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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

Tue, 28 Dec 2010 22:39:18 +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/2010/Dec/28/t12935758864y7mq7wdrxady89.htm/, Retrieved Sun, 05 May 2024 05:25:52 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=116571, Retrieved Sun, 05 May 2024 05:25:52 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

132

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

-       [Standard Deviation-Mean Plot] [Paper Standard de...] [2010-12-28 22:39:18] [a2e464febd5f86100a78930292e787b9] [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	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=116571&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=116571&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=116571&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	1278.91666666667	54.9271556176216	186
2	1049.33333333333	69.051144856987	233
3	768.666666666667	92.837427144379	272
4	482.166666666667	80.7969771411748	250
5	373.916666666667	24.6593457604482	69

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 1278.91666666667 & 54.9271556176216 & 186 \tabularnewline
2 & 1049.33333333333 & 69.051144856987 & 233 \tabularnewline
3 & 768.666666666667 & 92.837427144379 & 272 \tabularnewline
4 & 482.166666666667 & 80.7969771411748 & 250 \tabularnewline
5 & 373.916666666667 & 24.6593457604482 & 69 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=116571&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]1278.91666666667[/C][C]54.9271556176216[/C][C]186[/C][/ROW]
[ROW][C]2[/C][C]1049.33333333333[/C][C]69.051144856987[/C][C]233[/C][/ROW]
[ROW][C]3[/C][C]768.666666666667[/C][C]92.837427144379[/C][C]272[/C][/ROW]
[ROW][C]4[/C][C]482.166666666667[/C][C]80.7969771411748[/C][C]250[/C][/ROW]
[ROW][C]5[/C][C]373.916666666667[/C][C]24.6593457604482[/C][C]69[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=116571&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=116571&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	1278.91666666667	54.9271556176216	186
2	1049.33333333333	69.051144856987	233
3	768.666666666667	92.837427144379	272
4	482.166666666667	80.7969771411748	250
5	373.916666666667	24.6593457604482	69

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	54.1964331904668
beta	0.0129749265287823
S.D.	0.0393658932628555
T-STAT	0.329598173783219
p-value	0.763375526451557

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 54.1964331904668 \tabularnewline
beta & 0.0129749265287823 \tabularnewline
S.D. & 0.0393658932628555 \tabularnewline
T-STAT & 0.329598173783219 \tabularnewline
p-value & 0.763375526451557 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=116571&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]54.1964331904668[/C][/ROW]
[ROW][C]beta[/C][C]0.0129749265287823[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0393658932628555[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.329598173783219[/C][/ROW]
[ROW][C]p-value[/C][C]0.763375526451557[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=116571&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=116571&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	54.1964331904668
beta	0.0129749265287823
S.D.	0.0393658932628555
T-STAT	0.329598173783219
p-value	0.763375526451557

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	1.03344055329255
beta	0.462664139634841
S.D.	0.520681865650023
T-STAT	0.888573561242137
p-value	0.439686961639234
Lambda	0.537335860365159

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 1.03344055329255 \tabularnewline
beta & 0.462664139634841 \tabularnewline
S.D. & 0.520681865650023 \tabularnewline
T-STAT & 0.888573561242137 \tabularnewline
p-value & 0.439686961639234 \tabularnewline
Lambda & 0.537335860365159 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=116571&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]1.03344055329255[/C][/ROW]
[ROW][C]beta[/C][C]0.462664139634841[/C][/ROW]
[ROW][C]S.D.[/C][C]0.520681865650023[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.888573561242137[/C][/ROW]
[ROW][C]p-value[/C][C]0.439686961639234[/C][/ROW]
[ROW][C]Lambda[/C][C]0.537335860365159[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=116571&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=116571&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	1.03344055329255
beta	0.462664139634841
S.D.	0.520681865650023
T-STAT	0.888573561242137
p-value	0.439686961639234
Lambda	0.537335860365159

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

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Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code