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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

Wed, 07 Dec 2011 15:51:51 -0500

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/2011/Dec/07/t13232911562bgadazn98zcky8.htm/, Retrieved Thu, 02 May 2024 20:59:48 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=152719, Retrieved Thu, 02 May 2024 20:59:48 +0000

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IsPrivate?

No (this computation is public)

User-defined keywords

KDGP2W83

Estimated Impact

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

-       [Standard Deviation-Mean Plot] [] [2011-12-07 20:51:51] [860f1af8dde2fbc4c0f468abef92388b] [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	'Gwilym Jenkins' @ jenkins.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 & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=152719&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' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=152719&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=152719&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' @ jenkins.wessa.net

Standard Deviation-Mean Plot
Section	Mean	Standard Deviation	Range
1	99.9833333333333	0.45293654649577	1.5
2	102.85	0.851202358164881	3
3	105.341666666667	0.889799092066531	3
4	107.5	0.648074069840785	1.8
5	109.216666666667	0.560573299616048	2
6	110.808333333333	0.88877682374387	2.7
7	111.825	0.502945867320279	1.80000000000001
8	114.458333333333	0.920926740086344	3
9	117.675	1.62934733168614	5
10	124.391666666667	2.50434470954827	8.10000000000001
11	125.016666666667	1.90732241319573	6.5

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 99.9833333333333 & 0.45293654649577 & 1.5 \tabularnewline
2 & 102.85 & 0.851202358164881 & 3 \tabularnewline
3 & 105.341666666667 & 0.889799092066531 & 3 \tabularnewline
4 & 107.5 & 0.648074069840785 & 1.8 \tabularnewline
5 & 109.216666666667 & 0.560573299616048 & 2 \tabularnewline
6 & 110.808333333333 & 0.88877682374387 & 2.7 \tabularnewline
7 & 111.825 & 0.502945867320279 & 1.80000000000001 \tabularnewline
8 & 114.458333333333 & 0.920926740086344 & 3 \tabularnewline
9 & 117.675 & 1.62934733168614 & 5 \tabularnewline
10 & 124.391666666667 & 2.50434470954827 & 8.10000000000001 \tabularnewline
11 & 125.016666666667 & 1.90732241319573 & 6.5 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=152719&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]99.9833333333333[/C][C]0.45293654649577[/C][C]1.5[/C][/ROW]
[ROW][C]2[/C][C]102.85[/C][C]0.851202358164881[/C][C]3[/C][/ROW]
[ROW][C]3[/C][C]105.341666666667[/C][C]0.889799092066531[/C][C]3[/C][/ROW]
[ROW][C]4[/C][C]107.5[/C][C]0.648074069840785[/C][C]1.8[/C][/ROW]
[ROW][C]5[/C][C]109.216666666667[/C][C]0.560573299616048[/C][C]2[/C][/ROW]
[ROW][C]6[/C][C]110.808333333333[/C][C]0.88877682374387[/C][C]2.7[/C][/ROW]
[ROW][C]7[/C][C]111.825[/C][C]0.502945867320279[/C][C]1.80000000000001[/C][/ROW]
[ROW][C]8[/C][C]114.458333333333[/C][C]0.920926740086344[/C][C]3[/C][/ROW]
[ROW][C]9[/C][C]117.675[/C][C]1.62934733168614[/C][C]5[/C][/ROW]
[ROW][C]10[/C][C]124.391666666667[/C][C]2.50434470954827[/C][C]8.10000000000001[/C][/ROW]
[ROW][C]11[/C][C]125.016666666667[/C][C]1.90732241319573[/C][C]6.5[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=152719&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=152719&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	99.9833333333333	0.45293654649577	1.5
2	102.85	0.851202358164881	3
3	105.341666666667	0.889799092066531	3
4	107.5	0.648074069840785	1.8
5	109.216666666667	0.560573299616048	2
6	110.808333333333	0.88877682374387	2.7
7	111.825	0.502945867320279	1.80000000000001
8	114.458333333333	0.920926740086344	3
9	117.675	1.62934733168614	5
10	124.391666666667	2.50434470954827	8.10000000000001
11	125.016666666667	1.90732241319573	6.5

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	-6.64476262545216
beta	0.069035016922113
S.D.	0.014128131804118
T-STAT	4.88635142135289
p-value	0.000863767932252937

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -6.64476262545216 \tabularnewline
beta & 0.069035016922113 \tabularnewline
S.D. & 0.014128131804118 \tabularnewline
T-STAT & 4.88635142135289 \tabularnewline
p-value & 0.000863767932252937 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=152719&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-6.64476262545216[/C][/ROW]
[ROW][C]beta[/C][C]0.069035016922113[/C][/ROW]
[ROW][C]S.D.[/C][C]0.014128131804118[/C][/ROW]
[ROW][C]T-STAT[/C][C]4.88635142135289[/C][/ROW]
[ROW][C]p-value[/C][C]0.000863767932252937[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=152719&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=152719&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	-6.64476262545216
beta	0.069035016922113
S.D.	0.014128131804118
T-STAT	4.88635142135289
p-value	0.000863767932252937

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	-30.0098167547634
beta	6.3487590407113
S.D.	1.46369049187331
T-STAT	4.33750104681338
p-value	0.001884330990408
Lambda	-5.3487590407113

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -30.0098167547634 \tabularnewline
beta & 6.3487590407113 \tabularnewline
S.D. & 1.46369049187331 \tabularnewline
T-STAT & 4.33750104681338 \tabularnewline
p-value & 0.001884330990408 \tabularnewline
Lambda & -5.3487590407113 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=152719&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-30.0098167547634[/C][/ROW]
[ROW][C]beta[/C][C]6.3487590407113[/C][/ROW]
[ROW][C]S.D.[/C][C]1.46369049187331[/C][/ROW]
[ROW][C]T-STAT[/C][C]4.33750104681338[/C][/ROW]
[ROW][C]p-value[/C][C]0.001884330990408[/C][/ROW]
[ROW][C]Lambda[/C][C]-5.3487590407113[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=152719&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=152719&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	-30.0098167547634
beta	6.3487590407113
S.D.	1.46369049187331
T-STAT	4.33750104681338
p-value	0.001884330990408
Lambda	-5.3487590407113

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')

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Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code