Repository of Reproducible Computations

Free Statistics

of Irreproducible Research!

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

Mon, 01 Dec 2008 15:41:40 -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/01/t122817135256q6het7truy157.htm/, Retrieved Sun, 05 May 2024 20:00:50 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=27478, Retrieved Sun, 05 May 2024 20:00:50 +0000

QR Codes:

Paste this QR Code to cite your computation.

Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Non Stationary Time Series

Estimated Impact

178

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

-     [Standard Deviation-Mean Plot] [Q8] [2008-11-26 19:34:28] [8eb83367d7ce233bbf617141d324189b]
F         [Standard Deviation-Mean Plot] [question 8 Standa...] [2008-12-01 22:41:40] [3efbb18563b4564408d69b3c9a8e9a6e] [Current]

Feedback Forum

2008-12-08 07:50:27 [0762c65deec3d397cd9f26b3749a0847] [reply] 
je hebt de technieken goed toegepast. ook een goede conclusie gegevens maar het is puur toeval dat je voor beide reeksen dezelfde resultaten bekomt.
2008-12-09 07:45:10 [An De Koninck] [reply] 
Het berust inderdaad op toeval dat je hetzelfde resultaat bekomt. 
Wel goede berekeningen.

Post a new message

Dataseries X:

Download CSV

Histogram

Boxplots

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	'Sir Ronald Aylmer Fisher' @ 193.190.124.24

\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 & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=27478&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]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=27478&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=27478&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	'Sir Ronald Aylmer Fisher' @ 193.190.124.24

Standard Deviation-Mean Plot
Section	Mean	Standard Deviation	Range
1	3466.83333333333	395.964836210429	1460
2	3420.58333333333	459.323704103669	1324
3	3617.91666666667	362.524847633256	1132
4	4207.75	675.969892417218	2317
5	4688.83333333333	598.344964856977	1758
6	5180.83333333333	508.562293195835	1565
7	4604.08333333333	438.868681608713	1200

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 3466.83333333333 & 395.964836210429 & 1460 \tabularnewline
2 & 3420.58333333333 & 459.323704103669 & 1324 \tabularnewline
3 & 3617.91666666667 & 362.524847633256 & 1132 \tabularnewline
4 & 4207.75 & 675.969892417218 & 2317 \tabularnewline
5 & 4688.83333333333 & 598.344964856977 & 1758 \tabularnewline
6 & 5180.83333333333 & 508.562293195835 & 1565 \tabularnewline
7 & 4604.08333333333 & 438.868681608713 & 1200 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=27478&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]3466.83333333333[/C][C]395.964836210429[/C][C]1460[/C][/ROW]
[ROW][C]2[/C][C]3420.58333333333[/C][C]459.323704103669[/C][C]1324[/C][/ROW]
[ROW][C]3[/C][C]3617.91666666667[/C][C]362.524847633256[/C][C]1132[/C][/ROW]
[ROW][C]4[/C][C]4207.75[/C][C]675.969892417218[/C][C]2317[/C][/ROW]
[ROW][C]5[/C][C]4688.83333333333[/C][C]598.344964856977[/C][C]1758[/C][/ROW]
[ROW][C]6[/C][C]5180.83333333333[/C][C]508.562293195835[/C][C]1565[/C][/ROW]
[ROW][C]7[/C][C]4604.08333333333[/C][C]438.868681608713[/C][C]1200[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=27478&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=27478&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	3466.83333333333	395.964836210429	1460
2	3420.58333333333	459.323704103669	1324
3	3617.91666666667	362.524847633256	1132
4	4207.75	675.969892417218	2317
5	4688.83333333333	598.344964856977	1758
6	5180.83333333333	508.562293195835	1565
7	4604.08333333333	438.868681608713	1200

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	169.599696531845
beta	0.0771704596582882
S.D.	0.0641000346945755
T-STAT	1.20390667533943
p-value	0.282505976489347

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 169.599696531845 \tabularnewline
beta & 0.0771704596582882 \tabularnewline
S.D. & 0.0641000346945755 \tabularnewline
T-STAT & 1.20390667533943 \tabularnewline
p-value & 0.282505976489347 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=27478&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]169.599696531845[/C][/ROW]
[ROW][C]beta[/C][C]0.0771704596582882[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0641000346945755[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.20390667533943[/C][/ROW]
[ROW][C]p-value[/C][C]0.282505976489347[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=27478&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=27478&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	169.599696531845
beta	0.0771704596582882
S.D.	0.0641000346945755
T-STAT	1.20390667533943
p-value	0.282505976489347

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	0.217240027260564
beta	0.715832490241344
S.D.	0.508607271214527
T-STAT	1.40743660335798
p-value	0.218320004365828
Lambda	0.284167509758656

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 0.217240027260564 \tabularnewline
beta & 0.715832490241344 \tabularnewline
S.D. & 0.508607271214527 \tabularnewline
T-STAT & 1.40743660335798 \tabularnewline
p-value & 0.218320004365828 \tabularnewline
Lambda & 0.284167509758656 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=27478&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]0.217240027260564[/C][/ROW]
[ROW][C]beta[/C][C]0.715832490241344[/C][/ROW]
[ROW][C]S.D.[/C][C]0.508607271214527[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.40743660335798[/C][/ROW]
[ROW][C]p-value[/C][C]0.218320004365828[/C][/ROW]
[ROW][C]Lambda[/C][C]0.284167509758656[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=27478&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=27478&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	0.217240027260564
beta	0.715832490241344
S.D.	0.508607271214527
T-STAT	1.40743660335798
p-value	0.218320004365828
Lambda	0.284167509758656

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 ; par2 = ; par3 = ; par4 = ; par5 = ; par6 = ; par7 = ; par8 = ; par9 = ; par10 = ; par11 = ; par12 = ; par13 = ; par14 = ; par15 = ; par16 = ; par17 = ; par18 = ; par19 = ; par20 = ;

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