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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, 10 Dec 2009 11:34:21 -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/10/t1260470816147q8fdbyfzptn4.htm/, Retrieved Fri, 29 Mar 2024 00:05:08 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=65714, Retrieved Fri, 29 Mar 2024 00:05:08 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact144
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [data set] [2008-12-01 19:54:57] [b98453cac15ba1066b407e146608df68]
- RMP   [Standard Deviation-Mean Plot] [] [2009-11-27 14:40:44] [b98453cac15ba1066b407e146608df68]
-    D    [Standard Deviation-Mean Plot] [BBWS9-Regressieta...] [2009-12-01 20:06:37] [408e92805dcb18620260f240a7fb9d53]
-    D      [Standard Deviation-Mean Plot] [shw-ws9] [2009-12-04 12:49:51] [2663058f2a5dda519058ac6b2228468f]
-    D        [Standard Deviation-Mean Plot] [ws 9 regressie model] [2009-12-04 18:48:55] [134dc66689e3d457a82860db6471d419]
-    D            [Standard Deviation-Mean Plot] [sdmp icp] [2009-12-10 18:34:21] [4f297b039e1043ebee7ff7a83b1eaaaa] [Current]
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Dataseries X:
100.00
102.04
102.51
102.71
103.00
103.39
102.32
103.88
104.65
104.46
104.65
104.36
102.71
104.55
104.76
105.72
106.20
106.50
105.14
106.50
106.69
106.50
106.50
106.39
105.43
107.18
107.37
107.46
107.66
107.37
106.30
107.85
107.95
107.85
107.66
107.76
106.69
108.92
109.22
109.02
108.62
109.02
107.76
109.60
109.80
109.41
109.60
109.60
108.15
110.18
110.27
110.87
111.25
111.15
109.99
111.83
111.73
112.31
112.12
111.73
110.27
112.71
113.38
113.57
113.77
114.15
112.99
115.03
115.03
114.84
114.75
114.84
113.32
115.92
115.84
116.49
116.90
116.99
115.74
117.73
117.17
116.83
117.08
117.23
115.25
117.98
117.97
118.56
118.42
118.51
117.25
119.08
118.85
119.41
120.43
120.87
119.31
122.24
123.14
123.39
124.46
125.33
124.17
125.48
125.35
125.15
124.31
124.14
121.81
124.62
123.93
124.29
124.16
124.02
122.00
124.58
124.06




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 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 & 2 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=65714&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]2 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=65714&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=65714&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 time2 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
1103.1641666666671.373035511249264.65000000000001
2105.681.195506739268493.98
3107.320.7410189544870552.52000000000000
4108.9383333333330.9003113939413423.11
5110.9651.173971503448484.16
6113.77751.373225300987694.76000000000001
7116.4366666666671.158135910797524.41000000000001
8118.5483333333331.454996615637015.62
9123.87251.744362999128136.17

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 103.164166666667 & 1.37303551124926 & 4.65000000000001 \tabularnewline
2 & 105.68 & 1.19550673926849 & 3.98 \tabularnewline
3 & 107.32 & 0.741018954487055 & 2.52000000000000 \tabularnewline
4 & 108.938333333333 & 0.900311393941342 & 3.11 \tabularnewline
5 & 110.965 & 1.17397150344848 & 4.16 \tabularnewline
6 & 113.7775 & 1.37322530098769 & 4.76000000000001 \tabularnewline
7 & 116.436666666667 & 1.15813591079752 & 4.41000000000001 \tabularnewline
8 & 118.548333333333 & 1.45499661563701 & 5.62 \tabularnewline
9 & 123.8725 & 1.74436299912813 & 6.17 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=65714&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]103.164166666667[/C][C]1.37303551124926[/C][C]4.65000000000001[/C][/ROW]
[ROW][C]2[/C][C]105.68[/C][C]1.19550673926849[/C][C]3.98[/C][/ROW]
[ROW][C]3[/C][C]107.32[/C][C]0.741018954487055[/C][C]2.52000000000000[/C][/ROW]
[ROW][C]4[/C][C]108.938333333333[/C][C]0.900311393941342[/C][C]3.11[/C][/ROW]
[ROW][C]5[/C][C]110.965[/C][C]1.17397150344848[/C][C]4.16[/C][/ROW]
[ROW][C]6[/C][C]113.7775[/C][C]1.37322530098769[/C][C]4.76000000000001[/C][/ROW]
[ROW][C]7[/C][C]116.436666666667[/C][C]1.15813591079752[/C][C]4.41000000000001[/C][/ROW]
[ROW][C]8[/C][C]118.548333333333[/C][C]1.45499661563701[/C][C]5.62[/C][/ROW]
[ROW][C]9[/C][C]123.8725[/C][C]1.74436299912813[/C][C]6.17[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=65714&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=65714&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
1103.1641666666671.373035511249264.65000000000001
2105.681.195506739268493.98
3107.320.7410189544870552.52000000000000
4108.9383333333330.9003113939413423.11
5110.9651.173971503448484.16
6113.77751.373225300987694.76000000000001
7116.4366666666671.158135910797524.41000000000001
8118.5483333333331.454996615637015.62
9123.87251.744362999128136.17







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-1.84883330219163
beta0.0275146186796103
S.D.0.0133141926238685
T-STAT2.0665630622081
p-value0.0776095326294685

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -1.84883330219163 \tabularnewline
beta & 0.0275146186796103 \tabularnewline
S.D. & 0.0133141926238685 \tabularnewline
T-STAT & 2.0665630622081 \tabularnewline
p-value & 0.0776095326294685 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=65714&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-1.84883330219163[/C][/ROW]
[ROW][C]beta[/C][C]0.0275146186796103[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0133141926238685[/C][/ROW]
[ROW][C]T-STAT[/C][C]2.0665630622081[/C][/ROW]
[ROW][C]p-value[/C][C]0.0776095326294685[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=65714&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=65714&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-1.84883330219163
beta0.0275146186796103
S.D.0.0133141926238685
T-STAT2.0665630622081
p-value0.0776095326294685







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-11.1794204543675
beta2.40849008746145
S.D.1.37191898161260
T-STAT1.75556291569815
p-value0.122593783761124
Lambda-1.40849008746145

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -11.1794204543675 \tabularnewline
beta & 2.40849008746145 \tabularnewline
S.D. & 1.37191898161260 \tabularnewline
T-STAT & 1.75556291569815 \tabularnewline
p-value & 0.122593783761124 \tabularnewline
Lambda & -1.40849008746145 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=65714&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-11.1794204543675[/C][/ROW]
[ROW][C]beta[/C][C]2.40849008746145[/C][/ROW]
[ROW][C]S.D.[/C][C]1.37191898161260[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.75556291569815[/C][/ROW]
[ROW][C]p-value[/C][C]0.122593783761124[/C][/ROW]
[ROW][C]Lambda[/C][C]-1.40849008746145[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=65714&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=65714&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-11.1794204543675
beta2.40849008746145
S.D.1.37191898161260
T-STAT1.75556291569815
p-value0.122593783761124
Lambda-1.40849008746145



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')