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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, 06 Dec 2008 03:53:06 -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/2008/Dec/06/t1228560819ooyef3ud25dmo2o.htm/, Retrieved Sat, 25 May 2024 17:28:54 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=29491, Retrieved Sat, 25 May 2024 17:28:54 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

177

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

-     [Univariate Data Series] [data set] [2008-12-01 19:54:57] [b98453cac15ba1066b407e146608df68]
F RMPD    [Standard Deviation-Mean Plot] [Standard Deviatio...] [2008-12-06 10:53:06] [72e979bcc364082694890d2eccc1a66f] [Current]

Feedback Forum

2008-12-16 20:31:59 [Sofie Mertens] [reply] 
De conclusie is correct, men kan lambda het best gelijk aan 1 stellen. Men had hier ook nog moeten kijken naar de grafiek. Dan had men kunnen besluiten dat er geen consistent verband te zien is tussen de 2 assen. 

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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	2 seconds
R Server	'Sir Ronald Aylmer Fisher' @ 193.190.124.24

\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 & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=29491&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]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=29491&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=29491&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	'Sir Ronald Aylmer Fisher' @ 193.190.124.24

Standard Deviation-Mean Plot
Section	Mean	Standard Deviation	Range
1	321.916666666667	19.1949725109720	57
2	329.083333333333	54.1638227691667	135
3	364	36.4666722065255	96
4	305.166666666667	12.6622799421484	39
5	237.75	20.8550190165777	62

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 321.916666666667 & 19.1949725109720 & 57 \tabularnewline
2 & 329.083333333333 & 54.1638227691667 & 135 \tabularnewline
3 & 364 & 36.4666722065255 & 96 \tabularnewline
4 & 305.166666666667 & 12.6622799421484 & 39 \tabularnewline
5 & 237.75 & 20.8550190165777 & 62 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=29491&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]321.916666666667[/C][C]19.1949725109720[/C][C]57[/C][/ROW]
[ROW][C]2[/C][C]329.083333333333[/C][C]54.1638227691667[/C][C]135[/C][/ROW]
[ROW][C]3[/C][C]364[/C][C]36.4666722065255[/C][C]96[/C][/ROW]
[ROW][C]4[/C][C]305.166666666667[/C][C]12.6622799421484[/C][C]39[/C][/ROW]
[ROW][C]5[/C][C]237.75[/C][C]20.8550190165777[/C][C]62[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=29491&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=29491&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	321.916666666667	19.1949725109720	57
2	329.083333333333	54.1638227691667	135
3	364	36.4666722065255	96
4	305.166666666667	12.6622799421484	39
5	237.75	20.8550190165777	62

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	-23.0622602693219
beta	0.166025611848302
S.D.	0.184044769936791
T-STAT	0.902093615077038
p-value	0.433497777177743

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -23.0622602693219 \tabularnewline
beta & 0.166025611848302 \tabularnewline
S.D. & 0.184044769936791 \tabularnewline
T-STAT & 0.902093615077038 \tabularnewline
p-value & 0.433497777177743 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=29491&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-23.0622602693219[/C][/ROW]
[ROW][C]beta[/C][C]0.166025611848302[/C][/ROW]
[ROW][C]S.D.[/C][C]0.184044769936791[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.902093615077038[/C][/ROW]
[ROW][C]p-value[/C][C]0.433497777177743[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=29491&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=29491&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	-23.0622602693219
beta	0.166025611848302
S.D.	0.184044769936791
T-STAT	0.902093615077038
p-value	0.433497777177743

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	-5.58644939968285
beta	1.53704754127958
S.D.	1.87275110848739
T-STAT	0.820743095178863
p-value	0.471935650618494
Lambda	-0.537047541279583

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -5.58644939968285 \tabularnewline
beta & 1.53704754127958 \tabularnewline
S.D. & 1.87275110848739 \tabularnewline
T-STAT & 0.820743095178863 \tabularnewline
p-value & 0.471935650618494 \tabularnewline
Lambda & -0.537047541279583 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=29491&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-5.58644939968285[/C][/ROW]
[ROW][C]beta[/C][C]1.53704754127958[/C][/ROW]
[ROW][C]S.D.[/C][C]1.87275110848739[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.820743095178863[/C][/ROW]
[ROW][C]p-value[/C][C]0.471935650618494[/C][/ROW]
[ROW][C]Lambda[/C][C]-0.537047541279583[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=29491&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=29491&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	-5.58644939968285
beta	1.53704754127958
S.D.	1.87275110848739
T-STAT	0.820743095178863
p-value	0.471935650618494
Lambda	-0.537047541279583

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