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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, 27 Jul 2010 12:42:19 +0000

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/2010/Jul/27/t1280234606nk7m1janl6zmkel.htm/, Retrieved Fri, 03 May 2024 22:55:12 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=78136, Retrieved Fri, 03 May 2024 22:55:12 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Habimana Christelle

Estimated Impact

223

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

-       [Standard Deviation-Mean Plot] [Tijdreeks 2 - Sta...] [2010-07-27 12:42:19] [ac302f869d0778eba7cafda3b14e71eb] [Current]

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Boxplots

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' @ 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 & 1 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=78136&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' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=78136&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=78136&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' @ 72.249.127.135

Standard Deviation-Mean Plot
Section	Mean	Standard Deviation	Range
1	372.833333333333	2.32900030576263	7
2	364.333333333333	5.08711980189064	17
3	339.166666666667	11.8692370386132	37
4	307.75	19.4708406691554	56
5	251.416666666667	29.3395740606541	86
6	190	25.6515106767613	80
7	133.75	26.3305042592324	87

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 372.833333333333 & 2.32900030576263 & 7 \tabularnewline
2 & 364.333333333333 & 5.08711980189064 & 17 \tabularnewline
3 & 339.166666666667 & 11.8692370386132 & 37 \tabularnewline
4 & 307.75 & 19.4708406691554 & 56 \tabularnewline
5 & 251.416666666667 & 29.3395740606541 & 86 \tabularnewline
6 & 190 & 25.6515106767613 & 80 \tabularnewline
7 & 133.75 & 26.3305042592324 & 87 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=78136&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]372.833333333333[/C][C]2.32900030576263[/C][C]7[/C][/ROW]
[ROW][C]2[/C][C]364.333333333333[/C][C]5.08711980189064[/C][C]17[/C][/ROW]
[ROW][C]3[/C][C]339.166666666667[/C][C]11.8692370386132[/C][C]37[/C][/ROW]
[ROW][C]4[/C][C]307.75[/C][C]19.4708406691554[/C][C]56[/C][/ROW]
[ROW][C]5[/C][C]251.416666666667[/C][C]29.3395740606541[/C][C]86[/C][/ROW]
[ROW][C]6[/C][C]190[/C][C]25.6515106767613[/C][C]80[/C][/ROW]
[ROW][C]7[/C][C]133.75[/C][C]26.3305042592324[/C][C]87[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=78136&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=78136&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	372.833333333333	2.32900030576263	7
2	364.333333333333	5.08711980189064	17
3	339.166666666667	11.8692370386132	37
4	307.75	19.4708406691554	56
5	251.416666666667	29.3395740606541	86
6	190	25.6515106767613	80
7	133.75	26.3305042592324	87

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	45.5145739174532
beta	-0.101326645711422
S.D.	0.0272722772001033
T-STAT	-3.71537165627804
p-value	0.0137779902495435

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 45.5145739174532 \tabularnewline
beta & -0.101326645711422 \tabularnewline
S.D. & 0.0272722772001033 \tabularnewline
T-STAT & -3.71537165627804 \tabularnewline
p-value & 0.0137779902495435 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=78136&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]45.5145739174532[/C][/ROW]
[ROW][C]beta[/C][C]-0.101326645711422[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0272722772001033[/C][/ROW]
[ROW][C]T-STAT[/C][C]-3.71537165627804[/C][/ROW]
[ROW][C]p-value[/C][C]0.0137779902495435[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=78136&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=78136&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	45.5145739174532
beta	-0.101326645711422
S.D.	0.0272722772001033
T-STAT	-3.71537165627804
p-value	0.0137779902495435

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	12.6587019798006
beta	-1.81332993557309
S.D.	0.786390124071151
T-STAT	-2.30589103304789
p-value	0.0692613706061056
Lambda	2.81332993557309

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 12.6587019798006 \tabularnewline
beta & -1.81332993557309 \tabularnewline
S.D. & 0.786390124071151 \tabularnewline
T-STAT & -2.30589103304789 \tabularnewline
p-value & 0.0692613706061056 \tabularnewline
Lambda & 2.81332993557309 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=78136&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]12.6587019798006[/C][/ROW]
[ROW][C]beta[/C][C]-1.81332993557309[/C][/ROW]
[ROW][C]S.D.[/C][C]0.786390124071151[/C][/ROW]
[ROW][C]T-STAT[/C][C]-2.30589103304789[/C][/ROW]
[ROW][C]p-value[/C][C]0.0692613706061056[/C][/ROW]
[ROW][C]Lambda[/C][C]2.81332993557309[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=78136&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=78136&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	12.6587019798006
beta	-1.81332993557309
S.D.	0.786390124071151
T-STAT	-2.30589103304789
p-value	0.0692613706061056
Lambda	2.81332993557309

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