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Author's title

Author

*The author of this computation has been verified*

R Software Module

rwasp_smp.wasp

Title produced by software

Standard Deviation-Mean Plot

Date of computation

Mon, 05 Dec 2011 11:03:35 -0500

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/2011/Dec/05/t13231010469ofc87bdbdl0ebc.htm/, Retrieved Fri, 03 May 2024 06:03:11 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=151014, Retrieved Fri, 03 May 2024 06:03:11 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

130

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

-     [Univariate Explorative Data Analysis] [Run Sequence gebo...] [2008-12-12 13:32:37] [76963dc1903f0f612b6153510a3818cf]
- R  D  [Univariate Explorative Data Analysis] [Run Sequence gebo...] [2008-12-17 12:14:40] [76963dc1903f0f612b6153510a3818cf]
-         [Univariate Explorative Data Analysis] [Run Sequence Plot...] [2008-12-22 18:19:51] [1ce0d16c8f4225c977b42c8fa93bc163]
- RMP       [(Partial) Autocorrelation Function] [Identifying Integ...] [2009-11-22 12:16:10] [b98453cac15ba1066b407e146608df68]
-    D        [(Partial) Autocorrelation Function] [ACF van Y(t) (d=0...] [2009-11-26 00:58:58] [9717cb857c153ca3061376906953b329]
- R PD          [(Partial) Autocorrelation Function] [WS9 ACF] [2011-12-02 16:43:02] [abc1cbe561c2c4615f632bb3153b1275]
- RMPD              [Standard Deviation-Mean Plot] [WS 9 - Standard D...] [2011-12-05 16:03:35] [c897fb90cb9e1f725365d7e541ad7850] [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	'Gwilym Jenkins' @ jenkins.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 & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=151014&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' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=151014&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=151014&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' @ jenkins.wessa.net

Standard Deviation-Mean Plot
Section	Mean	Standard Deviation	Range
1	29217.9166666667	7850.75588090186	28353
2	30084.5833333333	9097.19064984883	27385
3	26815.5833333333	6479.57569399744	24449
4	26259.3333333333	7596.89037260203	22874
5	22932.4166666667	5566.33655367584	20000
6	23735.25	6529.31853780943	20890
7	22458.8333333333	5033.65207800701	15936
8	23118.5	7012.69518282898	23808
9	23009.8333333333	6104.52451924477	21757
10	24156.25	6153.22854095902	19196
11	21032.8333333333	4752.75558029872	16277
12	24755.25	5877.29268417479	20132

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 29217.9166666667 & 7850.75588090186 & 28353 \tabularnewline
2 & 30084.5833333333 & 9097.19064984883 & 27385 \tabularnewline
3 & 26815.5833333333 & 6479.57569399744 & 24449 \tabularnewline
4 & 26259.3333333333 & 7596.89037260203 & 22874 \tabularnewline
5 & 22932.4166666667 & 5566.33655367584 & 20000 \tabularnewline
6 & 23735.25 & 6529.31853780943 & 20890 \tabularnewline
7 & 22458.8333333333 & 5033.65207800701 & 15936 \tabularnewline
8 & 23118.5 & 7012.69518282898 & 23808 \tabularnewline
9 & 23009.8333333333 & 6104.52451924477 & 21757 \tabularnewline
10 & 24156.25 & 6153.22854095902 & 19196 \tabularnewline
11 & 21032.8333333333 & 4752.75558029872 & 16277 \tabularnewline
12 & 24755.25 & 5877.29268417479 & 20132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=151014&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]29217.9166666667[/C][C]7850.75588090186[/C][C]28353[/C][/ROW]
[ROW][C]2[/C][C]30084.5833333333[/C][C]9097.19064984883[/C][C]27385[/C][/ROW]
[ROW][C]3[/C][C]26815.5833333333[/C][C]6479.57569399744[/C][C]24449[/C][/ROW]
[ROW][C]4[/C][C]26259.3333333333[/C][C]7596.89037260203[/C][C]22874[/C][/ROW]
[ROW][C]5[/C][C]22932.4166666667[/C][C]5566.33655367584[/C][C]20000[/C][/ROW]
[ROW][C]6[/C][C]23735.25[/C][C]6529.31853780943[/C][C]20890[/C][/ROW]
[ROW][C]7[/C][C]22458.8333333333[/C][C]5033.65207800701[/C][C]15936[/C][/ROW]
[ROW][C]8[/C][C]23118.5[/C][C]7012.69518282898[/C][C]23808[/C][/ROW]
[ROW][C]9[/C][C]23009.8333333333[/C][C]6104.52451924477[/C][C]21757[/C][/ROW]
[ROW][C]10[/C][C]24156.25[/C][C]6153.22854095902[/C][C]19196[/C][/ROW]
[ROW][C]11[/C][C]21032.8333333333[/C][C]4752.75558029872[/C][C]16277[/C][/ROW]
[ROW][C]12[/C][C]24755.25[/C][C]5877.29268417479[/C][C]20132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=151014&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=151014&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	29217.9166666667	7850.75588090186	28353
2	30084.5833333333	9097.19064984883	27385
3	26815.5833333333	6479.57569399744	24449
4	26259.3333333333	7596.89037260203	22874
5	22932.4166666667	5566.33655367584	20000
6	23735.25	6529.31853780943	20890
7	22458.8333333333	5033.65207800701	15936
8	23118.5	7012.69518282898	23808
9	23009.8333333333	6104.52451924477	21757
10	24156.25	6153.22854095902	19196
11	21032.8333333333	4752.75558029872	16277
12	24755.25	5877.29268417479	20132

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	-3216.31419335881
beta	0.391999885501702
S.D.	0.0671965606294172
T-STAT	5.83363020115784
p-value	0.000165234131641354

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -3216.31419335881 \tabularnewline
beta & 0.391999885501702 \tabularnewline
S.D. & 0.0671965606294172 \tabularnewline
T-STAT & 5.83363020115784 \tabularnewline
p-value & 0.000165234131641354 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=151014&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-3216.31419335881[/C][/ROW]
[ROW][C]beta[/C][C]0.391999885501702[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0671965606294172[/C][/ROW]
[ROW][C]T-STAT[/C][C]5.83363020115784[/C][/ROW]
[ROW][C]p-value[/C][C]0.000165234131641354[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=151014&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=151014&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	-3216.31419335881
beta	0.391999885501702
S.D.	0.0671965606294172
T-STAT	5.83363020115784
p-value	0.000165234131641354

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	-6.3436923078573
beta	1.49390765792706
S.D.	0.265886384401912
T-STAT	5.61859405207032
p-value	0.000221890364761257
Lambda	-0.493907657927064

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -6.3436923078573 \tabularnewline
beta & 1.49390765792706 \tabularnewline
S.D. & 0.265886384401912 \tabularnewline
T-STAT & 5.61859405207032 \tabularnewline
p-value & 0.000221890364761257 \tabularnewline
Lambda & -0.493907657927064 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=151014&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-6.3436923078573[/C][/ROW]
[ROW][C]beta[/C][C]1.49390765792706[/C][/ROW]
[ROW][C]S.D.[/C][C]0.265886384401912[/C][/ROW]
[ROW][C]T-STAT[/C][C]5.61859405207032[/C][/ROW]
[ROW][C]p-value[/C][C]0.000221890364761257[/C][/ROW]
[ROW][C]Lambda[/C][C]-0.493907657927064[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=151014&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=151014&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	-6.3436923078573
beta	1.49390765792706
S.D.	0.265886384401912
T-STAT	5.61859405207032
p-value	0.000221890364761257
Lambda	-0.493907657927064

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

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Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code