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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

Fri, 02 Jul 2010 18:20:35 +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/02/t1278094882vwy9tcv8518fajt.htm/, Retrieved Fri, 03 May 2024 21:34:59 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=77934, Retrieved Fri, 03 May 2024 21:34:59 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

thomas talboom

Estimated Impact

205

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

-     [Harrell-Davis Quantiles] [percentielen] [2010-07-01 11:45:42] [b6623a0531b43a362887826f077b4445]
- RMP   [Mean Plot] [gemiddeldegrafieken] [2010-07-01 13:10:54] [b6623a0531b43a362887826f077b4445]
- RMPD      [Standard Deviation-Mean Plot] [Standard Deviatio...] [2010-07-02 18:20:35] [58d9ccda37eeb031a0ffa1e9ea016ece] [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=77934&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=77934&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=77934&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	233.833333333333	2.32900030576263	7
2	236.583333333333	6.57071095272364	22
3	224.5	11.9810456365651	39
4	203.416666666667	13.1802768168843	39
5	171.416666666667	20.2998357957234	59
6	149.416666666667	18.8460670280099	55
7	131.666666666667	19.9878751125564	59

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 233.833333333333 & 2.32900030576263 & 7 \tabularnewline
2 & 236.583333333333 & 6.57071095272364 & 22 \tabularnewline
3 & 224.5 & 11.9810456365651 & 39 \tabularnewline
4 & 203.416666666667 & 13.1802768168843 & 39 \tabularnewline
5 & 171.416666666667 & 20.2998357957234 & 59 \tabularnewline
6 & 149.416666666667 & 18.8460670280099 & 55 \tabularnewline
7 & 131.666666666667 & 19.9878751125564 & 59 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=77934&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]233.833333333333[/C][C]2.32900030576263[/C][C]7[/C][/ROW]
[ROW][C]2[/C][C]236.583333333333[/C][C]6.57071095272364[/C][C]22[/C][/ROW]
[ROW][C]3[/C][C]224.5[/C][C]11.9810456365651[/C][C]39[/C][/ROW]
[ROW][C]4[/C][C]203.416666666667[/C][C]13.1802768168843[/C][C]39[/C][/ROW]
[ROW][C]5[/C][C]171.416666666667[/C][C]20.2998357957234[/C][C]59[/C][/ROW]
[ROW][C]6[/C][C]149.416666666667[/C][C]18.8460670280099[/C][C]55[/C][/ROW]
[ROW][C]7[/C][C]131.666666666667[/C][C]19.9878751125564[/C][C]59[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=77934&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=77934&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	233.833333333333	2.32900030576263	7
2	236.583333333333	6.57071095272364	22
3	224.5	11.9810456365651	39
4	203.416666666667	13.1802768168843	39
5	171.416666666667	20.2998357957234	59
6	149.416666666667	18.8460670280099	55
7	131.666666666667	19.9878751125564	59

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	41.6849263175632
beta	-0.1470201154162
S.D.	0.0329376736755910
T-STAT	-4.46358528122621
p-value	0.00661844525220058

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 41.6849263175632 \tabularnewline
beta & -0.1470201154162 \tabularnewline
S.D. & 0.0329376736755910 \tabularnewline
T-STAT & -4.46358528122621 \tabularnewline
p-value & 0.00661844525220058 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=77934&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]41.6849263175632[/C][/ROW]
[ROW][C]beta[/C][C]-0.1470201154162[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0329376736755910[/C][/ROW]
[ROW][C]T-STAT[/C][C]-4.46358528122621[/C][/ROW]
[ROW][C]p-value[/C][C]0.00661844525220058[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=77934&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=77934&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	41.6849263175632
beta	-0.1470201154162
S.D.	0.0329376736755910
T-STAT	-4.46358528122621
p-value	0.00661844525220058

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	15.5719477468724
beta	-2.51550130791200
S.D.	1.01290675234421
T-STAT	-2.48344805885662
p-value	0.0556055939871728
Lambda	3.51550130791200

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 15.5719477468724 \tabularnewline
beta & -2.51550130791200 \tabularnewline
S.D. & 1.01290675234421 \tabularnewline
T-STAT & -2.48344805885662 \tabularnewline
p-value & 0.0556055939871728 \tabularnewline
Lambda & 3.51550130791200 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=77934&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]15.5719477468724[/C][/ROW]
[ROW][C]beta[/C][C]-2.51550130791200[/C][/ROW]
[ROW][C]S.D.[/C][C]1.01290675234421[/C][/ROW]
[ROW][C]T-STAT[/C][C]-2.48344805885662[/C][/ROW]
[ROW][C]p-value[/C][C]0.0556055939871728[/C][/ROW]
[ROW][C]Lambda[/C][C]3.51550130791200[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=77934&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=77934&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	15.5719477468724
beta	-2.51550130791200
S.D.	1.01290675234421
T-STAT	-2.48344805885662
p-value	0.0556055939871728
Lambda	3.51550130791200

Figure 1

PNG link

Postscript link

PDF link

Figure 2

PNG link

Postscript link

PDF link

Parameters (Session):

par1 = 48 ; par2 = 1 ; par3 = 0 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;

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