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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

Thu, 29 Nov 2007 02:15:42 -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/2007/Nov/29/t1196327555x3k4i6m1s7hf702.htm/, Retrieved Fri, 03 May 2024 10:01:15 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=7295, Retrieved Fri, 03 May 2024 10:01:15 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

249

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

-       [Standard Deviation-Mean Plot] [standard deviatio...] [2007-11-29 09:15:42] [5f37cd8ab253ad45d932eaa1e9b30ad5] [Current]

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Summary of compuational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	2 seconds
R Server	'Herman Ole Andreas Wold' @ 193.190.124.10:1001

\begin{tabular}{lllllllll}
\hline
Summary of compuational 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 & 'Herman Ole Andreas Wold' @ 193.190.124.10:1001 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=7295&T=0

[TABLE]
[ROW][C]Summary of compuational 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]'Herman Ole Andreas Wold' @ 193.190.124.10:1001[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=7295&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=7295&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 compuational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	2 seconds
R Server	'Herman Ole Andreas Wold' @ 193.190.124.10:1001

Standard Deviation-Mean Plot
Section	Mean	Standard Deviation	Range
1	108.808333333333	0.0288675134594838	0.100000000000009
2	114.666666666667	4.46589771761988	11.2
3	123.183333333333	2.39728381652438	19.5
4	128.016666666667	4.57877183479932	25.9

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 108.808333333333 & 0.0288675134594838 & 0.100000000000009 \tabularnewline
2 & 114.666666666667 & 4.46589771761988 & 11.2 \tabularnewline
3 & 123.183333333333 & 2.39728381652438 & 19.5 \tabularnewline
4 & 128.016666666667 & 4.57877183479932 & 25.9 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=7295&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]108.808333333333[/C][C]0.0288675134594838[/C][C]0.100000000000009[/C][/ROW]
[ROW][C]2[/C][C]114.666666666667[/C][C]4.46589771761988[/C][C]11.2[/C][/ROW]
[ROW][C]3[/C][C]123.183333333333[/C][C]2.39728381652438[/C][C]19.5[/C][/ROW]
[ROW][C]4[/C][C]128.016666666667[/C][C]4.57877183479932[/C][C]25.9[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=7295&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=7295&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	108.808333333333	0.0288675134594838	0.100000000000009
2	114.666666666667	4.46589771761988	11.2
3	123.183333333333	2.39728381652438	19.5
4	128.016666666667	4.57877183479932	25.9

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	-16.1760252030703
beta	0.16047805697516
S.D.	0.135123657087416
T-STAT	1.18763849672408
p-value	0.356903446577829

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -16.1760252030703 \tabularnewline
beta & 0.16047805697516 \tabularnewline
S.D. & 0.135123657087416 \tabularnewline
T-STAT & 1.18763849672408 \tabularnewline
p-value & 0.356903446577829 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=7295&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-16.1760252030703[/C][/ROW]
[ROW][C]beta[/C][C]0.16047805697516[/C][/ROW]
[ROW][C]S.D.[/C][C]0.135123657087416[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.18763849672408[/C][/ROW]
[ROW][C]p-value[/C][C]0.356903446577829[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=7295&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=7295&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	-16.1760252030703
beta	0.16047805697516
S.D.	0.135123657087416
T-STAT	1.18763849672408
p-value	0.356903446577829

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	-122.025120789873
beta	25.5765897191835
S.D.	15.3916548026816
T-STAT	1.66171799244922
p-value	0.238457326791838
Lambda	-24.5765897191835

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -122.025120789873 \tabularnewline
beta & 25.5765897191835 \tabularnewline
S.D. & 15.3916548026816 \tabularnewline
T-STAT & 1.66171799244922 \tabularnewline
p-value & 0.238457326791838 \tabularnewline
Lambda & -24.5765897191835 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=7295&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-122.025120789873[/C][/ROW]
[ROW][C]beta[/C][C]25.5765897191835[/C][/ROW]
[ROW][C]S.D.[/C][C]15.3916548026816[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.66171799244922[/C][/ROW]
[ROW][C]p-value[/C][C]0.238457326791838[/C][/ROW]
[ROW][C]Lambda[/C][C]-24.5765897191835[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=7295&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=7295&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	-122.025120789873
beta	25.5765897191835
S.D.	15.3916548026816
T-STAT	1.66171799244922
p-value	0.238457326791838
Lambda	-24.5765897191835

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

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Figures (Output of Computation)

Input Parameters & R Code