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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

Fri, 23 Dec 2011 06:59:05 -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/23/t1324641590ozhmlmag53pwlk6.htm/, Retrieved Mon, 29 Apr 2024 20:20:36 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=160317, Retrieved Mon, 29 Apr 2024 20:20:36 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

111

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]
- RMP   [(Partial) Autocorrelation Function] [Unemployment] [2010-11-29 09:05:21] [b98453cac15ba1066b407e146608df68]
- R P     [(Partial) Autocorrelation Function] [ws9] [2011-12-04 18:35:07] [8501ca4b76170905b8a207a77f626994]
-    D      [(Partial) Autocorrelation Function] [Workshop 9_Graph1] [2011-12-06 09:05:34] [f722e8e78b9e5c5ebaa2263f273aa636]
- RMP         [Spectral Analysis] [Workshop 9_Graph2] [2011-12-06 09:28:52] [f722e8e78b9e5c5ebaa2263f273aa636]
- R P           [Spectral Analysis] [Workshop 9_Graph2] [2011-12-06 09:35:47] [f722e8e78b9e5c5ebaa2263f273aa636]
-   PD            [Spectral Analysis] [Paper: CP ] [2011-12-23 11:41:11] [f722e8e78b9e5c5ebaa2263f273aa636]
- RM                  [Standard Deviation-Mean Plot] [Paper: Standard D...] [2011-12-23 11:59:05] [3e64eea457df40fcb7af8f28e1ee6256] [Current]

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Dataseries X:

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Histogram

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	'AstonUniversity' @ aston.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 & 2 seconds \tabularnewline
R Server & 'AstonUniversity' @ aston.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=160317&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]'AstonUniversity' @ aston.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=160317&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=160317&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	'AstonUniversity' @ aston.wessa.net

Standard Deviation-Mean Plot
Section	Mean	Standard Deviation	Range
1	25.1858333333333	0.300407551452518	1.01
2	22.8791666666667	0.630893426143842	2.38
3	22.295	0.581150895754591	1.86
4	23.0433333333333	0.797932935588555	2.15
5	24.5241666666667	0.76591547520044	2.19
6	26.9041666666667	0.716715466978396	1.95
7	27.2183333333333	0.613200743244129	1.96
8	25.8825	0.772988592177377	2.34
9	24.3591666666667	0.536511600032746	1.98
10	25.65	1.12940048456934	3.52
11	24.3083333333333	0.993559563418623	3.15
12	25.1241666666667	1.00219267185265	2.8
13	27.2766666666667	1.04759754011768	2.95
14	27.355	0.785001447595655	2.65
15	29.5158333333333	1.34741812592105	4.42
16	31.3275	0.409259308774012	1.4
17	33.7733333333333	1.04397259919923	2.9
18	34.595	0.467750904960011	1.43
19	36.6358333333333	0.562291712278395	1.8
20	37.955	1.15951792490751	3.71
21	39.035	0.828399332777044	3.16999999999999

