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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

Sun, 25 Nov 2007 13:07:05 -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/2007/Nov/25/t1196020683bdatetuovkcnwtl.htm/, Retrieved Sat, 04 May 2024 14:21:46 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=6546, Retrieved Sat, 04 May 2024 14:21:46 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

181

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

-       [Standard Deviation-Mean Plot] [Totale werkloosheid] [2007-11-25 20:07:05] [4a507cbea0acb4f2b617b46f2010fec1] [Current]

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Dataseries X:

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Histogram

Boxplots

8,5
8,6
8,5
8,5
9
9
8,8
8
7,9
8,1
9,3
9,4
9,4
9,3
9
9,1
9,7
9,7
9,6
8,3
8,2
8,4
10,6
10,9
10,9
9,6
9,3
9,3
9,6
9,5
9,5
9
8,9
9
10,1
10,2
10,2
9,5
9,3
9,3
9,4
9,3
9,1
9
8,9
9
9,8
10
9,8
9,4
9
8,9
9,3
9,1
8,8
8,9
8,7
8,6
9,1
9,3
8,9

Summary of compuational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	1 seconds
R Server	'Gwilym Jenkins' @ 72.249.127.135

\begin{tabular}{lllllllll}
\hline
Summary of compuational 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' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=6546&T=0

[TABLE]
[ROW][C]Summary of compuational 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' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=6546&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6546&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 compuational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	1 seconds
R Server	'Gwilym Jenkins' @ 72.249.127.135

Standard Deviation-Mean Plot
Section	Mean	Standard Deviation	Range
1	8.63333333333333	0.486795333759165	0.9
2	9.35	0.841535393303109	2.3
3	9.575	0.580164553459541	2.4
4	9.4	0.411206650105405	1.7
5	9.075	0.336087109920249	0.8

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 8.63333333333333 & 0.486795333759165 & 0.9 \tabularnewline
2 & 9.35 & 0.841535393303109 & 2.3 \tabularnewline
3 & 9.575 & 0.580164553459541 & 2.4 \tabularnewline
4 & 9.4 & 0.411206650105405 & 1.7 \tabularnewline
5 & 9.075 & 0.336087109920249 & 0.8 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=6546&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]8.63333333333333[/C][C]0.486795333759165[/C][C]0.9[/C][/ROW]
[ROW][C]2[/C][C]9.35[/C][C]0.841535393303109[/C][C]2.3[/C][/ROW]
[ROW][C]3[/C][C]9.575[/C][C]0.580164553459541[/C][C]2.4[/C][/ROW]
[ROW][C]4[/C][C]9.4[/C][C]0.411206650105405[/C][C]1.7[/C][/ROW]
[ROW][C]5[/C][C]9.075[/C][C]0.336087109920249[/C][C]0.8[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=6546&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6546&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	8.63333333333333	0.486795333759165	0.9
2	9.35	0.841535393303109	2.3
3	9.575	0.580164553459541	2.4
4	9.4	0.411206650105405	1.7
5	9.075	0.336087109920249	0.8

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	-1.01227244626996
beta	0.167642677883359
S.D.	0.291940164848778
T-STAT	0.574236429475868
p-value	0.606037391883809

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -1.01227244626996 \tabularnewline
beta & 0.167642677883359 \tabularnewline
S.D. & 0.291940164848778 \tabularnewline
T-STAT & 0.574236429475868 \tabularnewline
p-value & 0.606037391883809 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=6546&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-1.01227244626996[/C][/ROW]
[ROW][C]beta[/C][C]0.167642677883359[/C][/ROW]
[ROW][C]S.D.[/C][C]0.291940164848778[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.574236429475868[/C][/ROW]
[ROW][C]p-value[/C][C]0.606037391883809[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=6546&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6546&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	-1.01227244626996
beta	0.167642677883359
S.D.	0.291940164848778
T-STAT	0.574236429475868
p-value	0.606037391883809

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	-6.54180292828558
beta	2.63987416470469
S.D.	4.75260404772094
T-STAT	0.555458468283428
p-value	0.617314789745103
Lambda	-1.63987416470469

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -6.54180292828558 \tabularnewline
beta & 2.63987416470469 \tabularnewline
S.D. & 4.75260404772094 \tabularnewline
T-STAT & 0.555458468283428 \tabularnewline
p-value & 0.617314789745103 \tabularnewline
Lambda & -1.63987416470469 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=6546&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-6.54180292828558[/C][/ROW]
[ROW][C]beta[/C][C]2.63987416470469[/C][/ROW]
[ROW][C]S.D.[/C][C]4.75260404772094[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.555458468283428[/C][/ROW]
[ROW][C]p-value[/C][C]0.617314789745103[/C][/ROW]
[ROW][C]Lambda[/C][C]-1.63987416470469[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=6546&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6546&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	-6.54180292828558
beta	2.63987416470469
S.D.	4.75260404772094
T-STAT	0.555458468283428
p-value	0.617314789745103
Lambda	-1.63987416470469

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