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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

Sat, 17 Dec 2016 12:55:34 +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/17/t1481975811n74q1kk730sgwg8.htm/, Retrieved Fri, 01 Nov 2024 03:36:20 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=300736, Retrieved Fri, 01 Nov 2024 03:36:20 +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] [] [2016-12-17 11:55:34] [349958aef20b862f8399a5ba04d6f6e3] [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=300736&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=300736&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=300736&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	1341.16666666667	717.092340108597	2574
2	1322.83333333333	598.324605321671	2338
3	1451.5	550.379786230299	1728
4	3166	1331.25204225195	4156
5	4248.5	2154.21314468352	7516
6	3936.5	1314.45616130779	4388
7	7538	1984.50964861715	6368
8	3691.83333333333	666.569758108064	2406
9	6072	1143.13349256252	3836
10	9210.33333333333	2171.19453227243	6920

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 1341.16666666667 & 717.092340108597 & 2574 \tabularnewline
2 & 1322.83333333333 & 598.324605321671 & 2338 \tabularnewline
3 & 1451.5 & 550.379786230299 & 1728 \tabularnewline
4 & 3166 & 1331.25204225195 & 4156 \tabularnewline
5 & 4248.5 & 2154.21314468352 & 7516 \tabularnewline
6 & 3936.5 & 1314.45616130779 & 4388 \tabularnewline
7 & 7538 & 1984.50964861715 & 6368 \tabularnewline
8 & 3691.83333333333 & 666.569758108064 & 2406 \tabularnewline
9 & 6072 & 1143.13349256252 & 3836 \tabularnewline
10 & 9210.33333333333 & 2171.19453227243 & 6920 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=300736&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]1341.16666666667[/C][C]717.092340108597[/C][C]2574[/C][/ROW]
[ROW][C]2[/C][C]1322.83333333333[/C][C]598.324605321671[/C][C]2338[/C][/ROW]
[ROW][C]3[/C][C]1451.5[/C][C]550.379786230299[/C][C]1728[/C][/ROW]
[ROW][C]4[/C][C]3166[/C][C]1331.25204225195[/C][C]4156[/C][/ROW]
[ROW][C]5[/C][C]4248.5[/C][C]2154.21314468352[/C][C]7516[/C][/ROW]
[ROW][C]6[/C][C]3936.5[/C][C]1314.45616130779[/C][C]4388[/C][/ROW]
[ROW][C]7[/C][C]7538[/C][C]1984.50964861715[/C][C]6368[/C][/ROW]
[ROW][C]8[/C][C]3691.83333333333[/C][C]666.569758108064[/C][C]2406[/C][/ROW]
[ROW][C]9[/C][C]6072[/C][C]1143.13349256252[/C][C]3836[/C][/ROW]
[ROW][C]10[/C][C]9210.33333333333[/C][C]2171.19453227243[/C][C]6920[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=300736&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=300736&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	1341.16666666667	717.092340108597	2574
2	1322.83333333333	598.324605321671	2338
3	1451.5	550.379786230299	1728
4	3166	1331.25204225195	4156
5	4248.5	2154.21314468352	7516
6	3936.5	1314.45616130779	4388
7	7538	1984.50964861715	6368
8	3691.83333333333	666.569758108064	2406
9	6072	1143.13349256252	3836
10	9210.33333333333	2171.19453227243	6920

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	462.368792008753
beta	0.190750164957831
S.D.	0.0517148737690699
T-STAT	3.68849715866301
p-value	0.00614348322701312

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 462.368792008753 \tabularnewline
beta & 0.190750164957831 \tabularnewline
S.D. & 0.0517148737690699 \tabularnewline
T-STAT & 3.68849715866301 \tabularnewline
p-value & 0.00614348322701312 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=300736&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]462.368792008753[/C][/ROW]
[ROW][C]beta[/C][C]0.190750164957831[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0517148737690699[/C][/ROW]
[ROW][C]T-STAT[/C][C]3.68849715866301[/C][/ROW]
[ROW][C]p-value[/C][C]0.00614348322701312[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=300736&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=300736&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	462.368792008753
beta	0.190750164957831
S.D.	0.0517148737690699
T-STAT	3.68849715866301
p-value	0.00614348322701312

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	1.8895094586504
beta	0.630109419687828
S.D.	0.150218689170845
T-STAT	4.1946140201716
p-value	0.00301865317400799
Lambda	0.369890580312172

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 1.8895094586504 \tabularnewline
beta & 0.630109419687828 \tabularnewline
S.D. & 0.150218689170845 \tabularnewline
T-STAT & 4.1946140201716 \tabularnewline
p-value & 0.00301865317400799 \tabularnewline
Lambda & 0.369890580312172 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=300736&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]1.8895094586504[/C][/ROW]
[ROW][C]beta[/C][C]0.630109419687828[/C][/ROW]
[ROW][C]S.D.[/C][C]0.150218689170845[/C][/ROW]
[ROW][C]T-STAT[/C][C]4.1946140201716[/C][/ROW]
[ROW][C]p-value[/C][C]0.00301865317400799[/C][/ROW]
[ROW][C]Lambda[/C][C]0.369890580312172[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=300736&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=300736&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	1.8895094586504
beta	0.630109419687828
S.D.	0.150218689170845
T-STAT	4.1946140201716
p-value	0.00301865317400799
Lambda	0.369890580312172

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