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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

Wed, 12 Aug 2015 17:00:57 +0100

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/2015/Aug/12/t143939528528ifgu1e2dg05s7.htm/, Retrieved Sun, 19 May 2024 21:16:45 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=280026, Retrieved Sun, 19 May 2024 21:16:45 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

176

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

-       [Standard Deviation-Mean Plot] [] [2015-08-12 16:00:57] [d41d8cd98f00b204e9800998ecf8427e] [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	'Herman Ole Andreas Wold' @ wold.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 & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=280026&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]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=280026&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=280026&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	'Herman Ole Andreas Wold' @ wold.wessa.net

Standard Deviation-Mean Plot
Section	Mean	Standard Deviation	Range
1	52275	6517.82520895931	24300
2	50925	8888.51403881334	32400
3	48750	9538.86785735079	31500
4	49200	10448.8363858461	38700
5	48825	12346.8895604594	41400
6	50250	12428.3766218499	41400
7	51225	12168.6725204145	45000
8	51825	13073.0204480971	45000
9	51450	14260.4029013591	50400

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 52275 & 6517.82520895931 & 24300 \tabularnewline
2 & 50925 & 8888.51403881334 & 32400 \tabularnewline
3 & 48750 & 9538.86785735079 & 31500 \tabularnewline
4 & 49200 & 10448.8363858461 & 38700 \tabularnewline
5 & 48825 & 12346.8895604594 & 41400 \tabularnewline
6 & 50250 & 12428.3766218499 & 41400 \tabularnewline
7 & 51225 & 12168.6725204145 & 45000 \tabularnewline
8 & 51825 & 13073.0204480971 & 45000 \tabularnewline
9 & 51450 & 14260.4029013591 & 50400 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=280026&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]52275[/C][C]6517.82520895931[/C][C]24300[/C][/ROW]
[ROW][C]2[/C][C]50925[/C][C]8888.51403881334[/C][C]32400[/C][/ROW]
[ROW][C]3[/C][C]48750[/C][C]9538.86785735079[/C][C]31500[/C][/ROW]
[ROW][C]4[/C][C]49200[/C][C]10448.8363858461[/C][C]38700[/C][/ROW]
[ROW][C]5[/C][C]48825[/C][C]12346.8895604594[/C][C]41400[/C][/ROW]
[ROW][C]6[/C][C]50250[/C][C]12428.3766218499[/C][C]41400[/C][/ROW]
[ROW][C]7[/C][C]51225[/C][C]12168.6725204145[/C][C]45000[/C][/ROW]
[ROW][C]8[/C][C]51825[/C][C]13073.0204480971[/C][C]45000[/C][/ROW]
[ROW][C]9[/C][C]51450[/C][C]14260.4029013591[/C][C]50400[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=280026&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=280026&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	52275	6517.82520895931	24300
2	50925	8888.51403881334	32400
3	48750	9538.86785735079	31500
4	49200	10448.8363858461	38700
5	48825	12346.8895604594	41400
6	50250	12428.3766218499	41400
7	51225	12168.6725204145	45000
8	51825	13073.0204480971	45000
9	51450	14260.4029013591	50400

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	16503.4268353552
beta	-0.107448317059865
S.D.	0.68875700161761
T-STAT	-0.156003230177716
p-value	0.88043412050898

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 16503.4268353552 \tabularnewline
beta & -0.107448317059865 \tabularnewline
S.D. & 0.68875700161761 \tabularnewline
T-STAT & -0.156003230177716 \tabularnewline
p-value & 0.88043412050898 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=280026&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]16503.4268353552[/C][/ROW]
[ROW][C]beta[/C][C]-0.107448317059865[/C][/ROW]
[ROW][C]S.D.[/C][C]0.68875700161761[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.156003230177716[/C][/ROW]
[ROW][C]p-value[/C][C]0.88043412050898[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=280026&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=280026&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	16503.4268353552
beta	-0.107448317059865
S.D.	0.68875700161761
T-STAT	-0.156003230177716
p-value	0.88043412050898

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	23.3271198827726
beta	-1.29633550728138
S.D.	3.45582772786258
T-STAT	-0.375115778147646
p-value	0.718681736243562
Lambda	2.29633550728138

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 23.3271198827726 \tabularnewline
beta & -1.29633550728138 \tabularnewline
S.D. & 3.45582772786258 \tabularnewline
T-STAT & -0.375115778147646 \tabularnewline
p-value & 0.718681736243562 \tabularnewline
Lambda & 2.29633550728138 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=280026&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]23.3271198827726[/C][/ROW]
[ROW][C]beta[/C][C]-1.29633550728138[/C][/ROW]
[ROW][C]S.D.[/C][C]3.45582772786258[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.375115778147646[/C][/ROW]
[ROW][C]p-value[/C][C]0.718681736243562[/C][/ROW]
[ROW][C]Lambda[/C][C]2.29633550728138[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=280026&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=280026&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	23.3271198827726
beta	-1.29633550728138
S.D.	3.45582772786258
T-STAT	-0.375115778147646
p-value	0.718681736243562
Lambda	2.29633550728138

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