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

Tue, 16 Dec 2008 02:33:50 -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/16/t1229420229ihaua69sc8u178a.htm/, Retrieved Wed, 15 May 2024 17:07:58 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=33880, Retrieved Wed, 15 May 2024 17:07:58 +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

205

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

-       [Standard Deviation-Mean Plot] [SMP] [2008-12-16 09:33:50] [c4d631a082add458929a68f815b04b21] [Current]

Feedback Forum

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	4 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 & 4 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=33880&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]4 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=33880&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=33880&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	4 seconds
R Server	'Sir Ronald Aylmer Fisher' @ 193.190.124.24

Standard Deviation-Mean Plot
Section	Mean	Standard Deviation	Range
1	22932.4166666667	5566.33655367584	20000
2	23735.25	6529.31853780943	20890
3	22458.8333333333	5033.652078007	15936
4	23118.5	7012.69518282898	23808

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 22932.4166666667 & 5566.33655367584 & 20000 \tabularnewline
2 & 23735.25 & 6529.31853780943 & 20890 \tabularnewline
3 & 22458.8333333333 & 5033.652078007 & 15936 \tabularnewline
4 & 23118.5 & 7012.69518282898 & 23808 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=33880&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]22932.4166666667[/C][C]5566.33655367584[/C][C]20000[/C][/ROW]
[ROW][C]2[/C][C]23735.25[/C][C]6529.31853780943[/C][C]20890[/C][/ROW]
[ROW][C]3[/C][C]22458.8333333333[/C][C]5033.652078007[/C][C]15936[/C][/ROW]
[ROW][C]4[/C][C]23118.5[/C][C]7012.69518282898[/C][C]23808[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=33880&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=33880&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	22932.4166666667	5566.33655367584	20000
2	23735.25	6529.31853780943	20890
3	22458.8333333333	5033.652078007	15936
4	23118.5	7012.69518282898	23808

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	-22968.2137967701
beta	1.25768179889860
S.D.	0.810061616460982
T-STAT	1.55257547492893
p-value	0.260719466008783

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -22968.2137967701 \tabularnewline
beta & 1.25768179889860 \tabularnewline
S.D. & 0.810061616460982 \tabularnewline
T-STAT & 1.55257547492893 \tabularnewline
p-value & 0.260719466008783 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=33880&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-22968.2137967701[/C][/ROW]
[ROW][C]beta[/C][C]1.25768179889860[/C][/ROW]
[ROW][C]S.D.[/C][C]0.810061616460982[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.55257547492893[/C][/ROW]
[ROW][C]p-value[/C][C]0.260719466008783[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=33880&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=33880&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	-22968.2137967701
beta	1.25768179889860
S.D.	0.810061616460982
T-STAT	1.55257547492893
p-value	0.260719466008783

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	-41.848281264449
beta	5.03152584923966
S.D.	2.99995636353789
T-STAT	1.67719967876663
p-value	0.235501045988027
Lambda	-4.03152584923966

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -41.848281264449 \tabularnewline
beta & 5.03152584923966 \tabularnewline
S.D. & 2.99995636353789 \tabularnewline
T-STAT & 1.67719967876663 \tabularnewline
p-value & 0.235501045988027 \tabularnewline
Lambda & -4.03152584923966 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=33880&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-41.848281264449[/C][/ROW]
[ROW][C]beta[/C][C]5.03152584923966[/C][/ROW]
[ROW][C]S.D.[/C][C]2.99995636353789[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.67719967876663[/C][/ROW]
[ROW][C]p-value[/C][C]0.235501045988027[/C][/ROW]
[ROW][C]Lambda[/C][C]-4.03152584923966[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=33880&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=33880&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	-41.848281264449
beta	5.03152584923966
S.D.	2.99995636353789
T-STAT	1.67719967876663
p-value	0.235501045988027
Lambda	-4.03152584923966

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