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Author's title

Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationMon, 12 May 2008 12:11:26 -0600
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/May/12/t1210616161ei04mk4mvsndif9.htm/, Retrieved Tue, 14 May 2024 20:12:57 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=12401, Retrieved Tue, 14 May 2024 20:12:57 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact141
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Standard Deviation-Mean Plot] [Gemiddelde prijs ...] [2008-05-12 18:11:26] [b107ae504153eeaf670a683b6341ab4f] [Current]
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Dataseries X:
0.33
0.35
0.35
0.34
0.37
0.38
0.39
0.37
0.37
0.37
0.37
0.38
0.36
0.36
0.36
0.36
0.38
0.37
0.39
0.39
0.4
0.42
0.42
0.4
0.36
0.36
0.36
0.36
0.35
0.38
0.4
0.39
0.39
0.39
0.36
0.35
0.35
0.33
0.33
0.32
0.36
0.37
0.38
0.38
0.38
0.38
0.39
0.4
0.38
0.41
0.41
0.43
0.42
0.41
0.41
0.43
0.44
0.46
0.44
0.43
0.43
0.42
0.42
0.42
0.43
0.44
0.45
0.44
0.47
0.48
0.48
0.45
0.44
0.44
0.45
0.46
0.45
0.46
0.47
0.48
0.48
0.46
0.47
0.47
0.43
0.41
0.39
0.41
0.44
0.45
0.45
0.46
0.45
0.45
0.46
0.46




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=12401&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=12401&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=12401&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
10.3641666666666670.01781640374554420.06
20.3841666666666670.02274696116900550.06
30.3708333333333330.01781640374554420.05
40.3641666666666670.02609713789020950.08
50.42250.02050498830661810.08
60.4441666666666670.02234373344457960.06
70.4608333333333330.01378954368902450.04
80.4383333333333330.02329000305762630.07

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 0.364166666666667 & 0.0178164037455442 & 0.06 \tabularnewline
2 & 0.384166666666667 & 0.0227469611690055 & 0.06 \tabularnewline
3 & 0.370833333333333 & 0.0178164037455442 & 0.05 \tabularnewline
4 & 0.364166666666667 & 0.0260971378902095 & 0.08 \tabularnewline
5 & 0.4225 & 0.0205049883066181 & 0.08 \tabularnewline
6 & 0.444166666666667 & 0.0223437334445796 & 0.06 \tabularnewline
7 & 0.460833333333333 & 0.0137895436890245 & 0.04 \tabularnewline
8 & 0.438333333333333 & 0.0232900030576263 & 0.07 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=12401&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]0.364166666666667[/C][C]0.0178164037455442[/C][C]0.06[/C][/ROW]
[ROW][C]2[/C][C]0.384166666666667[/C][C]0.0227469611690055[/C][C]0.06[/C][/ROW]
[ROW][C]3[/C][C]0.370833333333333[/C][C]0.0178164037455442[/C][C]0.05[/C][/ROW]
[ROW][C]4[/C][C]0.364166666666667[/C][C]0.0260971378902095[/C][C]0.08[/C][/ROW]
[ROW][C]5[/C][C]0.4225[/C][C]0.0205049883066181[/C][C]0.08[/C][/ROW]
[ROW][C]6[/C][C]0.444166666666667[/C][C]0.0223437334445796[/C][C]0.06[/C][/ROW]
[ROW][C]7[/C][C]0.460833333333333[/C][C]0.0137895436890245[/C][C]0.04[/C][/ROW]
[ROW][C]8[/C][C]0.438333333333333[/C][C]0.0232900030576263[/C][C]0.07[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=12401&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=12401&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
10.3641666666666670.01781640374554420.06
20.3841666666666670.02274696116900550.06
30.3708333333333330.01781640374554420.05
40.3641666666666670.02609713789020950.08
50.42250.02050498830661810.08
60.4441666666666670.02234373344457960.06
70.4608333333333330.01378954368902450.04
80.4383333333333330.02329000305762630.07







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha0.0310391265903135
beta-0.0258244178530977
S.D.0.0388650259405164
T-STAT-0.664464186711785
p-value0.531085427605794

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 0.0310391265903135 \tabularnewline
beta & -0.0258244178530977 \tabularnewline
S.D. & 0.0388650259405164 \tabularnewline
T-STAT & -0.664464186711785 \tabularnewline
p-value & 0.531085427605794 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=12401&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]0.0310391265903135[/C][/ROW]
[ROW][C]beta[/C][C]-0.0258244178530977[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0388650259405164[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.664464186711785[/C][/ROW]
[ROW][C]p-value[/C][C]0.531085427605794[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=12401&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=12401&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)
alpha0.0310391265903135
beta-0.0258244178530977
S.D.0.0388650259405164
T-STAT-0.664464186711785
p-value0.531085427605794







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-4.40913784139187
beta-0.560195892609314
S.D.0.818508432888746
T-STAT-0.684410654918026
p-value0.519262830031954
Lambda1.56019589260931

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -4.40913784139187 \tabularnewline
beta & -0.560195892609314 \tabularnewline
S.D. & 0.818508432888746 \tabularnewline
T-STAT & -0.684410654918026 \tabularnewline
p-value & 0.519262830031954 \tabularnewline
Lambda & 1.56019589260931 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=12401&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-4.40913784139187[/C][/ROW]
[ROW][C]beta[/C][C]-0.560195892609314[/C][/ROW]
[ROW][C]S.D.[/C][C]0.818508432888746[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.684410654918026[/C][/ROW]
[ROW][C]p-value[/C][C]0.519262830031954[/C][/ROW]
[ROW][C]Lambda[/C][C]1.56019589260931[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=12401&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=12401&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-4.40913784139187
beta-0.560195892609314
S.D.0.818508432888746
T-STAT-0.684410654918026
p-value0.519262830031954
Lambda1.56019589260931



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')