-0.0665758602735476
beta	0.0723248477936258
S.D.	0.0407789195799576
T-STAT	1.77358420817928
p-value	0.0995438742226366

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -0.0665758602735476 \tabularnewline
beta & 0.0723248477936258 \tabularnewline
S.D. & 0.0407789195799576 \tabularnewline
T-STAT & 1.77358420817928 \tabularnewline
p-value & 0.0995438742226366 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=70744&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-0.0665758602735476[/C][/ROW]
[ROW][C]beta[/C][C]0.0723248477936258[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0407789195799576[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.77358420817928[/C][/ROW]
[ROW][C]p-value[/C][C]0.0995438742226366[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=70744&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=70744&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	-0.0665758602735476
beta	0.0723248477936258
S.D.	0.0407789195799576
T-STAT	1.77358420817928
p-value	0.0995438742226366

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	-4.72702933607777
beta	3.62841708456887
S.D.	2.03216506104792
T-STAT	1.78549329191685
p-value	0.0975174872300828
Lambda	-2.62841708456887

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -4.72702933607777 \tabularnewline
beta & 3.62841708456887 \tabularnewline
S.D. & 2.03216506104792 \tabularnewline
T-STAT & 1.78549329191685 \tabularnewline
p-value & 0.0975174872300828 \tabularnewline
Lambda & -2.62841708456887 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=70744&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-4.72702933607777[/C][/ROW]
[ROW][C]beta[/C][C]3.62841708456887[/C][/ROW]
[ROW][C]S.D.[/C][C]2.03216506104792[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.78549329191685[/C][/ROW]
[ROW][C]p-value[/C][C]0.0975174872300828[/C][/ROW]
[ROW][C]Lambda[/C][C]-2.62841708456887[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=70744&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=70744&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	-4.72702933607777
beta	3.62841708456887
S.D.	2.03216506104792
T-STAT	1.78549329191685
p-value	0.0975174872300828
Lambda	-2.62841708456887

Figure 1

PNG link

Postscript link

PDF link

Figure 2

PNG link

Postscript link

PDF link

Parameters (Session):

par1 = 4 ;

Parameters (R input):

par1 = 4 ;

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')

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Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code