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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 computationTue, 15 Dec 2009 19:23:56 -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/16/t12609303152a5e01i25gt2dlc.htm/, Retrieved Tue, 30 Apr 2024 13:18:42 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=68217, Retrieved Tue, 30 Apr 2024 13:18:42 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact153
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Explorative Data Analysis] [Run Sequence gebo...] [2008-12-12 13:32:37] [76963dc1903f0f612b6153510a3818cf]
- R  D  [Univariate Explorative Data Analysis] [Run Sequence gebo...] [2008-12-17 12:14:40] [76963dc1903f0f612b6153510a3818cf]
-         [Univariate Explorative Data Analysis] [Run Sequence Plot...] [2008-12-22 18:19:51] [1ce0d16c8f4225c977b42c8fa93bc163]
- RMP       [Standard Deviation-Mean Plot] [Identifying Integ...] [2009-11-22 12:50:05] [b98453cac15ba1066b407e146608df68]
-    D        [Standard Deviation-Mean Plot] [Shwws8_v4] [2009-11-27 21:44:00] [5f89c040fdf1f8599c99d7f78a662321]
-   PD          [Standard Deviation-Mean Plot] [Paper] [2009-12-16 01:57:21] [5f89c040fdf1f8599c99d7f78a662321]
-    D              [Standard Deviation-Mean Plot] [Paper] [2009-12-16 02:23:56] [93b66894f6318f3da4fcda772f2ffa6f] [Current]
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Dataseries X:
1,226153808
1,226153808
1,168975899
1,208291812
1,226153808
1,198944113
1,189291568
1,17931089
1,135528369
1,110792234
1,147120647
1,158257019
1,110792234
1,123435982
1,123435982
1,123435982
1,053325834
1,053325834
1,053325834
1,036762412
1,068896991
1,168975899
1,234703632
1,251117312
1,281547755
1,28871661
1,340956389
1,322335636
1,380737173
1,416354029
1,421156497
1,396453607
1,401536772
1,364260913
1,259007596
1,217355482
1,158257019
1,135528369
0,903795442
0,931808694
-1,147122927
-1
-1,110793924
-0,931807741
-1
-0,979352648
0




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 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 & 3 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=68217&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]3 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=68217&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=68217&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 time3 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
11.181247831250.03821081695337280.115361574
21.1167944940.07110846762663150.2143549
31.340868204916670.06714313434045170.203801015000000

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 1.18124783125 & 0.0382108169533728 & 0.115361574 \tabularnewline
2 & 1.116794494 & 0.0711084676266315 & 0.2143549 \tabularnewline
3 & 1.34086820491667 & 0.0671431343404517 & 0.203801015000000 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=68217&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]1.18124783125[/C][C]0.0382108169533728[/C][C]0.115361574[/C][/ROW]
[ROW][C]2[/C][C]1.116794494[/C][C]0.0711084676266315[/C][C]0.2143549[/C][/ROW]
[ROW][C]3[/C][C]1.34086820491667[/C][C]0.0671431343404517[/C][C]0.203801015000000[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=68217&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=68217&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
11.181247831250.03821081695337280.115361574
21.1167944940.07110846762663150.2143549
31.340868204916670.06714313434045170.203801015000000







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha0.0343721312926888
beta0.0201560396812038
S.D.0.154369206117857
T-STAT0.130570339694661
p-value0.917343947127033

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 0.0343721312926888 \tabularnewline
beta & 0.0201560396812038 \tabularnewline
S.D. & 0.154369206117857 \tabularnewline
T-STAT & 0.130570339694661 \tabularnewline
p-value & 0.917343947127033 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=68217&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]0.0343721312926888[/C][/ROW]
[ROW][C]beta[/C][C]0.0201560396812038[/C][/ROW]
[ROW][C]S.D.[/C][C]0.154369206117857[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.130570339694661[/C][/ROW]
[ROW][C]p-value[/C][C]0.917343947127033[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=68217&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=68217&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)
alpha0.0343721312926888
beta0.0201560396812038
S.D.0.154369206117857
T-STAT0.130570339694661
p-value0.917343947127033







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-2.9639786476635
beta0.495873145993471
S.D.3.63030844044148
T-STAT0.136592566204421
p-value0.913577301288317
Lambda0.504126854006529

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -2.9639786476635 \tabularnewline
beta & 0.495873145993471 \tabularnewline
S.D. & 3.63030844044148 \tabularnewline
T-STAT & 0.136592566204421 \tabularnewline
p-value & 0.913577301288317 \tabularnewline
Lambda & 0.504126854006529 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=68217&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-2.9639786476635[/C][/ROW]
[ROW][C]beta[/C][C]0.495873145993471[/C][/ROW]
[ROW][C]S.D.[/C][C]3.63030844044148[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.136592566204421[/C][/ROW]
[ROW][C]p-value[/C][C]0.913577301288317[/C][/ROW]
[ROW][C]Lambda[/C][C]0.504126854006529[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=68217&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=68217&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-2.9639786476635
beta0.495873145993471
S.D.3.63030844044148
T-STAT0.136592566204421
p-value0.913577301288317
Lambda0.504126854006529



Parameters (Session):
par1 = 1 ; par2 = 1 ; par3 = 1 ; par4 = 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')