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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

Mon, 21 Dec 2009 03:12:11 -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/21/t12613903932ovn8np7vg2zc2r.htm/, Retrieved Sun, 05 May 2024 17:02:08 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=70085, Retrieved Sun, 05 May 2024 17:02:08 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

137

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

-       [Standard Deviation-Mean Plot] [Standard Deviatio...] [2009-12-21 10:12:11] [f340d7563d07b81b9aae66c73f3e92ac] [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	2 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 & 2 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=70085&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]2 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=70085&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=70085&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	2 seconds
R Server	'Gwilym Jenkins' @ 72.249.127.135

Standard Deviation-Mean Plot
Section	Mean	Standard Deviation	Range
1	540.25	31.340142715925	95
2	507.166666666667	20.4931622003462	65
3	545.916666666667	25.2387088465798	89
4	596.083333333333	19.4303339854949	53
5	595.916666666667	21.9191005677005	62

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 540.25 & 31.340142715925 & 95 \tabularnewline
2 & 507.166666666667 & 20.4931622003462 & 65 \tabularnewline
3 & 545.916666666667 & 25.2387088465798 & 89 \tabularnewline
4 & 596.083333333333 & 19.4303339854949 & 53 \tabularnewline
5 & 595.916666666667 & 21.9191005677005 & 62 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=70085&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]540.25[/C][C]31.340142715925[/C][C]95[/C][/ROW]
[ROW][C]2[/C][C]507.166666666667[/C][C]20.4931622003462[/C][C]65[/C][/ROW]
[ROW][C]3[/C][C]545.916666666667[/C][C]25.2387088465798[/C][C]89[/C][/ROW]
[ROW][C]4[/C][C]596.083333333333[/C][C]19.4303339854949[/C][C]53[/C][/ROW]
[ROW][C]5[/C][C]595.916666666667[/C][C]21.9191005677005[/C][C]62[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=70085&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=70085&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	540.25	31.340142715925	95
2	507.166666666667	20.4931622003462	65
3	545.916666666667	25.2387088465798	89
4	596.083333333333	19.4303339854949	53
5	595.916666666667	21.9191005677005	62

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	44.4864252918608
beta	-0.0373422731486085
S.D.	0.0687861385783624
T-STAT	-0.542874973364983
p-value	0.624952215203405

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 44.4864252918608 \tabularnewline
beta & -0.0373422731486085 \tabularnewline
S.D. & 0.0687861385783624 \tabularnewline
T-STAT & -0.542874973364983 \tabularnewline
p-value & 0.624952215203405 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=70085&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]44.4864252918608[/C][/ROW]
[ROW][C]beta[/C][C]-0.0373422731486085[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0687861385783624[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.542874973364983[/C][/ROW]
[ROW][C]p-value[/C][C]0.624952215203405[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=70085&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=70085&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	44.4864252918608
beta	-0.0373422731486085
S.D.	0.0687861385783624
T-STAT	-0.542874973364983
p-value	0.624952215203405

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	8.09079827762465
beta	-0.781754486633166
S.D.	1.53223535168724
T-STAT	-0.510205227788490
p-value	0.645075944387708
Lambda	1.78175448663317

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 8.09079827762465 \tabularnewline
beta & -0.781754486633166 \tabularnewline
S.D. & 1.53223535168724 \tabularnewline
T-STAT & -0.510205227788490 \tabularnewline
p-value & 0.645075944387708 \tabularnewline
Lambda & 1.78175448663317 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=70085&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]8.09079827762465[/C][/ROW]
[ROW][C]beta[/C][C]-0.781754486633166[/C][/ROW]
[ROW][C]S.D.[/C][C]1.53223535168724[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.510205227788490[/C][/ROW]
[ROW][C]p-value[/C][C]0.645075944387708[/C][/ROW]
[ROW][C]Lambda[/C][C]1.78175448663317[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=70085&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=70085&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	8.09079827762465
beta	-0.781754486633166
S.D.	1.53223535168724
T-STAT	-0.510205227788490
p-value	0.645075944387708
Lambda	1.78175448663317

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