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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

Tue, 20 Dec 2016 13:37:44 +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/2016/Dec/20/t1482237471its3cezpm6kclt5.htm/, Retrieved Fri, 17 May 2024 12:59:18 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=301636, Retrieved Fri, 17 May 2024 12:59:18 +0000

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Estimated Impact

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

-       [Standard Deviation-Mean Plot] [] [2016-12-20 12:37:44] [361c8dad91b3f1ef2e651cd04783c23b] [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	Big Analytics Cloud Computing Center

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input view raw input (R code)  \tabularnewline
Raw Outputview raw output of R engine  \tabularnewline
Computing time1 seconds \tabularnewline
R ServerBig Analytics Cloud Computing Center \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=301636&T=0

[TABLE]
[ROW]

Summary of computational transaction[/C][/ROW] [ROW]

Raw Input[/C]

view raw input (R code) [/C][/ROW] [ROW]

Raw Output[/C]

view raw output of R engine [/C][/ROW] [ROW]

Computing time[/C]

1 seconds[/C][/ROW] [ROW]

R Server[/C]

Big Analytics Cloud Computing Center[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=301636&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=301636&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	Big Analytics Cloud Computing Center

Standard Deviation-Mean Plot
Section	Mean	Standard Deviation	Range
1	2902.08333333333	202.882168369781	750
2	3224.16666666667	196.18907083513	715
3	3436.25	217.622744884144	720
4	2960.83333333333	237.886846032208	695
5	4072.5	361.276147213533	1090
6	4398.75	486.649607940961	1740
7	4657.91666666667	675.851174894341	1895
8	4372.08333333333	416.906673300421	1255
9	4149.58333333333	551.981794550465	1785
10	3761.66666666667	356.825226720649	1000

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 2902.08333333333 & 202.882168369781 & 750 \tabularnewline
2 & 3224.16666666667 & 196.18907083513 & 715 \tabularnewline
3 & 3436.25 & 217.622744884144 & 720 \tabularnewline
4 & 2960.83333333333 & 237.886846032208 & 695 \tabularnewline
5 & 4072.5 & 361.276147213533 & 1090 \tabularnewline
6 & 4398.75 & 486.649607940961 & 1740 \tabularnewline
7 & 4657.91666666667 & 675.851174894341 & 1895 \tabularnewline
8 & 4372.08333333333 & 416.906673300421 & 1255 \tabularnewline
9 & 4149.58333333333 & 551.981794550465 & 1785 \tabularnewline
10 & 3761.66666666667 & 356.825226720649 & 1000 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=301636&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]2902.08333333333[/C][C]202.882168369781[/C][C]750[/C][/ROW]
[ROW][C]2[/C][C]3224.16666666667[/C][C]196.18907083513[/C][C]715[/C][/ROW]
[ROW][C]3[/C][C]3436.25[/C][C]217.622744884144[/C][C]720[/C][/ROW]
[ROW][C]4[/C][C]2960.83333333333[/C][C]237.886846032208[/C][C]695[/C][/ROW]
[ROW][C]5[/C][C]4072.5[/C][C]361.276147213533[/C][C]1090[/C][/ROW]
[ROW][C]6[/C][C]4398.75[/C][C]486.649607940961[/C][C]1740[/C][/ROW]
[ROW][C]7[/C][C]4657.91666666667[/C][C]675.851174894341[/C][C]1895[/C][/ROW]
[ROW][C]8[/C][C]4372.08333333333[/C][C]416.906673300421[/C][C]1255[/C][/ROW]
[ROW][C]9[/C][C]4149.58333333333[/C][C]551.981794550465[/C][C]1785[/C][/ROW]
[ROW][C]10[/C][C]3761.66666666667[/C][C]356.825226720649[/C][C]1000[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=301636&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=301636&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	2902.08333333333	202.882168369781	750
2	3224.16666666667	196.18907083513	715
3	3436.25	217.622744884144	720
4	2960.83333333333	237.886846032208	695
5	4072.5	361.276147213533	1090
6	4398.75	486.649607940961	1740
7	4657.91666666667	675.851174894341	1895
8	4372.08333333333	416.906673300421	1255
9	4149.58333333333	551.981794550465	1785
10	3761.66666666667	356.825226720649	1000

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	-513.449578598915
beta	0.232987296287084
S.D.	0.0401969410586159
T-STAT	5.79614493419631
p-value	0.000406947849866038

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -513.449578598915 \tabularnewline
beta & 0.232987296287084 \tabularnewline
S.D. & 0.0401969410586159 \tabularnewline
T-STAT & 5.79614493419631 \tabularnewline
p-value & 0.000406947849866038 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=301636&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-513.449578598915[/C][/ROW]
[ROW][C]beta[/C][C]0.232987296287084[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0401969410586159[/C][/ROW]
[ROW][C]T-STAT[/C][C]5.79614493419631[/C][/ROW]
[ROW][C]p-value[/C][C]0.000406947849866038[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=301636&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=301636&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	-513.449578598915
beta	0.232987296287084
S.D.	0.0401969410586159
T-STAT	5.79614493419631
p-value	0.000406947849866038

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	-13.7438715731138
beta	2.37846313143744
S.D.	0.362727981960539
T-STAT	6.55715370670298
p-value	0.000177141758782578
Lambda	-1.37846313143744

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -13.7438715731138 \tabularnewline
beta & 2.37846313143744 \tabularnewline
S.D. & 0.362727981960539 \tabularnewline
T-STAT & 6.55715370670298 \tabularnewline
p-value & 0.000177141758782578 \tabularnewline
Lambda & -1.37846313143744 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=301636&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-13.7438715731138[/C][/ROW]
[ROW][C]beta[/C][C]2.37846313143744[/C][/ROW]
[ROW][C]S.D.[/C][C]0.362727981960539[/C][/ROW]
[ROW][C]T-STAT[/C][C]6.55715370670298[/C][/ROW]
[ROW][C]p-value[/C][C]0.000177141758782578[/C][/ROW]
[ROW][C]Lambda[/C][C]-1.37846313143744[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=301636&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=301636&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	-13.7438715731138
beta	2.37846313143744
S.D.	0.362727981960539
T-STAT	6.55715370670298
p-value	0.000177141758782578
Lambda	-1.37846313143744

Figure 1

PNG link

Postscript link

PDF link

Figure 2

PNG link

Postscript link

PDF link

Parameters (Session):

par1 = Default ; par2 = 1 ; par3 = 0 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;

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