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Author's title

Author

*Unverified author*

R Software Module

rwasp_smp.wasp

Title produced by software

Standard Deviation-Mean Plot

Date of computation

Sat, 04 May 2013 09:01:07 -0400

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/2013/May/04/t1367672485porueka5yk7pxsk.htm/, Retrieved Mon, 29 Apr 2024 11:52:21 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=208711, Retrieved Mon, 29 Apr 2024 11:52:21 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

168

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

-       [Standard Deviation-Mean Plot] [opgv 8 oef 6] [2013-05-04 13:01:07] [21ec67e1bcc74ce82382f49324ef9e61] [Current]

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Dataseries X:

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Histogram

Boxplots

6.3
6.2
6.2
6.3
6.5
6.5
6.2
6.2
6.2
6.1
6.1
6.2
6.1
6.1
6.2
6.2
6.4
6.2
5.7
5.7
5.7
5.9
6
6.3
6.4
6.5
6.8
7
7.3
7.4
6.9
6.9
7
7.1
7.2
7.1
6.8
6.5
6.4
6.5
6.7
6.6
6.2
6.2
6.5
6.8
6.8
6.5
5.9
5.5
5.6
6
6.3
6.2
5.6
5.4
5.7
5.9
6.2
6.3
6.1
5.9
5.9
5.7
5.9
6.1
6.1
6.5
6.8
6.8
6.9
6.9
6.8
6.6
6.5
6.5

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	3 seconds
R Server	'Gertrude Mary Cox' @ cox.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 3 seconds \tabularnewline
R Server & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=208711&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]3 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=208711&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=208711&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	3 seconds
R Server	'Gertrude Mary Cox' @ cox.wessa.net

Standard Deviation-Mean Plot
Section	Mean	Standard Deviation	Range
1	6.25	0.131425748134554	0.4
2	6.04166666666667	0.242930342928074	0.7
3	6.96666666666667	0.296443566094439	1
4	6.54166666666667	0.210878393795327	0.6
5	5.88333333333333	0.321455025366432	0.899999999999999
6	6.3	0.449241785476576	1.2

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 6.25 & 0.131425748134554 & 0.4 \tabularnewline
2 & 6.04166666666667 & 0.242930342928074 & 0.7 \tabularnewline
3 & 6.96666666666667 & 0.296443566094439 & 1 \tabularnewline
4 & 6.54166666666667 & 0.210878393795327 & 0.6 \tabularnewline
5 & 5.88333333333333 & 0.321455025366432 & 0.899999999999999 \tabularnewline
6 & 6.3 & 0.449241785476576 & 1.2 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=208711&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]6.25[/C][C]0.131425748134554[/C][C]0.4[/C][/ROW]
[ROW][C]2[/C][C]6.04166666666667[/C][C]0.242930342928074[/C][C]0.7[/C][/ROW]
[ROW][C]3[/C][C]6.96666666666667[/C][C]0.296443566094439[/C][C]1[/C][/ROW]
[ROW][C]4[/C][C]6.54166666666667[/C][C]0.210878393795327[/C][C]0.6[/C][/ROW]
[ROW][C]5[/C][C]5.88333333333333[/C][C]0.321455025366432[/C][C]0.899999999999999[/C][/ROW]
[ROW][C]6[/C][C]6.3[/C][C]0.449241785476576[/C][C]1.2[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=208711&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=208711&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	6.25	0.131425748134554	0.4
2	6.04166666666667	0.242930342928074	0.7
3	6.96666666666667	0.296443566094439	1
4	6.54166666666667	0.210878393795327	0.6
5	5.88333333333333	0.321455025366432	0.899999999999999
6	6.3	0.449241785476576	1.2

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	0.319582656919409
beta	-0.00697993189261212
S.D.	0.140807714198515
T-STAT	-0.04957066402464
p-value	0.962841022142897

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 0.319582656919409 \tabularnewline
beta & -0.00697993189261212 \tabularnewline
S.D. & 0.140807714198515 \tabularnewline
T-STAT & -0.04957066402464 \tabularnewline
p-value & 0.962841022142897 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=208711&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]0.319582656919409[/C][/ROW]
[ROW][C]beta[/C][C]-0.00697993189261212[/C][/ROW]
[ROW][C]S.D.[/C][C]0.140807714198515[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.04957066402464[/C][/ROW]
[ROW][C]p-value[/C][C]0.962841022142897[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=208711&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=208711&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	0.319582656919409
beta	-0.00697993189261212
S.D.	0.140807714198515
T-STAT	-0.04957066402464
p-value	0.962841022142897

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	-1.28719463671346
beta	-0.0387398968554469
S.D.	3.48805817673417
T-STAT	-0.011106436559415
p-value	0.991670386637808
Lambda	1.03873989685545

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -1.28719463671346 \tabularnewline
beta & -0.0387398968554469 \tabularnewline
S.D. & 3.48805817673417 \tabularnewline
T-STAT & -0.011106436559415 \tabularnewline
p-value & 0.991670386637808 \tabularnewline
Lambda & 1.03873989685545 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=208711&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-1.28719463671346[/C][/ROW]
[ROW][C]beta[/C][C]-0.0387398968554469[/C][/ROW]
[ROW][C]S.D.[/C][C]3.48805817673417[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.011106436559415[/C][/ROW]
[ROW][C]p-value[/C][C]0.991670386637808[/C][/ROW]
[ROW][C]Lambda[/C][C]1.03873989685545[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=208711&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=208711&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	-1.28719463671346
beta	-0.0387398968554469
S.D.	3.48805817673417
T-STAT	-0.011106436559415
p-value	0.991670386637808
Lambda	1.03873989685545

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