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Author's title

Author

*Unverified author*

R Software Module

rwasp_smp.wasp

Title produced by software

Standard Deviation-Mean Plot

Date of computation

Sun, 18 May 2008 10:05:02 -0600

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/May/18/t1211126741ozhm3rk4klgeezc.htm/, Retrieved Sun, 19 May 2024 11:51:52 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=12774, Retrieved Sun, 19 May 2024 11:51:52 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

147

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

-       [Standard Deviation-Mean Plot] [spreidings en gem...] [2008-05-18 16:05:02] [56744542a24c8707256dac9921ca917a] [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	1 seconds
R Server	'George Udny Yule' @ 72.249.76.132

\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 & 1 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=12774&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]1 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=12774&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=12774&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	1 seconds
R Server	'George Udny Yule' @ 72.249.76.132

Standard Deviation-Mean Plot
Section	Mean	Standard Deviation	Range
1	3478.16666666667	1555.29475916264	5100
2	3864.16666666667	1900.88375778375	6598
3	4337.66666666667	2119.88911945599	7681
4	5016	2380.61600125987	9008
5	5370.58333333333	2723.36708233604	9608
6	5469.33333333333	3541.36754102226	12095

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 3478.16666666667 & 1555.29475916264 & 5100 \tabularnewline
2 & 3864.16666666667 & 1900.88375778375 & 6598 \tabularnewline
3 & 4337.66666666667 & 2119.88911945599 & 7681 \tabularnewline
4 & 5016 & 2380.61600125987 & 9008 \tabularnewline
5 & 5370.58333333333 & 2723.36708233604 & 9608 \tabularnewline
6 & 5469.33333333333 & 3541.36754102226 & 12095 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=12774&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]3478.16666666667[/C][C]1555.29475916264[/C][C]5100[/C][/ROW]
[ROW][C]2[/C][C]3864.16666666667[/C][C]1900.88375778375[/C][C]6598[/C][/ROW]
[ROW][C]3[/C][C]4337.66666666667[/C][C]2119.88911945599[/C][C]7681[/C][/ROW]
[ROW][C]4[/C][C]5016[/C][C]2380.61600125987[/C][C]9008[/C][/ROW]
[ROW][C]5[/C][C]5370.58333333333[/C][C]2723.36708233604[/C][C]9608[/C][/ROW]
[ROW][C]6[/C][C]5469.33333333333[/C][C]3541.36754102226[/C][C]12095[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=12774&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=12774&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	3478.16666666667	1555.29475916264	5100
2	3864.16666666667	1900.88375778375	6598
3	4337.66666666667	2119.88911945599	7681
4	5016	2380.61600125987	9008
5	5370.58333333333	2723.36708233604	9608
6	5469.33333333333	3541.36754102226	12095

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	-1175.68716269817
beta	0.772646921283157
S.D.	0.175821308034232
T-STAT	4.39450104155023
p-value	0.0117413560802341

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -1175.68716269817 \tabularnewline
beta & 0.772646921283157 \tabularnewline
S.D. & 0.175821308034232 \tabularnewline
T-STAT & 4.39450104155023 \tabularnewline
p-value & 0.0117413560802341 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=12774&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-1175.68716269817[/C][/ROW]
[ROW][C]beta[/C][C]0.772646921283157[/C][/ROW]
[ROW][C]S.D.[/C][C]0.175821308034232[/C][/ROW]
[ROW][C]T-STAT[/C][C]4.39450104155023[/C][/ROW]
[ROW][C]p-value[/C][C]0.0117413560802341[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=12774&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=12774&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	-1175.68716269817
beta	0.772646921283157
S.D.	0.175821308034232
T-STAT	4.39450104155023
p-value	0.0117413560802341

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	-4.54939264546004
beta	1.45950305504561
S.D.	0.258457155220679
T-STAT	5.64698258711176
p-value	0.00484326493756996
Lambda	-0.459503055045614

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -4.54939264546004 \tabularnewline
beta & 1.45950305504561 \tabularnewline
S.D. & 0.258457155220679 \tabularnewline
T-STAT & 5.64698258711176 \tabularnewline
p-value & 0.00484326493756996 \tabularnewline
Lambda & -0.459503055045614 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=12774&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-4.54939264546004[/C][/ROW]
[ROW][C]beta[/C][C]1.45950305504561[/C][/ROW]
[ROW][C]S.D.[/C][C]0.258457155220679[/C][/ROW]
[ROW][C]T-STAT[/C][C]5.64698258711176[/C][/ROW]
[ROW][C]p-value[/C][C]0.00484326493756996[/C][/ROW]
[ROW][C]Lambda[/C][C]-0.459503055045614[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=12774&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=12774&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	-4.54939264546004
beta	1.45950305504561
S.D.	0.258457155220679
T-STAT	5.64698258711176
p-value	0.00484326493756996
Lambda	-0.459503055045614

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