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Author's title

Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationSun, 26 May 2013 13:40:35 -0400
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2013/May/26/t1369590471ijq3cbi0uj5aenb.htm/, Retrieved Mon, 29 Apr 2024 08:39:01 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=210644, Retrieved Mon, 29 Apr 2024 08:39:01 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact86
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Standard Deviation-Mean Plot] [] [2013-05-26 17:40:35] [01f42343b359ee979b76c94d8b15b060] [Current]
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Dataseries X:
22.38
22.38
22.38
22.38
22.41
22.41
22.41
22.41
22.41
22.41
22.41
22.41
22.41
22.41
22.41
22.41
23.11
23.11
23.11
23.11
23.11
23.11
23.11
23.11
23.11
23.11
23.11
23.11
23.82
23.82
23.82
23.82
23.82
23.82
23.82
23.82
23.82
23.82
23.82
23.82
26.1
26.1
26.1
26.1
26.1
26.1
26.1
26.1
26.1
26.1
26.1
26.1
27.07
27.07
27.07
27.07
27.07
27.07
27.07
27.07
27.07
27.07
27.07
27.07
27.45
27.45
27.45
27.45
27.45
27.45
27.45
27.45




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'George Udny Yule' @ yule.wessa.net

\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 & 'George Udny Yule' @ yule.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=210644&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]'George Udny Yule' @ yule.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=210644&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=210644&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'George Udny Yule' @ yule.wessa.net







Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
122.40.01477097891752050.0300000000000011
222.87666666666670.3446561747421310.699999999999999
323.58333333333330.3495798343813050.710000000000001
425.341.122594397731522.28
526.74666666666670.477594984999810.969999999999999
627.32333333333330.1870990662885850.379999999999999

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 22.4 & 0.0147709789175205 & 0.0300000000000011 \tabularnewline
2 & 22.8766666666667 & 0.344656174742131 & 0.699999999999999 \tabularnewline
3 & 23.5833333333333 & 0.349579834381305 & 0.710000000000001 \tabularnewline
4 & 25.34 & 1.12259439773152 & 2.28 \tabularnewline
5 & 26.7466666666667 & 0.47759498499981 & 0.969999999999999 \tabularnewline
6 & 27.3233333333333 & 0.187099066288585 & 0.379999999999999 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=210644&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]22.4[/C][C]0.0147709789175205[/C][C]0.0300000000000011[/C][/ROW]
[ROW][C]2[/C][C]22.8766666666667[/C][C]0.344656174742131[/C][C]0.699999999999999[/C][/ROW]
[ROW][C]3[/C][C]23.5833333333333[/C][C]0.349579834381305[/C][C]0.710000000000001[/C][/ROW]
[ROW][C]4[/C][C]25.34[/C][C]1.12259439773152[/C][C]2.28[/C][/ROW]
[ROW][C]5[/C][C]26.7466666666667[/C][C]0.47759498499981[/C][C]0.969999999999999[/C][/ROW]
[ROW][C]6[/C][C]27.3233333333333[/C][C]0.187099066288585[/C][C]0.379999999999999[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=210644&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=210644&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
122.40.01477097891752050.0300000000000011
222.87666666666670.3446561747421310.699999999999999
323.58333333333330.3495798343813050.710000000000001
425.341.122594397731522.28
526.74666666666670.477594984999810.969999999999999
627.32333333333330.1870990662885850.379999999999999







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-0.863336442692169
beta0.0517725372173324
S.D.0.0885104029870584
T-STAT0.584931663060018
p-value0.589999099315802

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -0.863336442692169 \tabularnewline
beta & 0.0517725372173324 \tabularnewline
S.D. & 0.0885104029870584 \tabularnewline
T-STAT & 0.584931663060018 \tabularnewline
p-value & 0.589999099315802 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=210644&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-0.863336442692169[/C][/ROW]
[ROW][C]beta[/C][C]0.0517725372173324[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0885104029870584[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.584931663060018[/C][/ROW]
[ROW][C]p-value[/C][C]0.589999099315802[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=210644&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=210644&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-0.863336442692169
beta0.0517725372173324
S.D.0.0885104029870584
T-STAT0.584931663060018
p-value0.589999099315802







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-28.7848347615788
beta8.53407126337322
S.D.7.79177793048212
T-STAT1.0952662331388
p-value0.334921916395836
Lambda-7.53407126337322

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -28.7848347615788 \tabularnewline
beta & 8.53407126337322 \tabularnewline
S.D. & 7.79177793048212 \tabularnewline
T-STAT & 1.0952662331388 \tabularnewline
p-value & 0.334921916395836 \tabularnewline
Lambda & -7.53407126337322 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=210644&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-28.7848347615788[/C][/ROW]
[ROW][C]beta[/C][C]8.53407126337322[/C][/ROW]
[ROW][C]S.D.[/C][C]7.79177793048212[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.0952662331388[/C][/ROW]
[ROW][C]p-value[/C][C]0.334921916395836[/C][/ROW]
[ROW][C]Lambda[/C][C]-7.53407126337322[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=210644&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=210644&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-28.7848347615788
beta8.53407126337322
S.D.7.79177793048212
T-STAT1.0952662331388
p-value0.334921916395836
Lambda-7.53407126337322



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')