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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

Wed, 21 Dec 2016 11:11:48 +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/21/t1482315907npwi6swqe9ecx6d.htm/, Retrieved Mon, 06 May 2024 11:26:37 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=302055, Retrieved Mon, 06 May 2024 11:26:37 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

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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] [bhkl] [2016-12-21 10:11:48] [6db9e6f0306aa16a744aea8c8a65c446] [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=302055&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=302055&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=302055&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	3316.66666666667	648.036661888442	2300
2	4474.16666666667	300.256203730727	970
3	4331.66666666667	269.201963160927	1000
4	4118.33333333333	970.340458839374	2720
5	5755.83333333333	747.461866869637	2090
6	3514.16666666667	486.218400858435	1520
7	2932.5	357.926477976083	1280
8	2565	286.372294241414	1080
9	3413.33333333333	448.499180770172	1670
10	4882.5	328.221793082887	930

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 3316.66666666667 & 648.036661888442 & 2300 \tabularnewline
2 & 4474.16666666667 & 300.256203730727 & 970 \tabularnewline
3 & 4331.66666666667 & 269.201963160927 & 1000 \tabularnewline
4 & 4118.33333333333 & 970.340458839374 & 2720 \tabularnewline
5 & 5755.83333333333 & 747.461866869637 & 2090 \tabularnewline
6 & 3514.16666666667 & 486.218400858435 & 1520 \tabularnewline
7 & 2932.5 & 357.926477976083 & 1280 \tabularnewline
8 & 2565 & 286.372294241414 & 1080 \tabularnewline
9 & 3413.33333333333 & 448.499180770172 & 1670 \tabularnewline
10 & 4882.5 & 328.221793082887 & 930 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=302055&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]3316.66666666667[/C][C]648.036661888442[/C][C]2300[/C][/ROW]
[ROW][C]2[/C][C]4474.16666666667[/C][C]300.256203730727[/C][C]970[/C][/ROW]
[ROW][C]3[/C][C]4331.66666666667[/C][C]269.201963160927[/C][C]1000[/C][/ROW]
[ROW][C]4[/C][C]4118.33333333333[/C][C]970.340458839374[/C][C]2720[/C][/ROW]
[ROW][C]5[/C][C]5755.83333333333[/C][C]747.461866869637[/C][C]2090[/C][/ROW]
[ROW][C]6[/C][C]3514.16666666667[/C][C]486.218400858435[/C][C]1520[/C][/ROW]
[ROW][C]7[/C][C]2932.5[/C][C]357.926477976083[/C][C]1280[/C][/ROW]
[ROW][C]8[/C][C]2565[/C][C]286.372294241414[/C][C]1080[/C][/ROW]
[ROW][C]9[/C][C]3413.33333333333[/C][C]448.499180770172[/C][C]1670[/C][/ROW]
[ROW][C]10[/C][C]4882.5[/C][C]328.221793082887[/C][C]930[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=302055&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=302055&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	3316.66666666667	648.036661888442	2300
2	4474.16666666667	300.256203730727	970
3	4331.66666666667	269.201963160927	1000
4	4118.33333333333	970.340458839374	2720
5	5755.83333333333	747.461866869637	2090
6	3514.16666666667	486.218400858435	1520
7	2932.5	357.926477976083	1280
8	2565	286.372294241414	1080
9	3413.33333333333	448.499180770172	1670
10	4882.5	328.221793082887	930

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	227.004599084486
beta	0.0654508040429954
S.D.	0.082444951446869
T-STAT	0.79387279505131
p-value	0.45017353611297

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 227.004599084486 \tabularnewline
beta & 0.0654508040429954 \tabularnewline
S.D. & 0.082444951446869 \tabularnewline
T-STAT & 0.79387279505131 \tabularnewline
p-value & 0.45017353611297 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=302055&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]227.004599084486[/C][/ROW]
[ROW][C]beta[/C][C]0.0654508040429954[/C][/ROW]
[ROW][C]S.D.[/C][C]0.082444951446869[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.79387279505131[/C][/ROW]
[ROW][C]p-value[/C][C]0.45017353611297[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=302055&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=302055&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	227.004599084486
beta	0.0654508040429954
S.D.	0.082444951446869
T-STAT	0.79387279505131
p-value	0.45017353611297

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	2.39585136950334
beta	0.447711985937168
S.D.	0.61789131332379
T-STAT	0.724580482494267
p-value	0.489355927932154
Lambda	0.552288014062832

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 2.39585136950334 \tabularnewline
beta & 0.447711985937168 \tabularnewline
S.D. & 0.61789131332379 \tabularnewline
T-STAT & 0.724580482494267 \tabularnewline
p-value & 0.489355927932154 \tabularnewline
Lambda & 0.552288014062832 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=302055&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]2.39585136950334[/C][/ROW]
[ROW][C]beta[/C][C]0.447711985937168[/C][/ROW]
[ROW][C]S.D.[/C][C]0.61789131332379[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.724580482494267[/C][/ROW]
[ROW][C]p-value[/C][C]0.489355927932154[/C][/ROW]
[ROW][C]Lambda[/C][C]0.552288014062832[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=302055&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=302055&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	2.39585136950334
beta	0.447711985937168
S.D.	0.61789131332379
T-STAT	0.724580482494267
p-value	0.489355927932154
Lambda	0.552288014062832

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