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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 computationThu, 17 Dec 2009 16:29:15 -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/t1261092596uokqnfjo5sbeqoi.htm/, Retrieved Sat, 27 Apr 2024 14:52:01 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=69148, Retrieved Sat, 27 Apr 2024 14:52:01 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact163
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]
-   PD        [Standard Deviation-Mean Plot] [Identifying integ...] [2009-11-23 19:29:32] [d46757a0a8c9b00540ab7e7e0c34bfc4]
-   P             [Standard Deviation-Mean Plot] [] [2009-12-17 23:29:15] [f90b018c65398c2fee7b197f24b65ddd] [Current]
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Dataseries X:
8.4
8.4
8.4
8.6
8.9
8.8
8.3
7.5
7.2
7.4
8.8
9.3
9.3
8.7
8.2
8.3
8.5
8.6
8.5
8.2
8.1
7.9
8.6
8.7
8.7
8.5
8.4
8.5
8.7
8.7
8.6
8.5
8.3
8
8.2
8.1
8.1
8
7.9
7.9
8
8
7.9
8
7.7
7.2
7.5
7.3
7
7
7
7.2
7.3
7.1
6.8
6.4
6.1
6.5
7.7
7.9
7.5
6.9
6.6
6.9
7.7
8
8
7.7
7.3
7.4
8.1
8.3
8.2




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=69148&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=69148&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=69148&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
18.333333333333330.6485414871895712.1
28.466666666666670.3651483716701111.4
38.433333333333330.2386832565759420.700
47.791666666666670.2998737107921310.9
570.5134553180524711.8
67.533333333333330.5348463387372171.7

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 8.33333333333333 & 0.648541487189571 & 2.1 \tabularnewline
2 & 8.46666666666667 & 0.365148371670111 & 1.4 \tabularnewline
3 & 8.43333333333333 & 0.238683256575942 & 0.700 \tabularnewline
4 & 7.79166666666667 & 0.299873710792131 & 0.9 \tabularnewline
5 & 7 & 0.513455318052471 & 1.8 \tabularnewline
6 & 7.53333333333333 & 0.534846338737217 & 1.7 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=69148&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]8.33333333333333[/C][C]0.648541487189571[/C][C]2.1[/C][/ROW]
[ROW][C]2[/C][C]8.46666666666667[/C][C]0.365148371670111[/C][C]1.4[/C][/ROW]
[ROW][C]3[/C][C]8.43333333333333[/C][C]0.238683256575942[/C][C]0.700[/C][/ROW]
[ROW][C]4[/C][C]7.79166666666667[/C][C]0.299873710792131[/C][C]0.9[/C][/ROW]
[ROW][C]5[/C][C]7[/C][C]0.513455318052471[/C][C]1.8[/C][/ROW]
[ROW][C]6[/C][C]7.53333333333333[/C][C]0.534846338737217[/C][C]1.7[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=69148&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=69148&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
18.333333333333330.6485414871895712.1
28.466666666666670.3651483716701111.4
38.433333333333330.2386832565759420.700
47.791666666666670.2998737107921310.9
570.5134553180524711.8
67.533333333333330.5348463387372171.7







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha1.08776978746855
beta-0.0825527298081765
S.D.0.126373492449734
T-STAT-0.653244032493701
p-value0.54924439802919

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 1.08776978746855 \tabularnewline
beta & -0.0825527298081765 \tabularnewline
S.D. & 0.126373492449734 \tabularnewline
T-STAT & -0.653244032493701 \tabularnewline
p-value & 0.54924439802919 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=69148&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]1.08776978746855[/C][/ROW]
[ROW][C]beta[/C][C]-0.0825527298081765[/C][/ROW]
[ROW][C]S.D.[/C][C]0.126373492449734[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.653244032493701[/C][/ROW]
[ROW][C]p-value[/C][C]0.54924439802919[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=69148&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=69148&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)
alpha1.08776978746855
beta-0.0825527298081765
S.D.0.126373492449734
T-STAT-0.653244032493701
p-value0.54924439802919







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha2.98448504919170
beta-1.87611572138014
S.D.2.33711386161391
T-STAT-0.80274895981515
p-value0.467106215117767
Lambda2.87611572138014

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 2.98448504919170 \tabularnewline
beta & -1.87611572138014 \tabularnewline
S.D. & 2.33711386161391 \tabularnewline
T-STAT & -0.80274895981515 \tabularnewline
p-value & 0.467106215117767 \tabularnewline
Lambda & 2.87611572138014 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=69148&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]2.98448504919170[/C][/ROW]
[ROW][C]beta[/C][C]-1.87611572138014[/C][/ROW]
[ROW][C]S.D.[/C][C]2.33711386161391[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.80274895981515[/C][/ROW]
[ROW][C]p-value[/C][C]0.467106215117767[/C][/ROW]
[ROW][C]Lambda[/C][C]2.87611572138014[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=69148&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=69148&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)
alpha2.98448504919170
beta-1.87611572138014
S.D.2.33711386161391
T-STAT-0.80274895981515
p-value0.467106215117767
Lambda2.87611572138014



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')