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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

Sat, 09 Jan 2016 11:02:32 +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/2016/Jan/09/t1452337414t8mrmymsp22q34a.htm/, Retrieved Sun, 05 May 2024 12:57:38 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=287494, Retrieved Sun, 05 May 2024 12:57:38 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

116

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

-     [Standard Deviation-Mean Plot] [] [2015-11-16 19:04:19] [a642a7d7b5f7c65c232df2d499025a08]
- R  D    [Standard Deviation-Mean Plot] [] [2016-01-09 11:02:32] [c6ba03d4d421ca9ab835e2907c34aa87] [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	'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 & 1 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=287494&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]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=287494&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=287494&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	'Herman Ole Andreas Wold' @ wold.wessa.net

Standard Deviation-Mean Plot
Section	Mean	Standard Deviation	Range
1	99.9916666666667	1.14372464369973	2.90000000000001
2	103.525	0.491981152632348	1.59999999999999
3	105.55	0.308957190326662	0.899999999999991
4	107.275	0.252712556798505	0.900000000000006
5	105.391666666667	0.342340429539031	1.09999999999999

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 99.9916666666667 & 1.14372464369973 & 2.90000000000001 \tabularnewline
2 & 103.525 & 0.491981152632348 & 1.59999999999999 \tabularnewline
3 & 105.55 & 0.308957190326662 & 0.899999999999991 \tabularnewline
4 & 107.275 & 0.252712556798505 & 0.900000000000006 \tabularnewline
5 & 105.391666666667 & 0.342340429539031 & 1.09999999999999 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=287494&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]99.9916666666667[/C][C]1.14372464369973[/C][C]2.90000000000001[/C][/ROW]
[ROW][C]2[/C][C]103.525[/C][C]0.491981152632348[/C][C]1.59999999999999[/C][/ROW]
[ROW][C]3[/C][C]105.55[/C][C]0.308957190326662[/C][C]0.899999999999991[/C][/ROW]
[ROW][C]4[/C][C]107.275[/C][C]0.252712556798505[/C][C]0.900000000000006[/C][/ROW]
[ROW][C]5[/C][C]105.391666666667[/C][C]0.342340429539031[/C][C]1.09999999999999[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=287494&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=287494&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	99.9916666666667	1.14372464369973	2.90000000000001
2	103.525	0.491981152632348	1.59999999999999
3	105.55	0.308957190326662	0.899999999999991
4	107.275	0.252712556798505	0.900000000000006
5	105.391666666667	0.342340429539031	1.09999999999999

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	13.7924045268382
beta	-0.127310835665464
S.D.	0.0203298584898756
T-STAT	-6.26225882137178
p-value	0.00821826263026623

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 13.7924045268382 \tabularnewline
beta & -0.127310835665464 \tabularnewline
S.D. & 0.0203298584898756 \tabularnewline
T-STAT & -6.26225882137178 \tabularnewline
p-value & 0.00821826263026623 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=287494&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]13.7924045268382[/C][/ROW]
[ROW][C]beta[/C][C]-0.127310835665464[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0203298584898756[/C][/ROW]
[ROW][C]T-STAT[/C][C]-6.26225882137178[/C][/ROW]
[ROW][C]p-value[/C][C]0.00821826263026623[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=287494&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=287494&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	13.7924045268382
beta	-0.127310835665464
S.D.	0.0203298584898756
T-STAT	-6.26225882137178
p-value	0.00821826263026623

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	101.81918670272
beta	-22.0893119322103
S.D.	1.33285726990257
T-STAT	-16.5729012633325
p-value	0.000478202560089048
Lambda	23.0893119322103

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 101.81918670272 \tabularnewline
beta & -22.0893119322103 \tabularnewline
S.D. & 1.33285726990257 \tabularnewline
T-STAT & -16.5729012633325 \tabularnewline
p-value & 0.000478202560089048 \tabularnewline
Lambda & 23.0893119322103 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=287494&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]101.81918670272[/C][/ROW]
[ROW][C]beta[/C][C]-22.0893119322103[/C][/ROW]
[ROW][C]S.D.[/C][C]1.33285726990257[/C][/ROW]
[ROW][C]T-STAT[/C][C]-16.5729012633325[/C][/ROW]
[ROW][C]p-value[/C][C]0.000478202560089048[/C][/ROW]
[ROW][C]Lambda[/C][C]23.0893119322103[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=287494&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=287494&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	101.81918670272
beta	-22.0893119322103
S.D.	1.33285726990257
T-STAT	-16.5729012633325
p-value	0.000478202560089048
Lambda	23.0893119322103

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