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 25.1858333333333 & 0.300407551452518 & 1.01 \tabularnewline
2 & 22.8791666666667 & 0.630893426143842 & 2.38 \tabularnewline
3 & 22.295 & 0.581150895754591 & 1.86 \tabularnewline
4 & 23.0433333333333 & 0.797932935588555 & 2.15 \tabularnewline
5 & 24.5241666666667 & 0.76591547520044 & 2.19 \tabularnewline
6 & 26.9041666666667 & 0.716715466978396 & 1.95 \tabularnewline
7 & 27.2183333333333 & 0.613200743244129 & 1.96 \tabularnewline
8 & 25.8825 & 0.772988592177377 & 2.34 \tabularnewline
9 & 24.3591666666667 & 0.536511600032746 & 1.98 \tabularnewline
10 & 25.65 & 1.12940048456934 & 3.52 \tabularnewline
11 & 24.3083333333333 & 0.993559563418623 & 3.15 \tabularnewline
12 & 25.1241666666667 & 1.00219267185265 & 2.8 \tabularnewline
13 & 27.2766666666667 & 1.04759754011768 & 2.95 \tabularnewline
14 & 27.355 & 0.785001447595655 & 2.65 \tabularnewline
15 & 29.5158333333333 & 1.34741812592105 & 4.42 \tabularnewline
16 & 31.3275 & 0.409259308774012 & 1.4 \tabularnewline
17 & 33.7733333333333 & 1.04397259919923 & 2.9 \tabularnewline
18 & 34.595 & 0.467750904960011 & 1.43 \tabularnewline
19 & 36.6358333333333 & 0.562291712278395 & 1.8 \tabularnewline
20 & 37.955 & 1.15951792490751 & 3.71 \tabularnewline
21 & 39.035 & 0.828399332777044 & 3.16999999999999 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=160317&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]25.1858333333333[/C][C]0.300407551452518[/C][C]1.01[/C][/ROW]
[ROW][C]2[/C][C]22.8791666666667[/C][C]0.630893426143842[/C][C]2.38[/C][/ROW]
[ROW][C]3[/C][C]22.295[/C][C]0.581150895754591[/C][C]1.86[/C][/ROW]
[ROW][C]4[/C][C]23.0433333333333[/C][C]0.797932935588555[/C][C]2.15[/C][/ROW]
[ROW][C]5[/C][C]24.5241666666667[/C][C]0.76591547520044[/C][C]2.19[/C][/ROW]
[ROW][C]6[/C][C]26.9041666666667[/C][C]0.716715466978396[/C][C]1.95[/C][/ROW]
[ROW][C]7[/C][C]27.2183333333333[/C][C]0.613200743244129[/C][C]1.96[/C][/ROW]
[ROW][C]8[/C][C]25.8825[/C][C]0.772988592177377[/C][C]2.34[/C][/ROW]
[ROW][C]9[/C][C]24.3591666666667[/C][C]0.536511600032746[/C][C]1.98[/C][/ROW]
[ROW][C]10[/C][C]25.65[/C][C]1.12940048456934[/C][C]3.52[/C][/ROW]
[ROW][C]11[/C][C]24.3083333333333[/C][C]0.993559563418623[/C][C]3.15[/C][/ROW]
[ROW][C]12[/C][C]25.1241666666667[/C][C]1.00219267185265[/C][C]2.8[/C][/ROW]
[ROW][C]13[/C][C]27.2766666666667[/C][C]1.04759754011768[/C][C]2.95[/C][/ROW]
[ROW][C]14[/C][C]27.355[/C][C]0.785001447595655[/C][C]2.65[/C][/ROW]
[ROW][C]15[/C][C]29.5158333333333[/C][C]1.34741812592105[/C][C]4.42[/C][/ROW]
[ROW][C]16[/C][C]31.3275[/C][C]0.409259308774012[/C][C]1.4[/C][/ROW]
[ROW][C]17[/C][C]33.7733333333333[/C][C]1.04397259919923[/C][C]2.9[/C][/ROW]
[ROW][C]18[/C][C]34.595[/C][C]0.467750904960011[/C][C]1.43[/C][/ROW]
[ROW][C]19[/C][C]36.6358333333333[/C][C]0.562291712278395[/C][C]1.8[/C][/ROW]
[ROW][C]20[/C][C]37.955[/C][C]1.15951792490751[/C][C]3.71[/C][/ROW]
[ROW][C]21[/C][C]39.035[/C][C]0.828399332777044[/C][C]3.16999999999999[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=160317&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=160317&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	25.1858333333333	0.300407551452518	1.01
2	22.8791666666667	0.630893426143842	2.38
3	22.295	0.581150895754591	1.86
4	23.0433333333333	0.797932935588555	2.15
5	24.5241666666667	0.76591547520044	2.19
6	26.9041666666667	0.716715466978396	1.95
7	27.2183333333333	0.613200743244129	1.96
8	25.8825	0.772988592177377	2.34
9	24.3591666666667	0.536511600032746	1.98
10	25.65	1.12940048456934	3.52
11	24.3083333333333	0.993559563418623	3.15
12	25.1241666666667	1.00219267185265	2.8
13	27.2766666666667	1.04759754011768	2.95
14	27.355	0.785001447595655	2.65
15	29.5158333333333	1.34741812592105	4.42
16	31.3275	0.409259308774012	1.4
17	33.7733333333333	1.04397259919923	2.9
18	34.595	0.467750904960011	1.43
19	36.6358333333333	0.562291712278395	1.8
20	37.955	1.15951792490751	3.71
21	39.035	0.828399332777044	3.16999999999999

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	0.607843987989329
beta	0.00626611133772121
S.D.	0.0120330997397691
T-STAT	0.520739582753715
p-value	0.6085640855208

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 0.607843987989329 \tabularnewline
beta & 0.00626611133772121 \tabularnewline
S.D. & 0.0120330997397691 \tabularnewline
T-STAT & 0.520739582753715 \tabularnewline
p-value & 0.6085640855208 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=160317&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]0.607843987989329[/C][/ROW]
[ROW][C]beta[/C][C]0.00626611133772121[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0120330997397691[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.520739582753715[/C][/ROW]
[ROW][C]p-value[/C][C]0.6085640855208[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=160317&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=160317&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	0.607843987989329
beta	0.00626611133772121
S.D.	0.0120330997397691
T-STAT	0.520739582753715
p-value	0.6085640855208

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	-0.983942386917476
beta	0.203920504174933
S.D.	0.498973298130569
T-STAT	0.408680193787789
p-value	0.687343863380516
Lambda	0.796079495825067

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -0.983942386917476 \tabularnewline
beta & 0.203920504174933 \tabularnewline
S.D. & 0.498973298130569 \tabularnewline
T-STAT & 0.408680193787789 \tabularnewline
p-value & 0.687343863380516 \tabularnewline
Lambda & 0.796079495825067 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=160317&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-0.983942386917476[/C][/ROW]
[ROW][C]beta[/C][C]0.203920504174933[/C][/ROW]
[ROW][C]S.D.[/C][C]0.498973298130569[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.408680193787789[/C][/ROW]
[ROW][C]p-value[/C][C]0.687343863380516[/C][/ROW]
[ROW][C]Lambda[/C][C]0.796079495825067[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=160317&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=160317&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	-0.983942386917476
beta	0.203920504174933
S.D.	0.498973298130569
T-STAT	0.408680193787789
p-value	0.687343863380516
Lambda	0.796079495825067

Figure 1

PNG link

Postscript link

PDF link

Figure 2

PNG link

Postscript link

PDF link

Parameters (Session):

par1 = Valutakoersen Eur-Dollar ; par4 = 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