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Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationFri, 18 Dec 2009 12:32:26 -0700
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2009/Dec/18/t1261164798tmalhdpi6z72ya1.htm/, Retrieved Sat, 27 Apr 2024 06:58:16 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=69443, Retrieved Sat, 27 Apr 2024 06:58:16 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact136
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Standard Deviation-Mean Plot] [Standard deviatio...] [2008-12-11 16:40:34] [12d343c4448a5f9e527bb31caeac580b]
-  M D    [Standard Deviation-Mean Plot] [Standard Deviatio...] [2009-12-18 19:32:26] [d45d8d97b86162be82506c3c0ea6e4a6] [Current]
-    D      [Standard Deviation-Mean Plot] [Standard Deviatio...] [2009-12-21 13:17:50] [976efdaed7598845c859b86bc2e467ce]
-    D      [Standard Deviation-Mean Plot] [Standard Deviatio...] [2009-12-21 14:42:25] [ae69f4b008b5eaa8ebe185637a6eee4e]
- RMPD      [(Partial) Autocorrelation Function] [Autocorrelatie fu...] [2009-12-21 15:27:36] [ae69f4b008b5eaa8ebe185637a6eee4e]
-   P         [(Partial) Autocorrelation Function] [Autocorrelatie en...] [2009-12-21 16:53:21] [ae69f4b008b5eaa8ebe185637a6eee4e]
-   P           [(Partial) Autocorrelation Function] [Autocorrelatie fu...] [2009-12-21 17:00:29] [ae69f4b008b5eaa8ebe185637a6eee4e]
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Dataseries X:
12.1
12
11.8
12.7
12.3
11.9
12
12.3
12.8
12.4
12.3
12.7
12.7
12.9
13
12.2
12.3
12.8
12.8
12.8
12.2
12.6
12.8
12.5
12.4
12.3
11.9
11.7
12
12.1
11.7
11.8
11.8
11.8
11.3
11.3
11.3
11.2
11.4
12.2
12.9
13.1
13.5
13.6
14.4
14.1
15.1
15.8
15.9
15.4
15.5
14.8
13.2
12.7
12.1
11.9
10.6
10.7
9.8
9
8.3
9.3
9
9.1
10




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135

\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' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=69443&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' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=69443&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=69443&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 Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
112.2750.3306330017076061
212.63333333333330.2741377667369370.8
311.84166666666670.3369875458538581.1
413.21666666666671.502018843443924.6
512.63333333333332.364253998557896.9

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 12.275 & 0.330633001707606 & 1 \tabularnewline
2 & 12.6333333333333 & 0.274137766736937 & 0.8 \tabularnewline
3 & 11.8416666666667 & 0.336987545853858 & 1.1 \tabularnewline
4 & 13.2166666666667 & 1.50201884344392 & 4.6 \tabularnewline
5 & 12.6333333333333 & 2.36425399855789 & 6.9 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=69443&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]12.275[/C][C]0.330633001707606[/C][C]1[/C][/ROW]
[ROW][C]2[/C][C]12.6333333333333[/C][C]0.274137766736937[/C][C]0.8[/C][/ROW]
[ROW][C]3[/C][C]11.8416666666667[/C][C]0.336987545853858[/C][C]1.1[/C][/ROW]
[ROW][C]4[/C][C]13.2166666666667[/C][C]1.50201884344392[/C][C]4.6[/C][/ROW]
[ROW][C]5[/C][C]12.6333333333333[/C][C]2.36425399855789[/C][C]6.9[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=69443&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=69443&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
SectionMeanStandard DeviationRange
112.2750.3306330017076061
212.63333333333330.2741377667369370.8
311.84166666666670.3369875458538581.1
413.21666666666671.502018843443924.6
512.63333333333332.364253998557896.9







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-11.6146658286644
beta1.00449457347639
S.D.0.89533090592947
T-STAT1.12192549907969
p-value0.343592290628115

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -11.6146658286644 \tabularnewline
beta & 1.00449457347639 \tabularnewline
S.D. & 0.89533090592947 \tabularnewline
T-STAT & 1.12192549907969 \tabularnewline
p-value & 0.343592290628115 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=69443&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-11.6146658286644[/C][/ROW]
[ROW][C]beta[/C][C]1.00449457347639[/C][/ROW]
[ROW][C]S.D.[/C][C]0.89533090592947[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.12192549907969[/C][/ROW]
[ROW][C]p-value[/C][C]0.343592290628115[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=69443&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=69443&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-11.6146658286644
beta1.00449457347639
S.D.0.89533090592947
T-STAT1.12192549907969
p-value0.343592290628115







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-38.4709429813567
beta15.0501234602525
S.D.11.2711639921533
T-STAT1.33527677094664
p-value0.274062345359740
Lambda-14.0501234602525

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -38.4709429813567 \tabularnewline
beta & 15.0501234602525 \tabularnewline
S.D. & 11.2711639921533 \tabularnewline
T-STAT & 1.33527677094664 \tabularnewline
p-value & 0.274062345359740 \tabularnewline
Lambda & -14.0501234602525 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=69443&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-38.4709429813567[/C][/ROW]
[ROW][C]beta[/C][C]15.0501234602525[/C][/ROW]
[ROW][C]S.D.[/C][C]11.2711639921533[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.33527677094664[/C][/ROW]
[ROW][C]p-value[/C][C]0.274062345359740[/C][/ROW]
[ROW][C]Lambda[/C][C]-14.0501234602525[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=69443&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=69443&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-38.4709429813567
beta15.0501234602525
S.D.11.2711639921533
T-STAT1.33527677094664
p-value0.274062345359740
Lambda-14.0501234602525



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')