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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

Wed, 21 Dec 2016 16:56:59 +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/t1482335829xnh6gbiguoompir.htm/, Retrieved Tue, 07 May 2024 00:07:27 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=302401, Retrieved Tue, 07 May 2024 00:07:27 +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] [] [2016-12-21 15:56:59] [24da340c2401d75222b6137c0718139b] [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=302401&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=302401&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=302401&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	7075	786.389910228438	2900
2	6575	730.037358944421	2300
3	6683.33333333333	815.568216123897	2600
4	6408.33333333333	783.301095403681	2300
5	6625	686.393738051538	2400
6	6575	735.001546071349	2400
7	6433.33333333333	791.239916877685	2600
8	6250	748.938642953541	2500
9	6150	1078.2983226952	3500
10	6433.33333333333	846.740631462608	2700

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 7075 & 786.389910228438 & 2900 \tabularnewline
2 & 6575 & 730.037358944421 & 2300 \tabularnewline
3 & 6683.33333333333 & 815.568216123897 & 2600 \tabularnewline
4 & 6408.33333333333 & 783.301095403681 & 2300 \tabularnewline
5 & 6625 & 686.393738051538 & 2400 \tabularnewline
6 & 6575 & 735.001546071349 & 2400 \tabularnewline
7 & 6433.33333333333 & 791.239916877685 & 2600 \tabularnewline
8 & 6250 & 748.938642953541 & 2500 \tabularnewline
9 & 6150 & 1078.2983226952 & 3500 \tabularnewline
10 & 6433.33333333333 & 846.740631462608 & 2700 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=302401&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]7075[/C][C]786.389910228438[/C][C]2900[/C][/ROW]
[ROW][C]2[/C][C]6575[/C][C]730.037358944421[/C][C]2300[/C][/ROW]
[ROW][C]3[/C][C]6683.33333333333[/C][C]815.568216123897[/C][C]2600[/C][/ROW]
[ROW][C]4[/C][C]6408.33333333333[/C][C]783.301095403681[/C][C]2300[/C][/ROW]
[ROW][C]5[/C][C]6625[/C][C]686.393738051538[/C][C]2400[/C][/ROW]
[ROW][C]6[/C][C]6575[/C][C]735.001546071349[/C][C]2400[/C][/ROW]
[ROW][C]7[/C][C]6433.33333333333[/C][C]791.239916877685[/C][C]2600[/C][/ROW]
[ROW][C]8[/C][C]6250[/C][C]748.938642953541[/C][C]2500[/C][/ROW]
[ROW][C]9[/C][C]6150[/C][C]1078.2983226952[/C][C]3500[/C][/ROW]
[ROW][C]10[/C][C]6433.33333333333[/C][C]846.740631462608[/C][C]2700[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=302401&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=302401&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	7075	786.389910228438	2900
2	6575	730.037358944421	2300
3	6683.33333333333	815.568216123897	2600
4	6408.33333333333	783.301095403681	2300
5	6625	686.393738051538	2400
6	6575	735.001546071349	2400
7	6433.33333333333	791.239916877685	2600
8	6250	748.938642953541	2500
9	6150	1078.2983226952	3500
10	6433.33333333333	846.740631462608	2700

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	2072.94302686158
beta	-0.195182428981011
S.D.	0.132400532553538
T-STAT	-1.47418160045607
p-value	0.178661551932188

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 2072.94302686158 \tabularnewline
beta & -0.195182428981011 \tabularnewline
S.D. & 0.132400532553538 \tabularnewline
T-STAT & -1.47418160045607 \tabularnewline
p-value & 0.178661551932188 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=302401&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]2072.94302686158[/C][/ROW]
[ROW][C]beta[/C][C]-0.195182428981011[/C][/ROW]
[ROW][C]S.D.[/C][C]0.132400532553538[/C][/ROW]
[ROW][C]T-STAT[/C][C]-1.47418160045607[/C][/ROW]
[ROW][C]p-value[/C][C]0.178661551932188[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=302401&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=302401&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	2072.94302686158
beta	-0.195182428981011
S.D.	0.132400532553538
T-STAT	-1.47418160045607
p-value	0.178661551932188

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	19.516019027372
beta	-1.46188817641335
S.D.	0.996372409479384
T-STAT	-1.46721061573474
p-value	0.180498152454316
Lambda	2.46188817641335

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 19.516019027372 \tabularnewline
beta & -1.46188817641335 \tabularnewline
S.D. & 0.996372409479384 \tabularnewline
T-STAT & -1.46721061573474 \tabularnewline
p-value & 0.180498152454316 \tabularnewline
Lambda & 2.46188817641335 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=302401&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]19.516019027372[/C][/ROW]
[ROW][C]beta[/C][C]-1.46188817641335[/C][/ROW]
[ROW][C]S.D.[/C][C]0.996372409479384[/C][/ROW]
[ROW][C]T-STAT[/C][C]-1.46721061573474[/C][/ROW]
[ROW][C]p-value[/C][C]0.180498152454316[/C][/ROW]
[ROW][C]Lambda[/C][C]2.46188817641335[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=302401&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=302401&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	19.516019027372
beta	-1.46188817641335
S.D.	0.996372409479384
T-STAT	-1.46721061573474
p-value	0.180498152454316
Lambda	2.46188817641335

Figure 1

PNG link

Postscript link

PDF link

Figure 2

PNG link

Postscript link

PDF link

Parameters (Session):

par1 = 2 ; par2 = 3 ; par3 = Exact Pearson Chi-Squared by Simulation ;

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