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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, 07 Dec 2009 07:15:47 -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/2009/Dec/07/t12601953940y0z8bhwqgs6afd.htm/, Retrieved Sat, 04 May 2024 20:17:30 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=64581, Retrieved Sat, 04 May 2024 20:17:30 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

193

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   [ARIMA Backward Selection] [] [2009-11-27 14:53:14] [b98453cac15ba1066b407e146608df68]
- RMPD    [Standard Deviation-Mean Plot] [Workshop 9 - opga...] [2009-12-01 19:37:41] [74be16979710d4c4e7c6647856088456]
-    D        [Standard Deviation-Mean Plot] [] [2009-12-07 14:15:47] [82bf023f1e4d9556a54030fcde33aa09] [Current]
- R  D          [Standard Deviation-Mean Plot] [Workshop9 R3 blog 1] [2009-12-11 10:40:37] [143cbdcaf7333bdd9926a1dde50d1082] 

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Dataseries X:

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Histogram

Boxplots

-706.026542296181 
-59.4405579520267 
-969.833720383066 
1994.56903063601 
102.064814516947 
1282.18411025837 
-307.754606959943 
225.069461418321 
-862.471322666482 
-2850.16172979440 
-3875.76341994283 
2996.98129088558 
1931.51753614196 
488.179241950267 
-601.581627830989 
-3495.10356420977 
265.163825175723 
640.313274555833 
-3418.45097379814 
2072.03398243007 
2662.9984145817 
-1064.81719671349 
-9.57987333730985 
-2208.8867746199 
-4275.21498681124 
381.837227886395 
1914.99171248840 
1019.08609621188 
884.745394297871 
-1702.08983953302 
-2064.71644375347 
-2452.89205796152 
1313.39939683182 
-569.737683944086 
-187.9171774845 
-128.334928612711 
-2601.14827891639 
581.657297679053 
-299.792761503996 
2868.57371158154 
2723.0124492194 
-1846.18418996859 
-6526.92686969168 
-3652.78139505582 
2790.5729463211 
-7703.28365973859 
-1373.42544129638 
-2976.48819823291 
5585.1945937738 
-2568.07437379205 
-4750.48266905558 
1324.51875012340 
-1689.96832952026 
-7068.09981170815 
1855.55513995599 
2269.56153308754 
-4661.24493442205 
3260.97170059017 
2160.39821896397 
4793.18303923311 
-2209.06420471032 
-2213.50510931699 
-3114.14394163762 
3411.46075067066 
-4693.81993673823 
5920.52037235391 
-2077.91680939984 
-3642.83868232441 
332.648590721953 
2734.67402718683 
7903.1305482291 
5491.06198558059 
4354.83029956606 
1619.51905250655 
5543.22938817069 
-366.008933224093 
-3459.03179080274 
1134.72876550400 
-2525.56367971036 
-926.76612281528 
-2956.34221718809 
-885.143314774538

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=64581&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=64581&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=64581&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	-252.548599356642	1890.79156762688	6872.74471082841
2	-228.184477972837	2033.49283201106	6158.10197879147
3	-488.903607532015	1817.13288482515	6190.20669929964
4	-1501.35119913361	3477.39006667904	10571.8573713201
5	42.6260714358241	4084.3395324563	12653.2944054819
6	653.51729921797	4273.20784837455	12596.9504849673

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & -252.548599356642 & 1890.79156762688 & 6872.74471082841 \tabularnewline
2 & -228.184477972837 & 2033.49283201106 & 6158.10197879147 \tabularnewline
3 & -488.903607532015 & 1817.13288482515 & 6190.20669929964 \tabularnewline
4 & -1501.35119913361 & 3477.39006667904 & 10571.8573713201 \tabularnewline
5 & 42.6260714358241 & 4084.3395324563 & 12653.2944054819 \tabularnewline
6 & 653.51729921797 & 4273.20784837455 & 12596.9504849673 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=64581&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]-252.548599356642[/C][C]1890.79156762688[/C][C]6872.74471082841[/C][/ROW]
[ROW][C]2[/C][C]-228.184477972837[/C][C]2033.49283201106[/C][C]6158.10197879147[/C][/ROW]
[ROW][C]3[/C][C]-488.903607532015[/C][C]1817.13288482515[/C][C]6190.20669929964[/C][/ROW]
[ROW][C]4[/C][C]-1501.35119913361[/C][C]3477.39006667904[/C][C]10571.8573713201[/C][/ROW]
[ROW][C]5[/C][C]42.6260714358241[/C][C]4084.3395324563[/C][C]12653.2944054819[/C][/ROW]
[ROW][C]6[/C][C]653.51729921797[/C][C]4273.20784837455[/C][C]12596.9504849673[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=64581&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=64581&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	-252.548599356642	1890.79156762688	6872.74471082841
2	-228.184477972837	2033.49283201106	6158.10197879147
3	-488.903607532015	1817.13288482515	6190.20669929964
4	-1501.35119913361	3477.39006667904	10571.8573713201
5	42.6260714358241	4084.3395324563	12653.2944054819
6	653.51729921797	4273.20784837455	12596.9504849673

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	3060.67485252565
beta	0.443810360434355
S.D.	0.776698896093243
T-STAT	0.571405936929612
p-value	0.598299095151353

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 3060.67485252565 \tabularnewline
beta & 0.443810360434355 \tabularnewline
S.D. & 0.776698896093243 \tabularnewline
T-STAT & 0.571405936929612 \tabularnewline
p-value & 0.598299095151353 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=64581&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]3060.67485252565[/C][/ROW]
[ROW][C]beta[/C][C]0.443810360434355[/C][/ROW]
[ROW][C]S.D.[/C][C]0.776698896093243[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.571405936929612[/C][/ROW]
[ROW][C]p-value[/C][C]0.598299095151353[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=64581&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=64581&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	3060.67485252565
beta	0.443810360434355
S.D.	0.776698896093243
T-STAT	0.571405936929612
p-value	0.598299095151353

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	8.25277781363841
beta	0.0165591102589068
S.D.	NaN
T-STAT	NaN
p-value	NaN
Lambda	0.983440889741093

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 8.25277781363841 \tabularnewline
beta & 0.0165591102589068 \tabularnewline
S.D. & NaN \tabularnewline
T-STAT & NaN \tabularnewline
p-value & NaN \tabularnewline
Lambda & 0.983440889741093 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=64581&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]8.25277781363841[/C][/ROW]
[ROW][C]beta[/C][C]0.0165591102589068[/C][/ROW]
[ROW][C]S.D.[/C][C]NaN[/C][/ROW]
[ROW][C]T-STAT[/C][C]NaN[/C][/ROW]
[ROW][C]p-value[/C][C]NaN[/C][/ROW]
[ROW][C]Lambda[/C][C]0.983440889741093[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=64581&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=64581&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	8.25277781363841
beta	0.0165591102589068
S.D.	NaN
T-STAT	NaN
p-value	NaN
Lambda	0.983440889741093

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')

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Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code