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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

Tue, 27 Nov 2007 04:11:44 -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/27/t1196161779lbiofzg7v1zci1s.htm/, Retrieved Sun, 05 May 2024 13:00:12 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=6853, Retrieved Sun, 05 May 2024 13:00:12 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

afzetprijzen in de bedrijfstak Tinne Van der Eycken

Estimated Impact

182

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

-       [Standard Deviation-Mean Plot] [Workshop 3] [2007-11-27 11:11:44] [c8635c97647ba59406cb570a9fab7b02] [Current]

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Boxplots

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	'Gwilym Jenkins' @ 72.249.127.135

\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 & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=6853&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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=6853&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6853&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	'Gwilym Jenkins' @ 72.249.127.135

Standard Deviation-Mean Plot
Section	Mean	Standard Deviation	Range
1	96.7916666666667	1.58542127084905	7.2
2	93.3416666666667	0.287491765362967	2
3	92.6666666666667	0.459907764138802	1.20000000000000
4	92.45	0.375378596764774	1
5	93.3583333333333	0.533357007050342	1.20000000000000

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 96.7916666666667 & 1.58542127084905 & 7.2 \tabularnewline
2 & 93.3416666666667 & 0.287491765362967 & 2 \tabularnewline
3 & 92.6666666666667 & 0.459907764138802 & 1.20000000000000 \tabularnewline
4 & 92.45 & 0.375378596764774 & 1 \tabularnewline
5 & 93.3583333333333 & 0.533357007050342 & 1.20000000000000 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=6853&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]96.7916666666667[/C][C]1.58542127084905[/C][C]7.2[/C][/ROW]
[ROW][C]2[/C][C]93.3416666666667[/C][C]0.287491765362967[/C][C]2[/C][/ROW]
[ROW][C]3[/C][C]92.6666666666667[/C][C]0.459907764138802[/C][C]1.20000000000000[/C][/ROW]
[ROW][C]4[/C][C]92.45[/C][C]0.375378596764774[/C][C]1[/C][/ROW]
[ROW][C]5[/C][C]93.3583333333333[/C][C]0.533357007050342[/C][C]1.20000000000000[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=6853&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6853&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	96.7916666666667	1.58542127084905	7.2
2	93.3416666666667	0.287491765362967	2
3	92.6666666666667	0.459907764138802	1.20000000000000
4	92.45	0.375378596764774	1
5	93.3583333333333	0.533357007050342	1.20000000000000

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	-26.5047660162713
beta	0.289720384440857
S.D.	0.0486024466216708
T-STAT	5.96102469277085
p-value	0.0094443003988611

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -26.5047660162713 \tabularnewline
beta & 0.289720384440857 \tabularnewline
S.D. & 0.0486024466216708 \tabularnewline
T-STAT & 5.96102469277085 \tabularnewline
p-value & 0.0094443003988611 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=6853&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-26.5047660162713[/C][/ROW]
[ROW][C]beta[/C][C]0.289720384440857[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0486024466216708[/C][/ROW]
[ROW][C]T-STAT[/C][C]5.96102469277085[/C][/ROW]
[ROW][C]p-value[/C][C]0.0094443003988611[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=6853&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6853&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	-26.5047660162713
beta	0.289720384440857
S.D.	0.0486024466216708
T-STAT	5.96102469277085
p-value	0.0094443003988611

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	-145.170676912273
beta	31.8349046380551
S.D.	8.63880034277244
T-STAT	3.68510711845418
p-value	0.0346340462571735
Lambda	-30.8349046380551

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -145.170676912273 \tabularnewline
beta & 31.8349046380551 \tabularnewline
S.D. & 8.63880034277244 \tabularnewline
T-STAT & 3.68510711845418 \tabularnewline
p-value & 0.0346340462571735 \tabularnewline
Lambda & -30.8349046380551 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=6853&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-145.170676912273[/C][/ROW]
[ROW][C]beta[/C][C]31.8349046380551[/C][/ROW]
[ROW][C]S.D.[/C][C]8.63880034277244[/C][/ROW]
[ROW][C]T-STAT[/C][C]3.68510711845418[/C][/ROW]
[ROW][C]p-value[/C][C]0.0346340462571735[/C][/ROW]
[ROW][C]Lambda[/C][C]-30.8349046380551[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=6853&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6853&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	-145.170676912273
beta	31.8349046380551
S.D.	8.63880034277244
T-STAT	3.68510711845418
p-value	0.0346340462571735
Lambda	-30.8349046380551

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