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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

Fri, 16 Dec 2016 16:41:10 +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/16/t1481902973qieyivnay7edyw9.htm/, Retrieved Fri, 01 Nov 2024 03:26:39 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=300383, Retrieved Fri, 01 Nov 2024 03:26:39 +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)

-     [ARIMA Forecasting] [Arima forecast 3e] [2016-12-14 14:39:22] [5f979cb1c6fa86b57093c7542788c28c]
- RMPD    [Standard Deviation-Mean Plot] [gqsdhjflkf] [2016-12-16 15:41:10] [4c05fa0998bf98e29c2e453b139976f4] [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=300383&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=300383&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=300383&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	5239.58333333333	171.112115469963	455
2	5594.58333333333	54.2074438587264	175
3	5450.41666666667	106.695367824248	380
4	5049.16666666667	267.622812362791	810
5	4999.58333333333	139.682404913519	455
6	5066.25	66.9166713838256	220
7	4998.33333333333	80.4626772127452	330
8	5099.58333333333	78.7821603402622	265
9	5007.91666666667	97.4553122143061	360

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 5239.58333333333 & 171.112115469963 & 455 \tabularnewline
2 & 5594.58333333333 & 54.2074438587264 & 175 \tabularnewline
3 & 5450.41666666667 & 106.695367824248 & 380 \tabularnewline
4 & 5049.16666666667 & 267.622812362791 & 810 \tabularnewline
5 & 4999.58333333333 & 139.682404913519 & 455 \tabularnewline
6 & 5066.25 & 66.9166713838256 & 220 \tabularnewline
7 & 4998.33333333333 & 80.4626772127452 & 330 \tabularnewline
8 & 5099.58333333333 & 78.7821603402622 & 265 \tabularnewline
9 & 5007.91666666667 & 97.4553122143061 & 360 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=300383&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]5239.58333333333[/C][C]171.112115469963[/C][C]455[/C][/ROW]
[ROW][C]2[/C][C]5594.58333333333[/C][C]54.2074438587264[/C][C]175[/C][/ROW]
[ROW][C]3[/C][C]5450.41666666667[/C][C]106.695367824248[/C][C]380[/C][/ROW]
[ROW][C]4[/C][C]5049.16666666667[/C][C]267.622812362791[/C][C]810[/C][/ROW]
[ROW][C]5[/C][C]4999.58333333333[/C][C]139.682404913519[/C][C]455[/C][/ROW]
[ROW][C]6[/C][C]5066.25[/C][C]66.9166713838256[/C][C]220[/C][/ROW]
[ROW][C]7[/C][C]4998.33333333333[/C][C]80.4626772127452[/C][C]330[/C][/ROW]
[ROW][C]8[/C][C]5099.58333333333[/C][C]78.7821603402622[/C][C]265[/C][/ROW]
[ROW][C]9[/C][C]5007.91666666667[/C][C]97.4553122143061[/C][C]360[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=300383&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=300383&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	5239.58333333333	171.112115469963	455
2	5594.58333333333	54.2074438587264	175
3	5450.41666666667	106.695367824248	380
4	5049.16666666667	267.622812362791	810
5	4999.58333333333	139.682404913519	455
6	5066.25	66.9166713838256	220
7	4998.33333333333	80.4626772127452	330
8	5099.58333333333	78.7821603402622	265
9	5007.91666666667	97.4553122143061	360

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	534.122912737484
beta	-0.0805103903464358
S.D.	0.11223259753324
T-STAT	-0.717352998290814
p-value	0.496390428580569

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 534.122912737484 \tabularnewline
beta & -0.0805103903464358 \tabularnewline
S.D. & 0.11223259753324 \tabularnewline
T-STAT & -0.717352998290814 \tabularnewline
p-value & 0.496390428580569 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=300383&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]534.122912737484[/C][/ROW]
[ROW][C]beta[/C][C]-0.0805103903464358[/C][/ROW]
[ROW][C]S.D.[/C][C]0.11223259753324[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.717352998290814[/C][/ROW]
[ROW][C]p-value[/C][C]0.496390428580569[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=300383&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=300383&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	534.122912737484
beta	-0.0805103903464358
S.D.	0.11223259753324
T-STAT	-0.717352998290814
p-value	0.496390428580569

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	37.3460859893794
beta	-3.82412424365339
S.D.	4.3396090613423
T-STAT	-0.881213996375641
p-value	0.407439135155993
Lambda	4.82412424365339

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 37.3460859893794 \tabularnewline
beta & -3.82412424365339 \tabularnewline
S.D. & 4.3396090613423 \tabularnewline
T-STAT & -0.881213996375641 \tabularnewline
p-value & 0.407439135155993 \tabularnewline
Lambda & 4.82412424365339 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=300383&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]37.3460859893794[/C][/ROW]
[ROW][C]beta[/C][C]-3.82412424365339[/C][/ROW]
[ROW][C]S.D.[/C][C]4.3396090613423[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.881213996375641[/C][/ROW]
[ROW][C]p-value[/C][C]0.407439135155993[/C][/ROW]
[ROW][C]Lambda[/C][C]4.82412424365339[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=300383&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=300383&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	37.3460859893794
beta	-3.82412424365339
S.D.	4.3396090613423
T-STAT	-0.881213996375641
p-value	0.407439135155993
Lambda	4.82412424365339

Figure 1

PNG link

Postscript link

PDF link

Figure 2

PNG link

Postscript link

PDF link

Parameters (Session):

par1 = 1 ; par2 = 12 ; par3 = BFGS ;

Parameters (R input):

par1 = 12 ;

R code (references can be found in the software module):

par1 <- '1'
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

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Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code