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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 computationWed, 02 Dec 2009 15:38:25 -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/02/t1259793547yjxwibccxyalpq3.htm/, Retrieved Sun, 28 Apr 2024 16:14:47 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=62616, Retrieved Sun, 28 Apr 2024 16:14:47 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact178
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Standard Deviation-Mean Plot] [workshop 3: Q1] [2007-11-27 09:39:46] [0089dec2868056b990fdbd23bf9edb23]
- RM D    [Standard Deviation-Mean Plot] [PAPER] [2009-12-02 22:38:25] [2d9a0b3c2f25bb8f387fafb994d0d852] [Current]
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Dataseries X:
595
591
589
584
573
567
569
621
629
628
612
595
597
593
590
580
574
573
573
620
626
620
588
566
557
561
549
532
526
511
499
555
565
542
527
510
514
517
508
493
490
469
478
528
534
518
506
502
516
528
533
536
537
524
536
587
597
581
564
564




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=62616&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=62616&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62616&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
1596.08333333333321.9770886207073115
2591.66666666666720.5264057577875109
3536.16666666666722.032345368213657
4504.7519.484842593900841
5550.2527.1297387984611107

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 596.083333333333 & 21.9770886207073 & 115 \tabularnewline
2 & 591.666666666667 & 20.5264057577875 & 109 \tabularnewline
3 & 536.166666666667 & 22.0323453682136 & 57 \tabularnewline
4 & 504.75 & 19.4848425939008 & 41 \tabularnewline
5 & 550.25 & 27.1297387984611 & 107 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=62616&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]596.083333333333[/C][C]21.9770886207073[/C][C]115[/C][/ROW]
[ROW][C]2[/C][C]591.666666666667[/C][C]20.5264057577875[/C][C]109[/C][/ROW]
[ROW][C]3[/C][C]536.166666666667[/C][C]22.0323453682136[/C][C]57[/C][/ROW]
[ROW][C]4[/C][C]504.75[/C][C]19.4848425939008[/C][C]41[/C][/ROW]
[ROW][C]5[/C][C]550.25[/C][C]27.1297387984611[/C][C]107[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=62616&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62616&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
1596.08333333333321.9770886207073115
2591.66666666666720.5264057577875109
3536.16666666666722.032345368213657
4504.7519.484842593900841
5550.2527.1297387984611107







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha17.9632794893333
beta0.00767710091788912
S.D.0.0438391879068693
T-STAT0.175119596973332
p-value0.87213796748121

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 17.9632794893333 \tabularnewline
beta & 0.00767710091788912 \tabularnewline
S.D. & 0.0438391879068693 \tabularnewline
T-STAT & 0.175119596973332 \tabularnewline
p-value & 0.87213796748121 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=62616&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]17.9632794893333[/C][/ROW]
[ROW][C]beta[/C][C]0.00767710091788912[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0438391879068693[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.175119596973332[/C][/ROW]
[ROW][C]p-value[/C][C]0.87213796748121[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=62616&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62616&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)
alpha17.9632794893333
beta0.00767710091788912
S.D.0.0438391879068693
T-STAT0.175119596973332
p-value0.87213796748121







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha1.41655762515047
beta0.265625761097737
S.D.1.03067503509410
T-STAT0.257720185367142
p-value0.813290275118794
Lambda0.734374238902263

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 1.41655762515047 \tabularnewline
beta & 0.265625761097737 \tabularnewline
S.D. & 1.03067503509410 \tabularnewline
T-STAT & 0.257720185367142 \tabularnewline
p-value & 0.813290275118794 \tabularnewline
Lambda & 0.734374238902263 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=62616&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]1.41655762515047[/C][/ROW]
[ROW][C]beta[/C][C]0.265625761097737[/C][/ROW]
[ROW][C]S.D.[/C][C]1.03067503509410[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.257720185367142[/C][/ROW]
[ROW][C]p-value[/C][C]0.813290275118794[/C][/ROW]
[ROW][C]Lambda[/C][C]0.734374238902263[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=62616&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62616&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)
alpha1.41655762515047
beta0.265625761097737
S.D.1.03067503509410
T-STAT0.257720185367142
p-value0.813290275118794
Lambda0.734374238902263



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')