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Author's title

Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationSat, 06 Dec 2008 04:15:17 -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/2008/Dec/06/t1228562355iuyo1k5avl81adu.htm/, Retrieved Fri, 17 May 2024 01:41:35 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=29505, Retrieved Fri, 17 May 2024 01:41:35 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact194
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F     [(Partial) Autocorrelation Function] [] [2008-12-03 07:50:35] [996314793dac993597edc1ca2281ff39]
- RMP     [Standard Deviation-Mean Plot] [] [2008-12-06 11:15:17] [e02910eed3830f1815f587e12f46cbdb] [Current]
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Dataseries X:
118.4
121.4
128.8
131.7
141.7
142.9
139.4
134.7
125.0
113.6
111.5
108.5
112.3
116.6
115.5
120.1
132.9
128.1
129.3
132.5
131.0
124.9
120.8
122.0
122.1
127.4
135.2
137.3
135.0
136.0
138.4
134.7
138.4
133.9
133.6
141.2
151.8
155.4
156.6
161.6
160.7
156.0
159.5
168.7
169.9
169.9
185.9
190.8
195.8
211.9
227.1
251.3
256.7
251.9
251.2
270.3
267.2
243.0
229.9
187.2




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=29505&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=29505&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=29505&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
1126.46666666666711.966797500761934.4
2123.8333333333337.0012120162847320.6
3134.4333333333335.1475207330296119.1
4165.56666666666712.204941870431339
5236.95833333333327.01691249210583.1

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 126.466666666667 & 11.9667975007619 & 34.4 \tabularnewline
2 & 123.833333333333 & 7.00121201628473 & 20.6 \tabularnewline
3 & 134.433333333333 & 5.14752073302961 & 19.1 \tabularnewline
4 & 165.566666666667 & 12.2049418704313 & 39 \tabularnewline
5 & 236.958333333333 & 27.016912492105 & 83.1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=29505&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]126.466666666667[/C][C]11.9667975007619[/C][C]34.4[/C][/ROW]
[ROW][C]2[/C][C]123.833333333333[/C][C]7.00121201628473[/C][C]20.6[/C][/ROW]
[ROW][C]3[/C][C]134.433333333333[/C][C]5.14752073302961[/C][C]19.1[/C][/ROW]
[ROW][C]4[/C][C]165.566666666667[/C][C]12.2049418704313[/C][C]39[/C][/ROW]
[ROW][C]5[/C][C]236.958333333333[/C][C]27.016912492105[/C][C]83.1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=29505&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=29505&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
1126.46666666666711.966797500761934.4
2123.8333333333337.0012120162847320.6
3134.4333333333335.1475207330296119.1
4165.56666666666712.204941870431339
5236.95833333333327.01691249210583.1







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-13.9452034105998
beta0.169021267900979
S.D.0.0374736885046345
T-STAT4.51039848612916
p-value0.0203636558437944

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -13.9452034105998 \tabularnewline
beta & 0.169021267900979 \tabularnewline
S.D. & 0.0374736885046345 \tabularnewline
T-STAT & 4.51039848612916 \tabularnewline
p-value & 0.0203636558437944 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=29505&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-13.9452034105998[/C][/ROW]
[ROW][C]beta[/C][C]0.169021267900979[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0374736885046345[/C][/ROW]
[ROW][C]T-STAT[/C][C]4.51039848612916[/C][/ROW]
[ROW][C]p-value[/C][C]0.0203636558437944[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=29505&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=29505&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-13.9452034105998
beta0.169021267900979
S.D.0.0374736885046345
T-STAT4.51039848612916
p-value0.0203636558437944







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-7.47901823253338
beta1.95964734530568
S.D.0.727649634522902
T-STAT2.69311939748387
p-value0.0742175145679864
Lambda-0.959647345305677

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -7.47901823253338 \tabularnewline
beta & 1.95964734530568 \tabularnewline
S.D. & 0.727649634522902 \tabularnewline
T-STAT & 2.69311939748387 \tabularnewline
p-value & 0.0742175145679864 \tabularnewline
Lambda & -0.959647345305677 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=29505&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-7.47901823253338[/C][/ROW]
[ROW][C]beta[/C][C]1.95964734530568[/C][/ROW]
[ROW][C]S.D.[/C][C]0.727649634522902[/C][/ROW]
[ROW][C]T-STAT[/C][C]2.69311939748387[/C][/ROW]
[ROW][C]p-value[/C][C]0.0742175145679864[/C][/ROW]
[ROW][C]Lambda[/C][C]-0.959647345305677[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=29505&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=29505&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-7.47901823253338
beta1.95964734530568
S.D.0.727649634522902
T-STAT2.69311939748387
p-value0.0742175145679864
Lambda-0.959647345305677



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')