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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

Fri, 25 May 2012 06:17:23 -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/May/25/t1337941063jpd1rxda5f81zcp.htm/, Retrieved Sat, 04 May 2024 03:01:36 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=167459, Retrieved Sat, 04 May 2024 03:01:36 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

120

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

-     [Bootstrap Plot - Central Tendency] [maximumprijs stud...] [2012-05-25 08:42:57] [65d089efb1547052afcdc66fb34b47a2]
- RMPD  [Blocked Bootstrap Plot - Central Tendency] [werkloosheid in B...] [2012-05-25 08:58:17] [65d089efb1547052afcdc66fb34b47a2]
- RMP       [Standard Deviation-Mean Plot] [werkloosheid in B...] [2012-05-25 10:17:23] [50083fea611f0183deb36cab794727ad] [Current]

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Dataseries X:

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Boxplots

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	'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 & 1 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=167459&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]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=167459&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=167459&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	'Gwilym Jenkins' @ jenkins.wessa.net

Standard Deviation-Mean Plot
Section	Mean	Standard Deviation	Range
1	596.25	21.9757097310148	62
2	588.333333333333	22.7129651934482	69
3	532.583333333333	21.8318296960834	66
4	504.916666666667	19.5794806010287	65
5	554.666666666667	25.5354774002877	73
6	567.25	22.017038856304	67
7	546.583333333333	19.028487415802	62

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 596.25 & 21.9757097310148 & 62 \tabularnewline
2 & 588.333333333333 & 22.7129651934482 & 69 \tabularnewline
3 & 532.583333333333 & 21.8318296960834 & 66 \tabularnewline
4 & 504.916666666667 & 19.5794806010287 & 65 \tabularnewline
5 & 554.666666666667 & 25.5354774002877 & 73 \tabularnewline
6 & 567.25 & 22.017038856304 & 67 \tabularnewline
7 & 546.583333333333 & 19.028487415802 & 62 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=167459&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]596.25[/C][C]21.9757097310148[/C][C]62[/C][/ROW]
[ROW][C]2[/C][C]588.333333333333[/C][C]22.7129651934482[/C][C]69[/C][/ROW]
[ROW][C]3[/C][C]532.583333333333[/C][C]21.8318296960834[/C][C]66[/C][/ROW]
[ROW][C]4[/C][C]504.916666666667[/C][C]19.5794806010287[/C][C]65[/C][/ROW]
[ROW][C]5[/C][C]554.666666666667[/C][C]25.5354774002877[/C][C]73[/C][/ROW]
[ROW][C]6[/C][C]567.25[/C][C]22.017038856304[/C][C]67[/C][/ROW]
[ROW][C]7[/C][C]546.583333333333[/C][C]19.028487415802[/C][C]62[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=167459&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=167459&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	596.25	21.9757097310148	62
2	588.333333333333	22.7129651934482	69
3	532.583333333333	21.8318296960834	66
4	504.916666666667	19.5794806010287	65
5	554.666666666667	25.5354774002877	73
6	567.25	22.017038856304	67
7	546.583333333333	19.028487415802	62

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	5.90589021172702
beta	0.0286177541701663
S.D.	0.0273137018388511
T-STAT	1.04774352224422
p-value	0.342738819792065

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 5.90589021172702 \tabularnewline
beta & 0.0286177541701663 \tabularnewline
S.D. & 0.0273137018388511 \tabularnewline
T-STAT & 1.04774352224422 \tabularnewline
p-value & 0.342738819792065 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=167459&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]5.90589021172702[/C][/ROW]
[ROW][C]beta[/C][C]0.0286177541701663[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0273137018388511[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.04774352224422[/C][/ROW]
[ROW][C]p-value[/C][C]0.342738819792065[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=167459&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=167459&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	5.90589021172702
beta	0.0286177541701663
S.D.	0.0273137018388511
T-STAT	1.04774352224422
p-value	0.342738819792065

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	-1.77065926055758
beta	0.767372948782177
S.D.	0.673217599813102
T-STAT	1.13985871580781
p-value	0.305987960548001
Lambda	0.232627051217823

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -1.77065926055758 \tabularnewline
beta & 0.767372948782177 \tabularnewline
S.D. & 0.673217599813102 \tabularnewline
T-STAT & 1.13985871580781 \tabularnewline
p-value & 0.305987960548001 \tabularnewline
Lambda & 0.232627051217823 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=167459&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-1.77065926055758[/C][/ROW]
[ROW][C]beta[/C][C]0.767372948782177[/C][/ROW]
[ROW][C]S.D.[/C][C]0.673217599813102[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.13985871580781[/C][/ROW]
[ROW][C]p-value[/C][C]0.305987960548001[/C][/ROW]
[ROW][C]Lambda[/C][C]0.232627051217823[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=167459&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=167459&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	-1.77065926055758
beta	0.767372948782177
S.D.	0.673217599813102
T-STAT	1.13985871580781
p-value	0.305987960548001
Lambda	0.232627051217823

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