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Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationFri, 18 Dec 2009 06:03:59 -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/t12611414786ccj98q41osu305.htm/, Retrieved Sat, 27 Apr 2024 07:15:47 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=69301, Retrieved Sat, 27 Apr 2024 07:15:47 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact137
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Standard Deviation-Mean Plot] [] [2009-12-18 13:03:59] [02cb93c9d037d32bf77dfc632a3a9fbe] [Current]
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Dataseries X:
100.00
110.08
123.28
106.30
114.60
110.22
117.82
138.84
131.13
153.26
148.76
110.75
132.00
138.55
126.50
119.47
152.49
152.46
134.08
162.33
130.46
142.83
148.39
122.88
125.86
133.31
140.97
110.30
123.04
125.99
112.24
136.10
111.86
109.63
135.75
114.39
121.79
101.33
147.01
113.01
101.89
117.85
128.68
117.27
121.55
109.18
127.88
104.92
100.93
116.79
107.50
109.18
128.31
83.80
93.16
103.99
106.33
97.55
111.71
105.43
103.62




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=69301&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=69301&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=69301&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
1122.08666666666717.246648334904953.26
2138.53666666666713.319743604775942.86
3123.28666666666711.416020906311231.34
4117.69666666666713.110976202010945.68
5105.3911.337581913104944.51

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 122.086666666667 & 17.2466483349049 & 53.26 \tabularnewline
2 & 138.536666666667 & 13.3197436047759 & 42.86 \tabularnewline
3 & 123.286666666667 & 11.4160209063112 & 31.34 \tabularnewline
4 & 117.696666666667 & 13.1109762020109 & 45.68 \tabularnewline
5 & 105.39 & 11.3375819131049 & 44.51 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=69301&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]122.086666666667[/C][C]17.2466483349049[/C][C]53.26[/C][/ROW]
[ROW][C]2[/C][C]138.536666666667[/C][C]13.3197436047759[/C][C]42.86[/C][/ROW]
[ROW][C]3[/C][C]123.286666666667[/C][C]11.4160209063112[/C][C]31.34[/C][/ROW]
[ROW][C]4[/C][C]117.696666666667[/C][C]13.1109762020109[/C][C]45.68[/C][/ROW]
[ROW][C]5[/C][C]105.39[/C][C]11.3375819131049[/C][C]44.51[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=69301&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=69301&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
1122.08666666666717.246648334904953.26
2138.53666666666713.319743604775942.86
3123.28666666666711.416020906311231.34
4117.69666666666713.110976202010945.68
5105.3911.337581913104944.51







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha6.52647690731073
beta0.055681667265423
S.D.0.111702323012164
T-STAT0.498482625642078
p-value0.652398833712378

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 6.52647690731073 \tabularnewline
beta & 0.055681667265423 \tabularnewline
S.D. & 0.111702323012164 \tabularnewline
T-STAT & 0.498482625642078 \tabularnewline
p-value & 0.652398833712378 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=69301&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]6.52647690731073[/C][/ROW]
[ROW][C]beta[/C][C]0.055681667265423[/C][/ROW]
[ROW][C]S.D.[/C][C]0.111702323012164[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.498482625642078[/C][/ROW]
[ROW][C]p-value[/C][C]0.652398833712378[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=69301&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=69301&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)
alpha6.52647690731073
beta0.055681667265423
S.D.0.111702323012164
T-STAT0.498482625642078
p-value0.652398833712378







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-0.168178383394819
beta0.571999412249642
S.D.0.943529594849858
T-STAT0.606233673402331
p-value0.587156285111685
Lambda0.428000587750358

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -0.168178383394819 \tabularnewline
beta & 0.571999412249642 \tabularnewline
S.D. & 0.943529594849858 \tabularnewline
T-STAT & 0.606233673402331 \tabularnewline
p-value & 0.587156285111685 \tabularnewline
Lambda & 0.428000587750358 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=69301&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-0.168178383394819[/C][/ROW]
[ROW][C]beta[/C][C]0.571999412249642[/C][/ROW]
[ROW][C]S.D.[/C][C]0.943529594849858[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.606233673402331[/C][/ROW]
[ROW][C]p-value[/C][C]0.587156285111685[/C][/ROW]
[ROW][C]Lambda[/C][C]0.428000587750358[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=69301&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=69301&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-0.168178383394819
beta0.571999412249642
S.D.0.943529594849858
T-STAT0.606233673402331
p-value0.587156285111685
Lambda0.428000587750358



Parameters (Session):
par1 = 60 ; par2 = 1 ; par3 = 1 ; par4 = 1 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;
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')