Repository of Reproducible Computations

Free Statistics

of Irreproducible Research!

Author's title

Author

*Unverified author*

R Software Module

rwasp_smp.wasp

Title produced by software

Standard Deviation-Mean Plot

Date of computation

Tue, 09 Dec 2008 14:54:11 -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/09/t1228859695iil1s0selt3ak2s.htm/, Retrieved Sun, 19 May 2024 08:50:58 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=31820, Retrieved Sun, 19 May 2024 08:50:58 +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

Estimated Impact

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

-     [Univariate Data Series] [data set] [2008-12-01 19:54:57] [b98453cac15ba1066b407e146608df68]
F RMPD    [Standard Deviation-Mean Plot] [Identification an...] [2008-12-09 21:54:11] [74a138e5b32af267311b5ad4cd13bf7e] [Current]
-    D      [Standard Deviation-Mean Plot] [Paper SMP] [2008-12-24 13:33:03] [1a689e9ccc515e1757f0522229a687e9] 
- RMPD      [Multiple Regression] [Paper Multiple Re...] [2008-12-24 13:43:47] [1a689e9ccc515e1757f0522229a687e9] 
-    D        [Multiple Regression] [Paper Multiple Re...] [2008-12-24 13:50:10] [1a689e9ccc515e1757f0522229a687e9] 

Feedback Forum

2008-12-14 14:24:54 [Gert-Jan Geudens] [reply] 
Correcte interpretatie, maar foutieve conclusie. De p-waarde is inderdaad zeer hoog en dus is de transformatie nutteloos. Je mag lambda in de volgende stappen dus gelijk stellen aan 1.
2008-12-15 14:21:39 [Stefan Temmerman] [reply] 
Zoals de vorige student zei, de p-waarde is te groot waardoor de regressie van de standard deviation mean plot op het toeval berust, de lambda-waarde moet dus gelijk aan 1 gesteld worden.

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=31820&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=31820&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=31820&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	103.758333333333	5.38321606026687	16.6
2	106.491666666667	7.29264365749153	23.5
3	109.075	9.61203081370614	33.7
4	120.716666666667	10.2658155884942	33.1
5	135.125	11.9924313252530	42.4
6	146.466666666667	9.2324854659397	32.9
7	151.158333333333	7.98708711646872	28.1

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 103.758333333333 & 5.38321606026687 & 16.6 \tabularnewline
2 & 106.491666666667 & 7.29264365749153 & 23.5 \tabularnewline
3 & 109.075 & 9.61203081370614 & 33.7 \tabularnewline
4 & 120.716666666667 & 10.2658155884942 & 33.1 \tabularnewline
5 & 135.125 & 11.9924313252530 & 42.4 \tabularnewline
6 & 146.466666666667 & 9.2324854659397 & 32.9 \tabularnewline
7 & 151.158333333333 & 7.98708711646872 & 28.1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=31820&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]103.758333333333[/C][C]5.38321606026687[/C][C]16.6[/C][/ROW]
[ROW][C]2[/C][C]106.491666666667[/C][C]7.29264365749153[/C][C]23.5[/C][/ROW]
[ROW][C]3[/C][C]109.075[/C][C]9.61203081370614[/C][C]33.7[/C][/ROW]
[ROW][C]4[/C][C]120.716666666667[/C][C]10.2658155884942[/C][C]33.1[/C][/ROW]
[ROW][C]5[/C][C]135.125[/C][C]11.9924313252530[/C][C]42.4[/C][/ROW]
[ROW][C]6[/C][C]146.466666666667[/C][C]9.2324854659397[/C][C]32.9[/C][/ROW]
[ROW][C]7[/C][C]151.158333333333[/C][C]7.98708711646872[/C][C]28.1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=31820&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=31820&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	103.758333333333	5.38321606026687	16.6
2	106.491666666667	7.29264365749153	23.5
3	109.075	9.61203081370614	33.7
4	120.716666666667	10.2658155884942	33.1
5	135.125	11.9924313252530	42.4
6	146.466666666667	9.2324854659397	32.9
7	151.158333333333	7.98708711646872	28.1

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	3.34257580894819
beta	0.0439597223831378
S.D.	0.0449094490887782
T-STAT	0.978852408014114
p-value	0.372607334699310

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 3.34257580894819 \tabularnewline
beta & 0.0439597223831378 \tabularnewline
S.D. & 0.0449094490887782 \tabularnewline
T-STAT & 0.978852408014114 \tabularnewline
p-value & 0.372607334699310 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=31820&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]3.34257580894819[/C][/ROW]
[ROW][C]beta[/C][C]0.0439597223831378[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0449094490887782[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.978852408014114[/C][/ROW]
[ROW][C]p-value[/C][C]0.372607334699310[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=31820&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=31820&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	3.34257580894819
beta	0.0439597223831378
S.D.	0.0449094490887782
T-STAT	0.978852408014114
p-value	0.372607334699310

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	-1.64450009474418
beta	0.787918411387997
S.D.	0.662152751848072
T-STAT	1.18993451161973
p-value	0.287487665802382
Lambda	0.212081588612003

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -1.64450009474418 \tabularnewline
beta & 0.787918411387997 \tabularnewline
S.D. & 0.662152751848072 \tabularnewline
T-STAT & 1.18993451161973 \tabularnewline
p-value & 0.287487665802382 \tabularnewline
Lambda & 0.212081588612003 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=31820&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-1.64450009474418[/C][/ROW]
[ROW][C]beta[/C][C]0.787918411387997[/C][/ROW]
[ROW][C]S.D.[/C][C]0.662152751848072[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.18993451161973[/C][/ROW]
[ROW][C]p-value[/C][C]0.287487665802382[/C][/ROW]
[ROW][C]Lambda[/C][C]0.212081588612003[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=31820&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=31820&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	-1.64450009474418
beta	0.787918411387997
S.D.	0.662152751848072
T-STAT	1.18993451161973
p-value	0.287487665802382
Lambda	0.212081588612003

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