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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, 30 Nov 2011 07:51:40 -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/Nov/30/t1322657729ubv7vb8bj1fm73d.htm/, Retrieved Sat, 27 Apr 2024 04:34:05 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=148913, Retrieved Sat, 27 Apr 2024 04:34:05 +0000

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Original text written by user:

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] [] [2011-11-30 12:51:40] [d22ab4133447fd2cf74cbadcaeb9b5f8] [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=148913&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=148913&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=148913&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	21.16	0.115443807661012	0.399999999999999
2	21.6483333333333	0.19020722351895	0.780000000000001
3	22.0966666666667	0.11979780946042	0.359999999999999
4	22.145	0.134603795704957	0.43
5	22.2875	0.0792148975887742	0.289999999999999

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 21.16 & 0.115443807661012 & 0.399999999999999 \tabularnewline
2 & 21.6483333333333 & 0.19020722351895 & 0.780000000000001 \tabularnewline
3 & 22.0966666666667 & 0.11979780946042 & 0.359999999999999 \tabularnewline
4 & 22.145 & 0.134603795704957 & 0.43 \tabularnewline
5 & 22.2875 & 0.0792148975887742 & 0.289999999999999 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=148913&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]21.16[/C][C]0.115443807661012[/C][C]0.399999999999999[/C][/ROW]
[ROW][C]2[/C][C]21.6483333333333[/C][C]0.19020722351895[/C][C]0.780000000000001[/C][/ROW]
[ROW][C]3[/C][C]22.0966666666667[/C][C]0.11979780946042[/C][C]0.359999999999999[/C][/ROW]
[ROW][C]4[/C][C]22.145[/C][C]0.134603795704957[/C][C]0.43[/C][/ROW]
[ROW][C]5[/C][C]22.2875[/C][C]0.0792148975887742[/C][C]0.289999999999999[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=148913&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=148913&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	21.16	0.115443807661012	0.399999999999999
2	21.6483333333333	0.19020722351895	0.780000000000001
3	22.0966666666667	0.11979780946042	0.359999999999999
4	22.145	0.134603795704957	0.43
5	22.2875	0.0792148975887742	0.289999999999999

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	0.774964937752706
beta	-0.0295923828039732
S.D.	0.047441924300956
T-STAT	-0.623760170777409
p-value	0.576995931974599

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 0.774964937752706 \tabularnewline
beta & -0.0295923828039732 \tabularnewline
S.D. & 0.047441924300956 \tabularnewline
T-STAT & -0.623760170777409 \tabularnewline
p-value & 0.576995931974599 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=148913&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]0.774964937752706[/C][/ROW]
[ROW][C]beta[/C][C]-0.0295923828039732[/C][/ROW]
[ROW][C]S.D.[/C][C]0.047441924300956[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.623760170777409[/C][/ROW]
[ROW][C]p-value[/C][C]0.576995931974599[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=148913&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=148913&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	0.774964937752706
beta	-0.0295923828039732
S.D.	0.047441924300956
T-STAT	-0.623760170777409
p-value	0.576995931974599

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	14.6090809810912
beta	-5.41535309953609
S.D.	7.94594457835734
T-STAT	-0.681524146831591
p-value	0.544436921013804
Lambda	6.41535309953609

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 14.6090809810912 \tabularnewline
beta & -5.41535309953609 \tabularnewline
S.D. & 7.94594457835734 \tabularnewline
T-STAT & -0.681524146831591 \tabularnewline
p-value & 0.544436921013804 \tabularnewline
Lambda & 6.41535309953609 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=148913&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]14.6090809810912[/C][/ROW]
[ROW][C]beta[/C][C]-5.41535309953609[/C][/ROW]
[ROW][C]S.D.[/C][C]7.94594457835734[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.681524146831591[/C][/ROW]
[ROW][C]p-value[/C][C]0.544436921013804[/C][/ROW]
[ROW][C]Lambda[/C][C]6.41535309953609[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=148913&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=148913&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	14.6090809810912
beta	-5.41535309953609
S.D.	7.94594457835734
T-STAT	-0.681524146831591
p-value	0.544436921013804
Lambda	6.41535309953609

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