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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

Fri, 10 Dec 2010 16:44:50 +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/10/t1291999524ceh2oedadzoc5vo.htm/, Retrieved Mon, 29 Apr 2024 14:44:25 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=107828, Retrieved Mon, 29 Apr 2024 14:44:25 +0000

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IsPrivate?

No (this computation is public)

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Estimated Impact

106

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

-       [Standard Deviation-Mean Plot] [paper SDMP] [2010-12-10 16:44:50] [5842cf9dd57f9603e676e11284d3404a] [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=107828&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=107828&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=107828&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	591.666666666667	20.5264057577875	60
2	536.166666666667	22.0323453682136	66
3	504.75	19.4848425939008	65
4	549.75	26.9076704170526	81
5	569.25	21.4904841520825	67

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 591.666666666667 & 20.5264057577875 & 60 \tabularnewline
2 & 536.166666666667 & 22.0323453682136 & 66 \tabularnewline
3 & 504.75 & 19.4848425939008 & 65 \tabularnewline
4 & 549.75 & 26.9076704170526 & 81 \tabularnewline
5 & 569.25 & 21.4904841520825 & 67 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=107828&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]591.666666666667[/C][C]20.5264057577875[/C][C]60[/C][/ROW]
[ROW][C]2[/C][C]536.166666666667[/C][C]22.0323453682136[/C][C]66[/C][/ROW]
[ROW][C]3[/C][C]504.75[/C][C]19.4848425939008[/C][C]65[/C][/ROW]
[ROW][C]4[/C][C]549.75[/C][C]26.9076704170526[/C][C]81[/C][/ROW]
[ROW][C]5[/C][C]569.25[/C][C]21.4904841520825[/C][C]67[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=107828&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=107828&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	591.666666666667	20.5264057577875	60
2	536.166666666667	22.0323453682136	66
3	504.75	19.4848425939008	65
4	549.75	26.9076704170526	81
5	569.25	21.4904841520825	67

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	16.9224406860806
beta	0.00938715703999549
S.D.	0.0498715487098561
T-STAT	0.188226700049126
p-value	0.862711508268087

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 16.9224406860806 \tabularnewline
beta & 0.00938715703999549 \tabularnewline
S.D. & 0.0498715487098561 \tabularnewline
T-STAT & 0.188226700049126 \tabularnewline
p-value & 0.862711508268087 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=107828&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]16.9224406860806[/C][/ROW]
[ROW][C]beta[/C][C]0.00938715703999549[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0498715487098561[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.188226700049126[/C][/ROW]
[ROW][C]p-value[/C][C]0.862711508268087[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=107828&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=107828&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	16.9224406860806
beta	0.00938715703999549
S.D.	0.0498715487098561
T-STAT	0.188226700049126
p-value	0.862711508268087

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	1.17187150214472
beta	0.303834310393286
S.D.	1.16606057830207
T-STAT	0.260564773432017
p-value	0.811289769293068
Lambda	0.696165689606714

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 1.17187150214472 \tabularnewline
beta & 0.303834310393286 \tabularnewline
S.D. & 1.16606057830207 \tabularnewline
T-STAT & 0.260564773432017 \tabularnewline
p-value & 0.811289769293068 \tabularnewline
Lambda & 0.696165689606714 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=107828&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]1.17187150214472[/C][/ROW]
[ROW][C]beta[/C][C]0.303834310393286[/C][/ROW]
[ROW][C]S.D.[/C][C]1.16606057830207[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.260564773432017[/C][/ROW]
[ROW][C]p-value[/C][C]0.811289769293068[/C][/ROW]
[ROW][C]Lambda[/C][C]0.696165689606714[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=107828&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=107828&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	1.17187150214472
beta	0.303834310393286
S.D.	1.16606057830207
T-STAT	0.260564773432017
p-value	0.811289769293068
Lambda	0.696165689606714

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')

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Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code