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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 computationSun, 22 Nov 2009 08:55:09 -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/22/t12589053403pk09xig6pjvtkl.htm/, Retrieved Sun, 28 Apr 2024 16:58:37 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=58651, Retrieved Sun, 28 Apr 2024 16:58:37 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact208
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] [WS 8 30] [2009-11-22 15:55:09] [2e4ef2c1b76db9b31c0a03b96e94ad77] [Current]
-    D            [Standard Deviation-Mean Plot] [Paper heteroskeda...] [2010-12-21 11:22:29] [a9e130f95bad0a0597234e75c6380c5a]
-    D              [Standard Deviation-Mean Plot] [] [2011-12-20 19:19:22] [06f5daa9a1979410bf169cb7a41fb3eb]
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Dataseries X:
103,63
103,64
103,66
103,77
103,88
103,91
103,91
103,92
104,05
104,23
104,30
104,31
104,31
104,34
104,55
104,65
104,73
104,75
104,75
104,76
104,94
105,29
105,38
105,43
105,43
105,42
105,52
105,69
105,72
105,74
105,74
105,74
105,95
106,17
106,34
106,37
106,37
106,36
106,44
106,29
106,23
106,23
106,23
106,23
106,34
106,44
106,44
106,48
106,50
106,57
106,40
106,37
106,25
106,21
106,21
106,24
106,19
106,08
106,13
106,09




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=58651&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=58651&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=58651&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
1103.9341666666670.2452256227652540.680000000000007
2104.8233333333330.3735172707053201.12000000000000
3105.8191666666670.3248064691847180.950000000000003
4106.340.09620054809898480.25
5106.270.1574801574802370.489999999999995

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 103.934166666667 & 0.245225622765254 & 0.680000000000007 \tabularnewline
2 & 104.823333333333 & 0.373517270705320 & 1.12000000000000 \tabularnewline
3 & 105.819166666667 & 0.324806469184718 & 0.950000000000003 \tabularnewline
4 & 106.34 & 0.0962005480989848 & 0.25 \tabularnewline
5 & 106.27 & 0.157480157480237 & 0.489999999999995 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=58651&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]103.934166666667[/C][C]0.245225622765254[/C][C]0.680000000000007[/C][/ROW]
[ROW][C]2[/C][C]104.823333333333[/C][C]0.373517270705320[/C][C]1.12000000000000[/C][/ROW]
[ROW][C]3[/C][C]105.819166666667[/C][C]0.324806469184718[/C][C]0.950000000000003[/C][/ROW]
[ROW][C]4[/C][C]106.34[/C][C]0.0962005480989848[/C][C]0.25[/C][/ROW]
[ROW][C]5[/C][C]106.27[/C][C]0.157480157480237[/C][C]0.489999999999995[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=58651&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=58651&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
1103.9341666666670.2452256227652540.680000000000007
2104.8233333333330.3735172707053201.12000000000000
3105.8191666666670.3248064691847180.950000000000003
4106.340.09620054809898480.25
5106.270.1574801574802370.489999999999995







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha6.52981956815439
beta-0.0596598316330789
S.D.0.0538045679663539
T-STAT-1.10882465723703
p-value0.348404340005441

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 6.52981956815439 \tabularnewline
beta & -0.0596598316330789 \tabularnewline
S.D. & 0.0538045679663539 \tabularnewline
T-STAT & -1.10882465723703 \tabularnewline
p-value & 0.348404340005441 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=58651&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]6.52981956815439[/C][/ROW]
[ROW][C]beta[/C][C]-0.0596598316330789[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0538045679663539[/C][/ROW]
[ROW][C]T-STAT[/C][C]-1.10882465723703[/C][/ROW]
[ROW][C]p-value[/C][C]0.348404340005441[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=58651&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=58651&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)
alpha6.52981956815439
beta-0.0596598316330789
S.D.0.0538045679663539
T-STAT-1.10882465723703
p-value0.348404340005441







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha153.70996774294
beta-33.3293903172517
S.D.26.3061247926034
T-STAT-1.26698214123211
p-value0.294582124757157
Lambda34.3293903172517

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 153.70996774294 \tabularnewline
beta & -33.3293903172517 \tabularnewline
S.D. & 26.3061247926034 \tabularnewline
T-STAT & -1.26698214123211 \tabularnewline
p-value & 0.294582124757157 \tabularnewline
Lambda & 34.3293903172517 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=58651&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]153.70996774294[/C][/ROW]
[ROW][C]beta[/C][C]-33.3293903172517[/C][/ROW]
[ROW][C]S.D.[/C][C]26.3061247926034[/C][/ROW]
[ROW][C]T-STAT[/C][C]-1.26698214123211[/C][/ROW]
[ROW][C]p-value[/C][C]0.294582124757157[/C][/ROW]
[ROW][C]Lambda[/C][C]34.3293903172517[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=58651&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=58651&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)
alpha153.70996774294
beta-33.3293903172517
S.D.26.3061247926034
T-STAT-1.26698214123211
p-value0.294582124757157
Lambda34.3293903172517



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')