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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, 26 Nov 2009 09:00:06 -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/26/t1259251345wtozxdgsb9rsltt.htm/, Retrieved Sun, 28 Apr 2024 20:21:51 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=60138, Retrieved Sun, 28 Apr 2024 20:21:51 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact108
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]
-    D          [Standard Deviation-Mean Plot] [WS 8.7] [2009-11-26 16:00:06] [51118f1042b56b16d340924f16263174] [Current]
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Dataseries X:
6,981656087
6,943025893
6,944087208
7,050989447
7,120606041
6,904349486
7,121413991
7,050469381
7,145274996
7,052721049
7,042723139
7,117124397
6,961485601
7,011844988
6,984531118
7,026693203
7,087406607
7,030326831
7,076315921
7,090826555
7,26304927
6,985086622
7,18946958
7,114769448
7,026337995
7,068597804
7,049168032
7,271912163
7,20362871
7,184704965
7,136960422
7,130178571
7,242153939
7,206377291
7,344848245
7,228098134
7,246296802
7,062705639
7,239143184
7,344072851
7,258412151
7,143933509
7,155240162
7,028733206
7,278973948
7,320990124
7,344912834
7,409741954
7,408833551
7,22314979
7,41052857
7,29593858
7,257566723
7,348651879
7,053239946
7,109389147
7,198557479
7,002064958
6,944665633
7,092158002




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=60138&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=60138&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60138&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
17.039536759583330.08031864142238440.240925510000000
27.0684838120.08914562944605690.301563669
37.174413855916670.09542971293775640.31851025
47.236096363666670.1173204783191950.381008748
57.195395354833330.1562589539876920.465862937000001

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 7.03953675958333 & 0.0803186414223844 & 0.240925510000000 \tabularnewline
2 & 7.068483812 & 0.0891456294460569 & 0.301563669 \tabularnewline
3 & 7.17441385591667 & 0.0954297129377564 & 0.31851025 \tabularnewline
4 & 7.23609636366667 & 0.117320478319195 & 0.381008748 \tabularnewline
5 & 7.19539535483333 & 0.156258953987692 & 0.465862937000001 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60138&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]7.03953675958333[/C][C]0.0803186414223844[/C][C]0.240925510000000[/C][/ROW]
[ROW][C]2[/C][C]7.068483812[/C][C]0.0891456294460569[/C][C]0.301563669[/C][/ROW]
[ROW][C]3[/C][C]7.17441385591667[/C][C]0.0954297129377564[/C][C]0.31851025[/C][/ROW]
[ROW][C]4[/C][C]7.23609636366667[/C][C]0.117320478319195[/C][C]0.381008748[/C][/ROW]
[ROW][C]5[/C][C]7.19539535483333[/C][C]0.156258953987692[/C][C]0.465862937000001[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=60138&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60138&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
17.039536759583330.08031864142238440.240925510000000
27.0684838120.08914562944605690.301563669
37.174413855916670.09542971293775640.31851025
47.236096363666670.1173204783191950.381008748
57.195395354833330.1562589539876920.465862937000001







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-1.70441555113832
beta0.253697987019539
S.D.0.146723396001468
T-STAT1.72909020601596
p-value0.182235133283849

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -1.70441555113832 \tabularnewline
beta & 0.253697987019539 \tabularnewline
S.D. & 0.146723396001468 \tabularnewline
T-STAT & 1.72909020601596 \tabularnewline
p-value & 0.182235133283849 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60138&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-1.70441555113832[/C][/ROW]
[ROW][C]beta[/C][C]0.253697987019539[/C][/ROW]
[ROW][C]S.D.[/C][C]0.146723396001468[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.72909020601596[/C][/ROW]
[ROW][C]p-value[/C][C]0.182235133283849[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=60138&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60138&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-1.70441555113832
beta0.253697987019539
S.D.0.146723396001468
T-STAT1.72909020601596
p-value0.182235133283849







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-35.5881203103557
beta16.953099561867
S.D.8.29182610175386
T-STAT2.04455560859883
p-value0.133460538317422
Lambda-15.953099561867

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -35.5881203103557 \tabularnewline
beta & 16.953099561867 \tabularnewline
S.D. & 8.29182610175386 \tabularnewline
T-STAT & 2.04455560859883 \tabularnewline
p-value & 0.133460538317422 \tabularnewline
Lambda & -15.953099561867 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60138&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-35.5881203103557[/C][/ROW]
[ROW][C]beta[/C][C]16.953099561867[/C][/ROW]
[ROW][C]S.D.[/C][C]8.29182610175386[/C][/ROW]
[ROW][C]T-STAT[/C][C]2.04455560859883[/C][/ROW]
[ROW][C]p-value[/C][C]0.133460538317422[/C][/ROW]
[ROW][C]Lambda[/C][C]-15.953099561867[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=60138&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60138&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-35.5881203103557
beta16.953099561867
S.D.8.29182610175386
T-STAT2.04455560859883
p-value0.133460538317422
Lambda-15.953099561867



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')