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Author's title

Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationTue, 27 Nov 2007 04:21:14 -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/2007/Nov/27/t1196162324ik6wpn25ji5psku.htm/, Retrieved Sun, 05 May 2024 11:19:18 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=6855, Retrieved Sun, 05 May 2024 11:19:18 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsinvesteringen in bedrijfstak Tinne Van der Eycken
Estimated Impact179
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Standard Deviation-Mean Plot] [workshop 3] [2007-11-27 11:21:14] [c8635c97647ba59406cb570a9fab7b02] [Current]
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Dataseries X:
109,2
126,3
104
96
262
89,8
86
92,7
126,8
92,8
87,8
100
72,4
104,9
52,3
65,3
110,2
54,4
47,5
65,2
69,8
53,6
116,1
56,6
47,2
90,6
60,4
59,3
131,6
59,4
65,5
70,5
81
73,3
107,5
88,9
55,8
80,5
86,3
112,6
148,6
47,1
57,8
81
60,1
76,1
82,5
66,8
58,7
54,2
103,3
77,8
118,4
64,9
40,8
77,7
66,8
69,2
82,4
62,7
58,2




Summary of compuational 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 compuational 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=6855&T=0

[TABLE]
[ROW][C]Summary of compuational 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=6855&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6855&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 compuational 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
1114.4548.4476756173841214.8
272.358333333333324.224084871854061.9
377.933333333333323.776165809609979.3
479.627.896464422444889.3
573.07521.17464714743048.2

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 114.45 & 48.4476756173841 & 214.8 \tabularnewline
2 & 72.3583333333333 & 24.2240848718540 & 61.9 \tabularnewline
3 & 77.9333333333333 & 23.7761658096099 & 79.3 \tabularnewline
4 & 79.6 & 27.8964644224448 & 89.3 \tabularnewline
5 & 73.075 & 21.1746471474304 & 8.2 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=6855&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]114.45[/C][C]48.4476756173841[/C][C]214.8[/C][/ROW]
[ROW][C]2[/C][C]72.3583333333333[/C][C]24.2240848718540[/C][C]61.9[/C][/ROW]
[ROW][C]3[/C][C]77.9333333333333[/C][C]23.7761658096099[/C][C]79.3[/C][/ROW]
[ROW][C]4[/C][C]79.6[/C][C]27.8964644224448[/C][C]89.3[/C][/ROW]
[ROW][C]5[/C][C]73.075[/C][C]21.1746471474304[/C][C]8.2[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=6855&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6855&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
1114.4548.4476756173841214.8
272.358333333333324.224084871854061.9
377.933333333333323.776165809609979.3
479.627.896464422444889.3
573.07521.17464714743048.2







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-22.8718523397643
beta0.622587261890704
S.D.0.0550924593087657
T-STAT11.3007709167858
p-value0.00148606418390774

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -22.8718523397643 \tabularnewline
beta & 0.622587261890704 \tabularnewline
S.D. & 0.0550924593087657 \tabularnewline
T-STAT & 11.3007709167858 \tabularnewline
p-value & 0.00148606418390774 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=6855&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-22.8718523397643[/C][/ROW]
[ROW][C]beta[/C][C]0.622587261890704[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0550924593087657[/C][/ROW]
[ROW][C]T-STAT[/C][C]11.3007709167858[/C][/ROW]
[ROW][C]p-value[/C][C]0.00148606418390774[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=6855&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6855&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-22.8718523397643
beta0.622587261890704
S.D.0.0550924593087657
T-STAT11.3007709167858
p-value0.00148606418390774







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-4.10004925143864
beta1.68365505581147
S.D.0.210987384011954
T-STAT7.97988497604236
p-value0.00410636634527057
Lambda-0.683655055811474

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -4.10004925143864 \tabularnewline
beta & 1.68365505581147 \tabularnewline
S.D. & 0.210987384011954 \tabularnewline
T-STAT & 7.97988497604236 \tabularnewline
p-value & 0.00410636634527057 \tabularnewline
Lambda & -0.683655055811474 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=6855&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-4.10004925143864[/C][/ROW]
[ROW][C]beta[/C][C]1.68365505581147[/C][/ROW]
[ROW][C]S.D.[/C][C]0.210987384011954[/C][/ROW]
[ROW][C]T-STAT[/C][C]7.97988497604236[/C][/ROW]
[ROW][C]p-value[/C][C]0.00410636634527057[/C][/ROW]
[ROW][C]Lambda[/C][C]-0.683655055811474[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=6855&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6855&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-4.10004925143864
beta1.68365505581147
S.D.0.210987384011954
T-STAT7.97988497604236
p-value0.00410636634527057
Lambda-0.683655055811474



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')