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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, 27 Nov 2009 06:25:22 -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/Nov/27/t1259328430q9r3sh9e7tx00vn.htm/, Retrieved Mon, 29 Apr 2024 22:15:54 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=60733, Retrieved Mon, 29 Apr 2024 22:15:54 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsshwws8vr9
Estimated Impact154
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]
- R  D          [Standard Deviation-Mean Plot] [] [2009-11-27 13:25:22] [4407d6264e55b051ec65750e6dca2820] [Current]
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Dataseries X:
15912,8
13866,5
17823,2
17872
17420,4
16704,4
15991,2
16583,6
19123,5
17838,7
17209,4
18586,5
16258,1
15141,6
19202,1
17746,5
19090,1
18040,3
17515,5
17751,8
21072,4
17170
19439,5
19795,4
17574,9
16165,4
19464,6
19932,1
19961,2
17343,4
18924,2
18574,1
21350,6
18594,6
19823,1
20844,4
19640,2
17735,4
19813,6
22160
20664,3
17877,4
20906,5
21164,1
21374,4
22952,3
21343,5
23899,3
22392,9
18274,1
22786,7
22321,5
17842,2
16373,5
15993,8
16446,1
17729
16643
16196,7
18252,1
17304




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 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 & 1 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60733&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' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=60733&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60733&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 time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
117077.68333333331401.140262807625257
218185.2751629.626272897625930.8
319046.051499.982528686135185.2
420794.251837.151874505756163.9
518437.63333333332576.157589523716792.9

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 17077.6833333333 & 1401.14026280762 & 5257 \tabularnewline
2 & 18185.275 & 1629.62627289762 & 5930.8 \tabularnewline
3 & 19046.05 & 1499.98252868613 & 5185.2 \tabularnewline
4 & 20794.25 & 1837.15187450575 & 6163.9 \tabularnewline
5 & 18437.6333333333 & 2576.15758952371 & 6792.9 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60733&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]17077.6833333333[/C][C]1401.14026280762[/C][C]5257[/C][/ROW]
[ROW][C]2[/C][C]18185.275[/C][C]1629.62627289762[/C][C]5930.8[/C][/ROW]
[ROW][C]3[/C][C]19046.05[/C][C]1499.98252868613[/C][C]5185.2[/C][/ROW]
[ROW][C]4[/C][C]20794.25[/C][C]1837.15187450575[/C][C]6163.9[/C][/ROW]
[ROW][C]5[/C][C]18437.6333333333[/C][C]2576.15758952371[/C][C]6792.9[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=60733&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60733&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
117077.68333333331401.140262807625257
218185.2751629.626272897625930.8
319046.051499.982528686135185.2
420794.251837.151874505756163.9
518437.63333333332576.157589523716792.9







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha522.792952365596
beta0.0676719416910218
S.D.0.194408257032624
T-STAT0.348091910929821
p-value0.750764637309087

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 522.792952365596 \tabularnewline
beta & 0.0676719416910218 \tabularnewline
S.D. & 0.194408257032624 \tabularnewline
T-STAT & 0.348091910929821 \tabularnewline
p-value & 0.750764637309087 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60733&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]522.792952365596[/C][/ROW]
[ROW][C]beta[/C][C]0.0676719416910218[/C][/ROW]
[ROW][C]S.D.[/C][C]0.194408257032624[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.348091910929821[/C][/ROW]
[ROW][C]p-value[/C][C]0.750764637309087[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=60733&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60733&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)
alpha522.792952365596
beta0.0676719416910218
S.D.0.194408257032624
T-STAT0.348091910929821
p-value0.750764637309087







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-1.52282991165830
beta0.913884623202932
S.D.1.84625083468930
T-STAT0.494994832788649
p-value0.654587829914546
Lambda0.0861153767970677

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -1.52282991165830 \tabularnewline
beta & 0.913884623202932 \tabularnewline
S.D. & 1.84625083468930 \tabularnewline
T-STAT & 0.494994832788649 \tabularnewline
p-value & 0.654587829914546 \tabularnewline
Lambda & 0.0861153767970677 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60733&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-1.52282991165830[/C][/ROW]
[ROW][C]beta[/C][C]0.913884623202932[/C][/ROW]
[ROW][C]S.D.[/C][C]1.84625083468930[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.494994832788649[/C][/ROW]
[ROW][C]p-value[/C][C]0.654587829914546[/C][/ROW]
[ROW][C]Lambda[/C][C]0.0861153767970677[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=60733&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60733&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-1.52282991165830
beta0.913884623202932
S.D.1.84625083468930
T-STAT0.494994832788649
p-value0.654587829914546
Lambda0.0861153767970677



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')