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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, 08 Aug 2013 11:09:30 -0400

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/2013/Aug/08/t13759746135441dtka27k20z1.htm/, Retrieved Mon, 29 Apr 2024 13:44:41 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=211006, Retrieved Mon, 29 Apr 2024 13:44:41 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Nick Hollevoet

Estimated Impact

190

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

-       [Standard Deviation-Mean Plot] [TIJDREEKS (B) - S...] [2013-08-08 15:09:30] [3f9aa5867cfe47c4a12580af2904c765] [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	'Gwilym Jenkins' @ jenkins.wessa.net

\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 & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=211006&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]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=211006&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=211006&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	'Gwilym Jenkins' @ jenkins.wessa.net

Standard Deviation-Mean Plot
Section	Mean	Standard Deviation	Range
1	1742.5	217.260840298644	810
2	1697.5	296.283801293778	1080
3	1625	317.962261911693	1050
4	1640	348.294546194871	1290
5	1627.5	411.562985348647	1380
6	1675	414.27922072833	1380
7	1707.5	405.62241734715	1500
8	1727.5	435.767348269902	1500
9	1715	475.346763378637	1680

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 1742.5 & 217.260840298644 & 810 \tabularnewline
2 & 1697.5 & 296.283801293778 & 1080 \tabularnewline
3 & 1625 & 317.962261911693 & 1050 \tabularnewline
4 & 1640 & 348.294546194871 & 1290 \tabularnewline
5 & 1627.5 & 411.562985348647 & 1380 \tabularnewline
6 & 1675 & 414.27922072833 & 1380 \tabularnewline
7 & 1707.5 & 405.62241734715 & 1500 \tabularnewline
8 & 1727.5 & 435.767348269902 & 1500 \tabularnewline
9 & 1715 & 475.346763378637 & 1680 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=211006&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]1742.5[/C][C]217.260840298644[/C][C]810[/C][/ROW]
[ROW][C]2[/C][C]1697.5[/C][C]296.283801293778[/C][C]1080[/C][/ROW]
[ROW][C]3[/C][C]1625[/C][C]317.962261911693[/C][C]1050[/C][/ROW]
[ROW][C]4[/C][C]1640[/C][C]348.294546194871[/C][C]1290[/C][/ROW]
[ROW][C]5[/C][C]1627.5[/C][C]411.562985348647[/C][C]1380[/C][/ROW]
[ROW][C]6[/C][C]1675[/C][C]414.27922072833[/C][C]1380[/C][/ROW]
[ROW][C]7[/C][C]1707.5[/C][C]405.62241734715[/C][C]1500[/C][/ROW]
[ROW][C]8[/C][C]1727.5[/C][C]435.767348269902[/C][C]1500[/C][/ROW]
[ROW][C]9[/C][C]1715[/C][C]475.346763378637[/C][C]1680[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=211006&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=211006&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	1742.5	217.260840298644	810
2	1697.5	296.283801293778	1080
3	1625	317.962261911693	1050
4	1640	348.294546194871	1290
5	1627.5	411.562985348647	1380
6	1675	414.27922072833	1380
7	1707.5	405.62241734715	1500
8	1727.5	435.767348269902	1500
9	1715	475.346763378637	1680

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	550.114227845169
beta	-0.107448317059863
S.D.	0.68875700161761
T-STAT	-0.156003230177712
p-value	0.880434120508983

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 550.114227845169 \tabularnewline
beta & -0.107448317059863 \tabularnewline
S.D. & 0.68875700161761 \tabularnewline
T-STAT & -0.156003230177712 \tabularnewline
p-value & 0.880434120508983 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=211006&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]550.114227845169[/C][/ROW]
[ROW][C]beta[/C][C]-0.107448317059863[/C][/ROW]
[ROW][C]S.D.[/C][C]0.68875700161761[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.156003230177712[/C][/ROW]
[ROW][C]p-value[/C][C]0.880434120508983[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=211006&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=211006&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	550.114227845169
beta	-0.107448317059863
S.D.	0.68875700161761
T-STAT	-0.156003230177712
p-value	0.880434120508983

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	15.5168295679875
beta	-1.29633550728114
S.D.	3.45582772786273
T-STAT	-0.375115778147559
p-value	0.718681736243623
Lambda	2.29633550728114

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 15.5168295679875 \tabularnewline
beta & -1.29633550728114 \tabularnewline
S.D. & 3.45582772786273 \tabularnewline
T-STAT & -0.375115778147559 \tabularnewline
p-value & 0.718681736243623 \tabularnewline
Lambda & 2.29633550728114 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=211006&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]15.5168295679875[/C][/ROW]
[ROW][C]beta[/C][C]-1.29633550728114[/C][/ROW]
[ROW][C]S.D.[/C][C]3.45582772786273[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.375115778147559[/C][/ROW]
[ROW][C]p-value[/C][C]0.718681736243623[/C][/ROW]
[ROW][C]Lambda[/C][C]2.29633550728114[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=211006&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=211006&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	15.5168295679875
beta	-1.29633550728114
S.D.	3.45582772786273
T-STAT	-0.375115778147559
p-value	0.718681736243623
Lambda	2.29633550728114

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