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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

Tue, 20 Dec 2016 14:57:55 +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/t1482242302uvn8i4nahs6wmhv.htm/, Retrieved Fri, 01 Nov 2024 03:41:16 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=301677, Retrieved Fri, 01 Nov 2024 03:41:16 +0000

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IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

113

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

-       [Standard Deviation-Mean Plot] [Standard Deviatio...] [2016-12-20 13:57:55] [86c9a777e8dbb7ef3face68c75fc8376] [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=301677&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=301677&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=301677&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	3010.83333333333	260.7927889875	870
2	3069.16666666667	284.579700717753	1115
3	3369.16666666667	331.291092362574	1115
4	3748.33333333333	376.57145484763	1405
5	4190.41666666667	466.33219886361	1675
6	4543.75	446.776967950351	1470
7	4745	480.511091537864	1770
8	5300.83333333333	831.241769154967	2490
9	6245.83333333333	810.066869667766	3010

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 3010.83333333333 & 260.7927889875 & 870 \tabularnewline
2 & 3069.16666666667 & 284.579700717753 & 1115 \tabularnewline
3 & 3369.16666666667 & 331.291092362574 & 1115 \tabularnewline
4 & 3748.33333333333 & 376.57145484763 & 1405 \tabularnewline
5 & 4190.41666666667 & 466.33219886361 & 1675 \tabularnewline
6 & 4543.75 & 446.776967950351 & 1470 \tabularnewline
7 & 4745 & 480.511091537864 & 1770 \tabularnewline
8 & 5300.83333333333 & 831.241769154967 & 2490 \tabularnewline
9 & 6245.83333333333 & 810.066869667766 & 3010 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=301677&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]3010.83333333333[/C][C]260.7927889875[/C][C]870[/C][/ROW]
[ROW][C]2[/C][C]3069.16666666667[/C][C]284.579700717753[/C][C]1115[/C][/ROW]
[ROW][C]3[/C][C]3369.16666666667[/C][C]331.291092362574[/C][C]1115[/C][/ROW]
[ROW][C]4[/C][C]3748.33333333333[/C][C]376.57145484763[/C][C]1405[/C][/ROW]
[ROW][C]5[/C][C]4190.41666666667[/C][C]466.33219886361[/C][C]1675[/C][/ROW]
[ROW][C]6[/C][C]4543.75[/C][C]446.776967950351[/C][C]1470[/C][/ROW]
[ROW][C]7[/C][C]4745[/C][C]480.511091537864[/C][C]1770[/C][/ROW]
[ROW][C]8[/C][C]5300.83333333333[/C][C]831.241769154967[/C][C]2490[/C][/ROW]
[ROW][C]9[/C][C]6245.83333333333[/C][C]810.066869667766[/C][C]3010[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=301677&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=301677&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	3010.83333333333	260.7927889875	870
2	3069.16666666667	284.579700717753	1115
3	3369.16666666667	331.291092362574	1115
4	3748.33333333333	376.57145484763	1405
5	4190.41666666667	466.33219886361	1675
6	4543.75	446.776967950351	1470
7	4745	480.511091537864	1770
8	5300.83333333333	831.241769154967	2490
9	6245.83333333333	810.066869667766	3010

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	-295.23398122862
beta	0.181702357159177
S.D.	0.0255505099712342
T-STAT	7.11149630139455
p-value	0.00019171727065252

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -295.23398122862 \tabularnewline
beta & 0.181702357159177 \tabularnewline
S.D. & 0.0255505099712342 \tabularnewline
T-STAT & 7.11149630139455 \tabularnewline
p-value & 0.00019171727065252 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=301677&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-295.23398122862[/C][/ROW]
[ROW][C]beta[/C][C]0.181702357159177[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0255505099712342[/C][/ROW]
[ROW][C]T-STAT[/C][C]7.11149630139455[/C][/ROW]
[ROW][C]p-value[/C][C]0.00019171727065252[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=301677&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=301677&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	-295.23398122862
beta	0.181702357159177
S.D.	0.0255505099712342
T-STAT	7.11149630139455
p-value	0.00019171727065252

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	-7.09930472688877
beta	1.5838778352577
S.D.	0.169107995767156
T-STAT	9.36607301193808
p-value	3.2889795760265e-05
Lambda	-0.583877835257698

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -7.09930472688877 \tabularnewline
beta & 1.5838778352577 \tabularnewline
S.D. & 0.169107995767156 \tabularnewline
T-STAT & 9.36607301193808 \tabularnewline
p-value & 3.2889795760265e-05 \tabularnewline
Lambda & -0.583877835257698 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=301677&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-7.09930472688877[/C][/ROW]
[ROW][C]beta[/C][C]1.5838778352577[/C][/ROW]
[ROW][C]S.D.[/C][C]0.169107995767156[/C][/ROW]
[ROW][C]T-STAT[/C][C]9.36607301193808[/C][/ROW]
[ROW][C]p-value[/C][C]3.2889795760265e-05[/C][/ROW]
[ROW][C]Lambda[/C][C]-0.583877835257698[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=301677&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=301677&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	-7.09930472688877
beta	1.5838778352577
S.D.	0.169107995767156
T-STAT	9.36607301193808
p-value	3.2889795760265e-05
Lambda	-0.583877835257698

Figure 1

PNG link

Postscript link

PDF link

Figure 2

PNG link

Postscript link

PDF link

Parameters (Session):

par1 = Default ; par2 = 1 ; par3 = 1 ; par4 = 1 ; 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