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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 computationTue, 24 Nov 2009 09:02:10 -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/Nov/24/t1259078605vjo5jn9ab4c8vnj.htm/, Retrieved Sun, 16 Jun 2024 23:07:40 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=59140, Retrieved Sun, 16 Jun 2024 23:07:40 +0000
QR Codes:

Original text written by user:Uitleg in Word document
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact218
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]
- R  D          [Standard Deviation-Mean Plot] [Bestedingen consu...] [2009-11-24 16:02:10] [8eb8270f5a1cfdf0409dcfcbf10be18b] [Current]
- R  D            [Standard Deviation-Mean Plot] [] [2010-12-29 11:43:03] [adca540665f1dd1a5a4406fd7f55bdf4]
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Dataseries X:
96.96
93.11
95.62
98.30
96.38
100.82
99.06
94.03
102.07
99.31
98.64
101.82
99.14
97.63
100.06
101.32
101.49
105.43
105.09
99.48
108.53
104.34
106.10
107.35
103.00
104.50
105.17
104.84
106.18
108.86
107.77
102.74
112.63
106.26
108.86
111.38
106.85
107.86
107.94
111.38
111.29
113.72
111.88
109.87
113.72
111.71
114.81
112.05
111.54
110.87
110.87
115.48
111.63
116.24
113.56
106.01
110.45
107.77
108.61
108.19




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=59140&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=59140&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59140&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
198.012.883987139045848.96
2102.9966666666673.5809453635834410.9
3106.8491666666673.129805275189829.89
4111.092.514463615311887.96
5110.9353.0747786320910410.2300000000000

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 98.01 & 2.88398713904584 & 8.96 \tabularnewline
2 & 102.996666666667 & 3.58094536358344 & 10.9 \tabularnewline
3 & 106.849166666667 & 3.12980527518982 & 9.89 \tabularnewline
4 & 111.09 & 2.51446361531188 & 7.96 \tabularnewline
5 & 110.935 & 3.07477863209104 & 10.2300000000000 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=59140&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]98.01[/C][C]2.88398713904584[/C][C]8.96[/C][/ROW]
[ROW][C]2[/C][C]102.996666666667[/C][C]3.58094536358344[/C][C]10.9[/C][/ROW]
[ROW][C]3[/C][C]106.849166666667[/C][C]3.12980527518982[/C][C]9.89[/C][/ROW]
[ROW][C]4[/C][C]111.09[/C][C]2.51446361531188[/C][C]7.96[/C][/ROW]
[ROW][C]5[/C][C]110.935[/C][C]3.07477863209104[/C][C]10.2300000000000[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=59140&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59140&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
198.012.883987139045848.96
2102.9966666666673.5809453635834410.9
3106.8491666666673.129805275189829.89
4111.092.514463615311887.96
5110.9353.0747786320910410.2300000000000







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha5.43764814230060
beta-0.0226546421971248
S.D.0.0380826662855122
T-STAT-0.594880674248989
p-value0.593806721729727

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 5.43764814230060 \tabularnewline
beta & -0.0226546421971248 \tabularnewline
S.D. & 0.0380826662855122 \tabularnewline
T-STAT & -0.594880674248989 \tabularnewline
p-value & 0.593806721729727 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=59140&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]5.43764814230060[/C][/ROW]
[ROW][C]beta[/C][C]-0.0226546421971248[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0380826662855122[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.594880674248989[/C][/ROW]
[ROW][C]p-value[/C][C]0.593806721729727[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=59140&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59140&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)
alpha5.43764814230060
beta-0.0226546421971248
S.D.0.0380826662855122
T-STAT-0.594880674248989
p-value0.593806721729727







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha4.72952942636777
beta-0.777615541860294
S.D.1.32495859158419
T-STAT-0.58689799575588
p-value0.598515094850969
Lambda1.77761554186029

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 4.72952942636777 \tabularnewline
beta & -0.777615541860294 \tabularnewline
S.D. & 1.32495859158419 \tabularnewline
T-STAT & -0.58689799575588 \tabularnewline
p-value & 0.598515094850969 \tabularnewline
Lambda & 1.77761554186029 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=59140&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]4.72952942636777[/C][/ROW]
[ROW][C]beta[/C][C]-0.777615541860294[/C][/ROW]
[ROW][C]S.D.[/C][C]1.32495859158419[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.58689799575588[/C][/ROW]
[ROW][C]p-value[/C][C]0.598515094850969[/C][/ROW]
[ROW][C]Lambda[/C][C]1.77761554186029[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=59140&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59140&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)
alpha4.72952942636777
beta-0.777615541860294
S.D.1.32495859158419
T-STAT-0.58689799575588
p-value0.598515094850969
Lambda1.77761554186029



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')