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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, 18 Dec 2008 09:12:04 -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/2008/Dec/18/t12296168034wswchuoy71vbnh.htm/, Retrieved Sat, 11 May 2024 10:08:30 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=34873, Retrieved Sat, 11 May 2024 10:08:30 +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] [] [2008-12-18 16:12:04] [b0654df83a8a0e1de3ceb7bf60f0d58f] [Current]
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Dataseries X:
565464
547344
554788
562325
560854
555332
543599
536662
542722
593530
610763
612613
611324
594167
595454
590865
589379
584428
573100
567456
569028
620735
628884
628232
612117
595404
597141
593408
590072
579799
574205
572775
572942
619567
625809
619916
587625
565742
557274
560576
548854
531673
525919
511038
498662
555362
564591
541657
527070
509846
514258
516922
507561
492622
490243
469357
477580
528379
533590
517945




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24

\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 & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=34873&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]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=34873&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=34873&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'Sir Ronald Aylmer Fisher' @ 193.190.124.24







Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
1565499.66666666726048.240049895375951
2596087.66666666721828.351103067561428
3596096.2519371.217416686753034
4545747.7525213.998543828488963
5507114.41666666720485.306128399564233

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 565499.666666667 & 26048.2400498953 & 75951 \tabularnewline
2 & 596087.666666667 & 21828.3511030675 & 61428 \tabularnewline
3 & 596096.25 & 19371.2174166867 & 53034 \tabularnewline
4 & 545747.75 & 25213.9985438284 & 88963 \tabularnewline
5 & 507114.416666667 & 20485.3061283995 & 64233 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=34873&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]565499.666666667[/C][C]26048.2400498953[/C][C]75951[/C][/ROW]
[ROW][C]2[/C][C]596087.666666667[/C][C]21828.3511030675[/C][C]61428[/C][/ROW]
[ROW][C]3[/C][C]596096.25[/C][C]19371.2174166867[/C][C]53034[/C][/ROW]
[ROW][C]4[/C][C]545747.75[/C][C]25213.9985438284[/C][C]88963[/C][/ROW]
[ROW][C]5[/C][C]507114.416666667[/C][C]20485.3061283995[/C][C]64233[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=34873&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=34873&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
1565499.66666666726048.240049895375951
2596087.66666666721828.351103067561428
3596096.2519371.217416686753034
4545747.7525213.998543828488963
5507114.41666666720485.306128399564233







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha27670.1660501137
beta-0.0090387132138629
S.D.0.0447724237624759
T-STAT-0.201881257575300
p-value0.852923894629025

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 27670.1660501137 \tabularnewline
beta & -0.0090387132138629 \tabularnewline
S.D. & 0.0447724237624759 \tabularnewline
T-STAT & -0.201881257575300 \tabularnewline
p-value & 0.852923894629025 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=34873&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]27670.1660501137[/C][/ROW]
[ROW][C]beta[/C][C]-0.0090387132138629[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0447724237624759[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.201881257575300[/C][/ROW]
[ROW][C]p-value[/C][C]0.852923894629025[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=34873&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=34873&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)
alpha27670.1660501137
beta-0.0090387132138629
S.D.0.0447724237624759
T-STAT-0.201881257575300
p-value0.852923894629025







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha12.4799064563901
beta-0.185935048777266
S.D.1.09291608594834
T-STAT-0.170127470139601
p-value0.875735870465546
Lambda1.18593504877727

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 12.4799064563901 \tabularnewline
beta & -0.185935048777266 \tabularnewline
S.D. & 1.09291608594834 \tabularnewline
T-STAT & -0.170127470139601 \tabularnewline
p-value & 0.875735870465546 \tabularnewline
Lambda & 1.18593504877727 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=34873&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]12.4799064563901[/C][/ROW]
[ROW][C]beta[/C][C]-0.185935048777266[/C][/ROW]
[ROW][C]S.D.[/C][C]1.09291608594834[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.170127470139601[/C][/ROW]
[ROW][C]p-value[/C][C]0.875735870465546[/C][/ROW]
[ROW][C]Lambda[/C][C]1.18593504877727[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=34873&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=34873&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)
alpha12.4799064563901
beta-0.185935048777266
S.D.1.09291608594834
T-STAT-0.170127470139601
p-value0.875735870465546
Lambda1.18593504877727



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')