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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

Tue, 21 Jul 2015 12:22:23 +0100

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/2015/Jul/21/t14374777744tcjrkctlhw7u40.htm/, Retrieved Wed, 15 May 2024 19:47:51 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=279621, Retrieved Wed, 15 May 2024 19:47:51 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

160

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

-       [Standard Deviation-Mean Plot] [2 STAP 21 HLN] [2015-07-21 11:22:23] [70d22f55a70f3427b60459805adf1606] [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	'Herman Ole Andreas Wold' @ wold.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 & 2 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=279621&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]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=279621&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=279621&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	'Herman Ole Andreas Wold' @ wold.wessa.net

Standard Deviation-Mean Plot
Section	Mean	Standard Deviation	Range
1	69700	8690.43361194574	32400
2	67900	11851.3520517511	43200
3	65000	12718.4904764677	42000
4	65600	13931.7818477948	51600
5	65100	16462.5194139459	55200
6	67000	16571.1688291332	55200
7	68300	16224.896693886	60000
8	69100	17430.6939307961	60000
9	68600	19013.8705351455	67200

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 69700 & 8690.43361194574 & 32400 \tabularnewline
2 & 67900 & 11851.3520517511 & 43200 \tabularnewline
3 & 65000 & 12718.4904764677 & 42000 \tabularnewline
4 & 65600 & 13931.7818477948 & 51600 \tabularnewline
5 & 65100 & 16462.5194139459 & 55200 \tabularnewline
6 & 67000 & 16571.1688291332 & 55200 \tabularnewline
7 & 68300 & 16224.896693886 & 60000 \tabularnewline
8 & 69100 & 17430.6939307961 & 60000 \tabularnewline
9 & 68600 & 19013.8705351455 & 67200 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=279621&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]69700[/C][C]8690.43361194574[/C][C]32400[/C][/ROW]
[ROW][C]2[/C][C]67900[/C][C]11851.3520517511[/C][C]43200[/C][/ROW]
[ROW][C]3[/C][C]65000[/C][C]12718.4904764677[/C][C]42000[/C][/ROW]
[ROW][C]4[/C][C]65600[/C][C]13931.7818477948[/C][C]51600[/C][/ROW]
[ROW][C]5[/C][C]65100[/C][C]16462.5194139459[/C][C]55200[/C][/ROW]
[ROW][C]6[/C][C]67000[/C][C]16571.1688291332[/C][C]55200[/C][/ROW]
[ROW][C]7[/C][C]68300[/C][C]16224.896693886[/C][C]60000[/C][/ROW]
[ROW][C]8[/C][C]69100[/C][C]17430.6939307961[/C][C]60000[/C][/ROW]
[ROW][C]9[/C][C]68600[/C][C]19013.8705351455[/C][C]67200[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=279621&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=279621&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	69700	8690.43361194574	32400
2	67900	11851.3520517511	43200
3	65000	12718.4904764677	42000
4	65600	13931.7818477948	51600
5	65100	16462.5194139459	55200
6	67000	16571.1688291332	55200
7	68300	16224.896693886	60000
8	69100	17430.6939307961	60000
9	68600	19013.8705351455	67200

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	22004.5691138069
beta	-0.107448317059865
S.D.	0.68875700161761
T-STAT	-0.156003230177716
p-value	0.88043412050898

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 22004.5691138069 \tabularnewline
beta & -0.107448317059865 \tabularnewline
S.D. & 0.68875700161761 \tabularnewline
T-STAT & -0.156003230177716 \tabularnewline
p-value & 0.88043412050898 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=279621&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]22004.5691138069[/C][/ROW]
[ROW][C]beta[/C][C]-0.107448317059865[/C][/ROW]
[ROW][C]S.D.[/C][C]0.68875700161761[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.156003230177716[/C][/ROW]
[ROW][C]p-value[/C][C]0.88043412050898[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=279621&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=279621&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	22004.5691138069
beta	-0.107448317059865
S.D.	0.68875700161761
T-STAT	-0.156003230177716
p-value	0.88043412050898

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	23.9877344405556
beta	-1.29633550728171
S.D.	3.45582772786257
T-STAT	-0.375115778147742
p-value	0.718681736243493
Lambda	2.29633550728171

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 23.9877344405556 \tabularnewline
beta & -1.29633550728171 \tabularnewline
S.D. & 3.45582772786257 \tabularnewline
T-STAT & -0.375115778147742 \tabularnewline
p-value & 0.718681736243493 \tabularnewline
Lambda & 2.29633550728171 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=279621&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]23.9877344405556[/C][/ROW]
[ROW][C]beta[/C][C]-1.29633550728171[/C][/ROW]
[ROW][C]S.D.[/C][C]3.45582772786257[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.375115778147742[/C][/ROW]
[ROW][C]p-value[/C][C]0.718681736243493[/C][/ROW]
[ROW][C]Lambda[/C][C]2.29633550728171[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=279621&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=279621&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	23.9877344405556
beta	-1.29633550728171
S.D.	3.45582772786257
T-STAT	-0.375115778147742
p-value	0.718681736243493
Lambda	2.29633550728171

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