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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

Sat, 27 Dec 2014 09:27:59 +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/2014/Dec/27/t1419672541c9j952zj7eo1ya0.htm/, Retrieved Thu, 16 May 2024 20:08:48 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=271577, Retrieved Thu, 16 May 2024 20:08:48 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

133

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

-       [Standard Deviation-Mean Plot] [] [2014-12-27 09:27:59] [7a6c09eb8232161d54860d64a56e9131] [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=271577&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=271577&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=271577&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	300	23.013829834175	72
2	377.25	27.7754797029191	93
3	426.083333333333	34.563402434928	105
4	419.333333333333	20.7948128730278	56
5	506.583333333333	26.6644411950152	67
6	656.083333333333	28.1794842630828	117

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 300 & 23.013829834175 & 72 \tabularnewline
2 & 377.25 & 27.7754797029191 & 93 \tabularnewline
3 & 426.083333333333 & 34.563402434928 & 105 \tabularnewline
4 & 419.333333333333 & 20.7948128730278 & 56 \tabularnewline
5 & 506.583333333333 & 26.6644411950152 & 67 \tabularnewline
6 & 656.083333333333 & 28.1794842630828 & 117 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=271577&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]300[/C][C]23.013829834175[/C][C]72[/C][/ROW]
[ROW][C]2[/C][C]377.25[/C][C]27.7754797029191[/C][C]93[/C][/ROW]
[ROW][C]3[/C][C]426.083333333333[/C][C]34.563402434928[/C][C]105[/C][/ROW]
[ROW][C]4[/C][C]419.333333333333[/C][C]20.7948128730278[/C][C]56[/C][/ROW]
[ROW][C]5[/C][C]506.583333333333[/C][C]26.6644411950152[/C][C]67[/C][/ROW]
[ROW][C]6[/C][C]656.083333333333[/C][C]28.1794842630828[/C][C]117[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=271577&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=271577&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	300	23.013829834175	72
2	377.25	27.7754797029191	93
3	426.083333333333	34.563402434928	105
4	419.333333333333	20.7948128730278	56
5	506.583333333333	26.6644411950152	67
6	656.083333333333	28.1794842630828	117

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	22.2182881270342
beta	0.0103084861746312
S.D.	0.0187664443473721
T-STAT	0.549304172054028
p-value	0.612021599462619

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 22.2182881270342 \tabularnewline
beta & 0.0103084861746312 \tabularnewline
S.D. & 0.0187664443473721 \tabularnewline
T-STAT & 0.549304172054028 \tabularnewline
p-value & 0.612021599462619 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=271577&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]22.2182881270342[/C][/ROW]
[ROW][C]beta[/C][C]0.0103084861746312[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0187664443473721[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.549304172054028[/C][/ROW]
[ROW][C]p-value[/C][C]0.612021599462619[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=271577&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=271577&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	22.2182881270342
beta	0.0103084861746312
S.D.	0.0187664443473721
T-STAT	0.549304172054028
p-value	0.612021599462619

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	1.97807529776346
beta	0.213786301757669
S.D.	0.314304215174758
T-STAT	0.68018910162818
p-value	0.533716017961237
Lambda	0.786213698242331

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 1.97807529776346 \tabularnewline
beta & 0.213786301757669 \tabularnewline
S.D. & 0.314304215174758 \tabularnewline
T-STAT & 0.68018910162818 \tabularnewline
p-value & 0.533716017961237 \tabularnewline
Lambda & 0.786213698242331 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=271577&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]1.97807529776346[/C][/ROW]
[ROW][C]beta[/C][C]0.213786301757669[/C][/ROW]
[ROW][C]S.D.[/C][C]0.314304215174758[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.68018910162818[/C][/ROW]
[ROW][C]p-value[/C][C]0.533716017961237[/C][/ROW]
[ROW][C]Lambda[/C][C]0.786213698242331[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=271577&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=271577&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	1.97807529776346
beta	0.213786301757669
S.D.	0.314304215174758
T-STAT	0.68018910162818
p-value	0.533716017961237
Lambda	0.786213698242331

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