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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, 03 Dec 2009 15:58:48 -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/04/t1259881274o360xu4jd68811q.htm/, Retrieved Sat, 27 Apr 2024 21:40:17 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=63145, Retrieved Sat, 27 Apr 2024 21:40:17 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsVerbetering
Estimated Impact140
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] [smp] [2009-11-26 18:37:16] [ed603017d2bee8fbd82b6d5ec04e12c3]
-               [Standard Deviation-Mean Plot] [WS8 SDMP] [2009-11-28 11:19:01] [aba88da643e3763d32ff92bd8f92a385]
-   PD              [Standard Deviation-Mean Plot] [Workshop 8] [2009-12-03 22:58:48] [682632737e024f9e62885141c5f654cd] [Current]
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Dataseries X:
100.00
94.97
107.50
124.27
107.06
79.71
163.41
144.83
166.82
154.26
132.60
157.51
104.02
106.03
113.23
117.64
113.34
66.62
185.99
174.57
208.19
163.81
162.46
148.16
113.41
105.63
111.79
132.36
110.75
67.37
178.29
156.38
189.71
152.80
150.80
160.40
127.25
108.47
117.09
147.25
116.19
75.83
181.94
179.12
183.15
197.90
155.42
162.54
125.90
105.50
121.11
137.51
97.20
69.74
152.58
146.59
161.16
152.84
121.95
140.12




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=63145&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=63145&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=63145&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
1127.74529.702262387048787.11
2138.67166666666741.3821706960274141.57
3135.807535.1159197580605122.34
4146.012537.2150209470707122.07
5127.68333333333326.697138196420891.42

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 127.745 & 29.7022623870487 & 87.11 \tabularnewline
2 & 138.671666666667 & 41.3821706960274 & 141.57 \tabularnewline
3 & 135.8075 & 35.1159197580605 & 122.34 \tabularnewline
4 & 146.0125 & 37.2150209470707 & 122.07 \tabularnewline
5 & 127.683333333333 & 26.6971381964208 & 91.42 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=63145&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]127.745[/C][C]29.7022623870487[/C][C]87.11[/C][/ROW]
[ROW][C]2[/C][C]138.671666666667[/C][C]41.3821706960274[/C][C]141.57[/C][/ROW]
[ROW][C]3[/C][C]135.8075[/C][C]35.1159197580605[/C][C]122.34[/C][/ROW]
[ROW][C]4[/C][C]146.0125[/C][C]37.2150209470707[/C][C]122.07[/C][/ROW]
[ROW][C]5[/C][C]127.683333333333[/C][C]26.6971381964208[/C][C]91.42[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=63145&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=63145&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
1127.74529.702262387048787.11
2138.67166666666741.3821706960274141.57
3135.807535.1159197580605122.34
4146.012537.2150209470707122.07
5127.68333333333326.697138196420891.42







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-48.856746931521
beta0.61308475358361
S.D.0.255126303988239
T-STAT2.40306367473529
p-value0.0956107898288016

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -48.856746931521 \tabularnewline
beta & 0.61308475358361 \tabularnewline
S.D. & 0.255126303988239 \tabularnewline
T-STAT & 2.40306367473529 \tabularnewline
p-value & 0.0956107898288016 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=63145&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-48.856746931521[/C][/ROW]
[ROW][C]beta[/C][C]0.61308475358361[/C][/ROW]
[ROW][C]S.D.[/C][C]0.255126303988239[/C][/ROW]
[ROW][C]T-STAT[/C][C]2.40306367473529[/C][/ROW]
[ROW][C]p-value[/C][C]0.0956107898288016[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=63145&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=63145&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-48.856746931521
beta0.61308475358361
S.D.0.255126303988239
T-STAT2.40306367473529
p-value0.0956107898288016







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-9.0636326021902
beta2.56423985925134
S.D.0.984736896361444
T-STAT2.60398474833845
p-value0.0800996559499168
Lambda-1.56423985925134

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -9.0636326021902 \tabularnewline
beta & 2.56423985925134 \tabularnewline
S.D. & 0.984736896361444 \tabularnewline
T-STAT & 2.60398474833845 \tabularnewline
p-value & 0.0800996559499168 \tabularnewline
Lambda & -1.56423985925134 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=63145&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-9.0636326021902[/C][/ROW]
[ROW][C]beta[/C][C]2.56423985925134[/C][/ROW]
[ROW][C]S.D.[/C][C]0.984736896361444[/C][/ROW]
[ROW][C]T-STAT[/C][C]2.60398474833845[/C][/ROW]
[ROW][C]p-value[/C][C]0.0800996559499168[/C][/ROW]
[ROW][C]Lambda[/C][C]-1.56423985925134[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=63145&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=63145&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-9.0636326021902
beta2.56423985925134
S.D.0.984736896361444
T-STAT2.60398474833845
p-value0.0800996559499168
Lambda-1.56423985925134



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')