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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, 03 Dec 2008 06:38:26 -0700

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/2008/Dec/03/t1228311582korkzndtmhbmpr1.htm/, Retrieved Sun, 19 May 2024 04:23:41 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=28702, Retrieved Sun, 19 May 2024 04:23:41 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

stand dev mannen

Estimated Impact

237

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

F     [Univariate Data Series] [Airline data] [2007-10-18 09:58:47] [42daae401fd3def69a25014f2252b4c2]
F RMPD  [Standard Deviation-Mean Plot] [non stationary ti...] [2008-12-02 17:35:08] [c96f3dce3a823a83b6ede18389e1cfd4]
F    D      [Standard Deviation-Mean Plot] [non stat time ser...] [2008-12-03 13:38:26] [3bdbbe597ac6c61989658933956ee6ac] [Current]

Feedback Forum

2008-12-10 00:01:24 [Peter Van Doninck] [reply] 
Ook hier is de p-waarde redelijk groot..

Post a new message

Dataseries X:

Download CSV

Histogram

Boxplots

7.6
7.9
7.9
8.1
8.2
8
7.5
6.8
6.5
6.6
7.6
8
8
7.7
7.5
7.6
7.7
7.9
7.8
7.5
7.5
7.1
7.5
7.5
7.6
7.7
7.7
7.9
8.1
8.2
8.2
8.1
7.9
7.3
6.9
6.6
6.7
6.9
7
7.1
7.2
7.1
6.9
7
6.8
6.4
6.7
6.7
6.4
6.3
6.2
6.5
6.8
6.8
6.5
6.3
5.9
5.9
6.4
6.4
6.5

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	2 seconds
R Server	'Gwilym Jenkins' @ 72.249.127.135

\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 & 2 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=28702&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]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=28702&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=28702&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	2 seconds
R Server	'Gwilym Jenkins' @ 72.249.127.135

Standard Deviation-Mean Plot
Section	Mean	Standard Deviation	Range
1	7.55833333333333	0.599178730860126	1.7
2	7.60833333333333	0.235326980770986	0.9
3	7.68333333333333	0.514928650544437	1.6
4	6.875	0.226133508433323	0.8
5	6.36666666666667	0.283912064918102	0.9

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 7.55833333333333 & 0.599178730860126 & 1.7 \tabularnewline
2 & 7.60833333333333 & 0.235326980770986 & 0.9 \tabularnewline
3 & 7.68333333333333 & 0.514928650544437 & 1.6 \tabularnewline
4 & 6.875 & 0.226133508433323 & 0.8 \tabularnewline
5 & 6.36666666666667 & 0.283912064918102 & 0.9 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=28702&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]7.55833333333333[/C][C]0.599178730860126[/C][C]1.7[/C][/ROW]
[ROW][C]2[/C][C]7.60833333333333[/C][C]0.235326980770986[/C][C]0.9[/C][/ROW]
[ROW][C]3[/C][C]7.68333333333333[/C][C]0.514928650544437[/C][C]1.6[/C][/ROW]
[ROW][C]4[/C][C]6.875[/C][C]0.226133508433323[/C][C]0.8[/C][/ROW]
[ROW][C]5[/C][C]6.36666666666667[/C][C]0.283912064918102[/C][C]0.9[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=28702&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=28702&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	7.55833333333333	0.599178730860126	1.7
2	7.60833333333333	0.235326980770986	0.9
3	7.68333333333333	0.514928650544437	1.6
4	6.875	0.226133508433323	0.8
5	6.36666666666667	0.283912064918102	0.9

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	-0.80022615809304
beta	0.162381271558315
S.D.	0.145908196282867
T-STAT	1.11290027356319
p-value	0.34690022641105

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -0.80022615809304 \tabularnewline
beta & 0.162381271558315 \tabularnewline
S.D. & 0.145908196282867 \tabularnewline
T-STAT & 1.11290027356319 \tabularnewline
p-value & 0.34690022641105 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=28702&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-0.80022615809304[/C][/ROW]
[ROW][C]beta[/C][C]0.162381271558315[/C][/ROW]
[ROW][C]S.D.[/C][C]0.145908196282867[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.11290027356319[/C][/ROW]
[ROW][C]p-value[/C][C]0.34690022641105[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=28702&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=28702&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	-0.80022615809304
beta	0.162381271558315
S.D.	0.145908196282867
T-STAT	1.11290027356319
p-value	0.34690022641105

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	-6.59511747506495
beta	2.79710235674929
S.D.	2.76590452368847
T-STAT	1.01127943238591
p-value	0.386364465024087
Lambda	-1.79710235674929

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -6.59511747506495 \tabularnewline
beta & 2.79710235674929 \tabularnewline
S.D. & 2.76590452368847 \tabularnewline
T-STAT & 1.01127943238591 \tabularnewline
p-value & 0.386364465024087 \tabularnewline
Lambda & -1.79710235674929 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=28702&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-6.59511747506495[/C][/ROW]
[ROW][C]beta[/C][C]2.79710235674929[/C][/ROW]
[ROW][C]S.D.[/C][C]2.76590452368847[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.01127943238591[/C][/ROW]
[ROW][C]p-value[/C][C]0.386364465024087[/C][/ROW]
[ROW][C]Lambda[/C][C]-1.79710235674929[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=28702&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=28702&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	-6.59511747506495
beta	2.79710235674929
S.D.	2.76590452368847
T-STAT	1.01127943238591
p-value	0.386364465024087
Lambda	-1.79710235674929

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