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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, 19 Mar 2016 19:22:51 +0000

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/Mar/19/t1458415716gfbp0tdde67bi0r.htm/, Retrieved Tue, 07 May 2024 20:29:23 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=294350, Retrieved Tue, 07 May 2024 20:29:23 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

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

-       [Standard Deviation-Mean Plot] [] [2016-03-19 19:22:51] [ed8c98a61958118f8b1101b2c94f1953] [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	'Sir Ronald Aylmer Fisher' @ fisher.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 & 1 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ fisher.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=294350&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]1 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Ronald Aylmer Fisher' @ fisher.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=294350&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=294350&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	'Sir Ronald Aylmer Fisher' @ fisher.wessa.net

Standard Deviation-Mean Plot
Section	Mean	Standard Deviation	Range
1	96.55	0.217088168095992	0.480000000000004
2	96.925	1.32966502958794	2.94
3	99.2425	0.203520157589992	0.450000000000003
4	100.0025	0.76433125850463	1.69
5	101.575	0.587947121926638	1.3
6	109.935	13.3599676782407	29.54

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 96.55 & 0.217088168095992 & 0.480000000000004 \tabularnewline
2 & 96.925 & 1.32966502958794 & 2.94 \tabularnewline
3 & 99.2425 & 0.203520157589992 & 0.450000000000003 \tabularnewline
4 & 100.0025 & 0.76433125850463 & 1.69 \tabularnewline
5 & 101.575 & 0.587947121926638 & 1.3 \tabularnewline
6 & 109.935 & 13.3599676782407 & 29.54 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=294350&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]96.55[/C][C]0.217088168095992[/C][C]0.480000000000004[/C][/ROW]
[ROW][C]2[/C][C]96.925[/C][C]1.32966502958794[/C][C]2.94[/C][/ROW]
[ROW][C]3[/C][C]99.2425[/C][C]0.203520157589992[/C][C]0.450000000000003[/C][/ROW]
[ROW][C]4[/C][C]100.0025[/C][C]0.76433125850463[/C][C]1.69[/C][/ROW]
[ROW][C]5[/C][C]101.575[/C][C]0.587947121926638[/C][C]1.3[/C][/ROW]
[ROW][C]6[/C][C]109.935[/C][C]13.3599676782407[/C][C]29.54[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=294350&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=294350&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	96.55	0.217088168095992	0.480000000000004
2	96.925	1.32966502958794	2.94
3	99.2425	0.203520157589992	0.450000000000003
4	100.0025	0.76433125850463	1.69
5	101.575	0.587947121926638	1.3
6	109.935	13.3599676782407	29.54

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	-95.3849581177981
beta	0.97441747036846
S.D.	0.214159308530667
T-STAT	4.5499655235809
p-value	0.0104178823870481

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -95.3849581177981 \tabularnewline
beta & 0.97441747036846 \tabularnewline
S.D. & 0.214159308530667 \tabularnewline
T-STAT & 4.5499655235809 \tabularnewline
p-value & 0.0104178823870481 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=294350&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-95.3849581177981[/C][/ROW]
[ROW][C]beta[/C][C]0.97441747036846[/C][/ROW]
[ROW][C]S.D.[/C][C]0.214159308530667[/C][/ROW]
[ROW][C]T-STAT[/C][C]4.5499655235809[/C][/ROW]
[ROW][C]p-value[/C][C]0.0104178823870481[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=294350&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=294350&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	-95.3849581177981
beta	0.97441747036846
S.D.	0.214159308530667
T-STAT	4.5499655235809
p-value	0.0104178823870481

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	-123.182829482792
beta	26.6759292653026
S.D.	9.21956211120456
T-STAT	2.89340523373483
p-value	0.0444108068501165
Lambda	-25.6759292653026

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -123.182829482792 \tabularnewline
beta & 26.6759292653026 \tabularnewline
S.D. & 9.21956211120456 \tabularnewline
T-STAT & 2.89340523373483 \tabularnewline
p-value & 0.0444108068501165 \tabularnewline
Lambda & -25.6759292653026 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=294350&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-123.182829482792[/C][/ROW]
[ROW][C]beta[/C][C]26.6759292653026[/C][/ROW]
[ROW][C]S.D.[/C][C]9.21956211120456[/C][/ROW]
[ROW][C]T-STAT[/C][C]2.89340523373483[/C][/ROW]
[ROW][C]p-value[/C][C]0.0444108068501165[/C][/ROW]
[ROW][C]Lambda[/C][C]-25.6759292653026[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=294350&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=294350&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	-123.182829482792
beta	26.6759292653026
S.D.	9.21956211120456
T-STAT	2.89340523373483
p-value	0.0444108068501165
Lambda	-25.6759292653026

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