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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, 10 Dec 2009 09:46:08 -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/10/t1260463665nzm0qe4cy3q1r0t.htm/, Retrieved Thu, 28 Mar 2024 13:13:58 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=65582, Retrieved Thu, 28 Mar 2024 13:13:58 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact132
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [data set] [2008-12-01 19:54:57] [b98453cac15ba1066b407e146608df68]
- RMP   [Standard Deviation-Mean Plot] [] [2009-11-27 14:40:44] [b98453cac15ba1066b407e146608df68]
-    D    [Standard Deviation-Mean Plot] [WS 9 SMP Producti...] [2009-12-04 09:49:19] [83058a88a37d754675a5cd22dab372fc]
-    D        [Standard Deviation-Mean Plot] [WS 9 Review 2 SMP] [2009-12-10 16:46:08] [eba9f01697e64705b70041e6f338cb22] [Current]
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Dataseries X:
29.837
29.571
30.167
30.524
30.996
31.033
31.198
30.937
31.649
33.115
34.106
33.926
33.382
32.851
32.948
36.112
36.113
35.210
35.193
34.383
35.349
37.058
38.076
36.630
36.045
35.638
35.114
35.465
35.254
35.299
35.916
36.683
37.288
38.536
38.977
36.407
34.955
34.951
32.680
34.791
34.178
35.213
34.871
35.299
35.443
37.108
36.419
34.471
33.868
34.385
33.643
34.627
32.919
35.500
36.110
37.086
37.711
40.427
39.884
38.512
38.767




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=65582&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=65582&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=65582&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
131.42158333333331.517465018817024.535
235.27541666666671.650062503407535.225
336.38516666666671.281473926477803.863
435.03158333333331.094571186964714.428
536.22266666666672.501904159683667.508

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 31.4215833333333 & 1.51746501881702 & 4.535 \tabularnewline
2 & 35.2754166666667 & 1.65006250340753 & 5.225 \tabularnewline
3 & 36.3851666666667 & 1.28147392647780 & 3.863 \tabularnewline
4 & 35.0315833333333 & 1.09457118696471 & 4.428 \tabularnewline
5 & 36.2226666666667 & 2.50190415968366 & 7.508 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=65582&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]31.4215833333333[/C][C]1.51746501881702[/C][C]4.535[/C][/ROW]
[ROW][C]2[/C][C]35.2754166666667[/C][C]1.65006250340753[/C][C]5.225[/C][/ROW]
[ROW][C]3[/C][C]36.3851666666667[/C][C]1.28147392647780[/C][C]3.863[/C][/ROW]
[ROW][C]4[/C][C]35.0315833333333[/C][C]1.09457118696471[/C][C]4.428[/C][/ROW]
[ROW][C]5[/C][C]36.2226666666667[/C][C]2.50190415968366[/C][C]7.508[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=65582&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=65582&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
131.42158333333331.517465018817024.535
235.27541666666671.650062503407535.225
336.38516666666671.281473926477803.863
435.03158333333331.094571186964714.428
536.22266666666672.501904159683667.508







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-0.457716386435334
beta0.0592765351331399
S.D.0.151927858951487
T-STAT0.390162380634009
p-value0.722469196116164

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -0.457716386435334 \tabularnewline
beta & 0.0592765351331399 \tabularnewline
S.D. & 0.151927858951487 \tabularnewline
T-STAT & 0.390162380634009 \tabularnewline
p-value & 0.722469196116164 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=65582&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-0.457716386435334[/C][/ROW]
[ROW][C]beta[/C][C]0.0592765351331399[/C][/ROW]
[ROW][C]S.D.[/C][C]0.151927858951487[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.390162380634009[/C][/ROW]
[ROW][C]p-value[/C][C]0.722469196116164[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=65582&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=65582&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-0.457716386435334
beta0.0592765351331399
S.D.0.151927858951487
T-STAT0.390162380634009
p-value0.722469196116164







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-2.41329926968769
beta0.80220578002412
S.D.2.98819697531146
T-STAT0.268458132663931
p-value0.80574880460894
Lambda0.197794219975880

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -2.41329926968769 \tabularnewline
beta & 0.80220578002412 \tabularnewline
S.D. & 2.98819697531146 \tabularnewline
T-STAT & 0.268458132663931 \tabularnewline
p-value & 0.80574880460894 \tabularnewline
Lambda & 0.197794219975880 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=65582&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-2.41329926968769[/C][/ROW]
[ROW][C]beta[/C][C]0.80220578002412[/C][/ROW]
[ROW][C]S.D.[/C][C]2.98819697531146[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.268458132663931[/C][/ROW]
[ROW][C]p-value[/C][C]0.80574880460894[/C][/ROW]
[ROW][C]Lambda[/C][C]0.197794219975880[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=65582&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=65582&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-2.41329926968769
beta0.80220578002412
S.D.2.98819697531146
T-STAT0.268458132663931
p-value0.80574880460894
Lambda0.197794219975880



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')