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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

Mon, 13 Aug 2012 12:23:53 -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/2012/Aug/13/t13448825579t8kbwtm1z2pqa8.htm/, Retrieved Sun, 28 Apr 2024 00:37:25 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=169297, Retrieved Sun, 28 Apr 2024 00:37:25 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Van Puyenbroeck Willem

Estimated Impact

158

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

-       [Standard Deviation-Mean Plot] [Tijdreeks 2 stap 21] [2012-08-13 16:23:53] [d94b10b2615af2e11b32dea0ad6a3c7b] [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=169297&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=169297&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=169297&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	1293.33333333333	71.7740562565273	220
2	1262.5	85.4001277410158	280
3	1250	89.3410218310614	300
4	1235	99.7724684196269	350
5	1243.33333333333	102.188180541706	370
6	1238.33333333333	117.22808640605	370
7	1227.5	114.425442180408	400
8	1235.83333333333	145.318354802221	440
9	1246.66666666667	156.863190730205	520

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 1293.33333333333 & 71.7740562565273 & 220 \tabularnewline
2 & 1262.5 & 85.4001277410158 & 280 \tabularnewline
3 & 1250 & 89.3410218310614 & 300 \tabularnewline
4 & 1235 & 99.7724684196269 & 350 \tabularnewline
5 & 1243.33333333333 & 102.188180541706 & 370 \tabularnewline
6 & 1238.33333333333 & 117.22808640605 & 370 \tabularnewline
7 & 1227.5 & 114.425442180408 & 400 \tabularnewline
8 & 1235.83333333333 & 145.318354802221 & 440 \tabularnewline
9 & 1246.66666666667 & 156.863190730205 & 520 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=169297&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]1293.33333333333[/C][C]71.7740562565273[/C][C]220[/C][/ROW]
[ROW][C]2[/C][C]1262.5[/C][C]85.4001277410158[/C][C]280[/C][/ROW]
[ROW][C]3[/C][C]1250[/C][C]89.3410218310614[/C][C]300[/C][/ROW]
[ROW][C]4[/C][C]1235[/C][C]99.7724684196269[/C][C]350[/C][/ROW]
[ROW][C]5[/C][C]1243.33333333333[/C][C]102.188180541706[/C][C]370[/C][/ROW]
[ROW][C]6[/C][C]1238.33333333333[/C][C]117.22808640605[/C][C]370[/C][/ROW]
[ROW][C]7[/C][C]1227.5[/C][C]114.425442180408[/C][C]400[/C][/ROW]
[ROW][C]8[/C][C]1235.83333333333[/C][C]145.318354802221[/C][C]440[/C][/ROW]
[ROW][C]9[/C][C]1246.66666666667[/C][C]156.863190730205[/C][C]520[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=169297&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=169297&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	1293.33333333333	71.7740562565273	220
2	1262.5	85.4001277410158	280
3	1250	89.3410218310614	300
4	1235	99.7724684196269	350
5	1243.33333333333	102.188180541706	370
6	1238.33333333333	117.22808640605	370
7	1227.5	114.425442180408	400
8	1235.83333333333	145.318354802221	440
9	1246.66666666667	156.863190730205	520

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	1153.53113701079
beta	-0.83681008717456
S.D.	0.426657972155665
T-STAT	-1.9613136089937
p-value	0.0906440837169654

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 1153.53113701079 \tabularnewline
beta & -0.83681008717456 \tabularnewline
S.D. & 0.426657972155665 \tabularnewline
T-STAT & -1.9613136089937 \tabularnewline
p-value & 0.0906440837169654 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=169297&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]1153.53113701079[/C][/ROW]
[ROW][C]beta[/C][C]-0.83681008717456[/C][/ROW]
[ROW][C]S.D.[/C][C]0.426657972155665[/C][/ROW]
[ROW][C]T-STAT[/C][C]-1.9613136089937[/C][/ROW]
[ROW][C]p-value[/C][C]0.0906440837169654[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=169297&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=169297&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	1153.53113701079
beta	-0.83681008717456
S.D.	0.426657972155665
T-STAT	-1.9613136089937
p-value	0.0906440837169654

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	82.5733404641941
beta	-10.9280691406542
S.D.	4.41003166766665
T-STAT	-2.4780024190702
p-value	0.0423337890254337
Lambda	11.9280691406542

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 82.5733404641941 \tabularnewline
beta & -10.9280691406542 \tabularnewline
S.D. & 4.41003166766665 \tabularnewline
T-STAT & -2.4780024190702 \tabularnewline
p-value & 0.0423337890254337 \tabularnewline
Lambda & 11.9280691406542 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=169297&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]82.5733404641941[/C][/ROW]
[ROW][C]beta[/C][C]-10.9280691406542[/C][/ROW]
[ROW][C]S.D.[/C][C]4.41003166766665[/C][/ROW]
[ROW][C]T-STAT[/C][C]-2.4780024190702[/C][/ROW]
[ROW][C]p-value[/C][C]0.0423337890254337[/C][/ROW]
[ROW][C]Lambda[/C][C]11.9280691406542[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=169297&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=169297&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	82.5733404641941
beta	-10.9280691406542
S.D.	4.41003166766665
T-STAT	-2.4780024190702
p-value	0.0423337890254337
Lambda	11.9280691406542

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