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Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationSat, 28 Apr 2012 16:55:28 -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/2012/Apr/28/t1335646559fblt9qinq6dnoy0.htm/, Retrieved Tue, 11 Jun 2024 19:07:44 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=165074, Retrieved Tue, 11 Jun 2024 19:07:44 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact121
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Standard Deviation-Mean Plot] [] [2012-04-28 20:55:28] [73066c1738da8cd0d8960e0866962dc1] [Current]
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Dataseries X:
4.95
4.95
4.96
4.93
4.95
4.96
4.97
5.01
5.04
5.07
5.07
5.08
5.07
5.08
5.09
5.09
5.14
5.17
5.17
5.18
5.18
5.18
5.17
5.17
5.18
5.18
5.26
5.26
5.26
5.28
5.28
5.31
5.37
5.42
5.43
5.43
5.44
5.5
5.52
5.55
5.55
5.55
5.55
5.55
5.55
5.55
5.55
5.56
5.57
5.59
5.69
5.73
5.76
5.77
5.77
5.79
5.79
5.79
5.79
5.79




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Gertrude Mary Cox' @ cox.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 & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=165074&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]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=165074&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=165074&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'Gertrude Mary Cox' @ cox.wessa.net







Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
14.9950.05567764362830030.15
25.140833333333330.04461111425588370.109999999999999
35.3050.08908627075124220.25
45.5350.03424510582152230.119999999999999
55.735833333333330.07890827048868290.22

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 4.995 & 0.0556776436283003 & 0.15 \tabularnewline
2 & 5.14083333333333 & 0.0446111142558837 & 0.109999999999999 \tabularnewline
3 & 5.305 & 0.0890862707512422 & 0.25 \tabularnewline
4 & 5.535 & 0.0342451058215223 & 0.119999999999999 \tabularnewline
5 & 5.73583333333333 & 0.0789082704886829 & 0.22 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=165074&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]4.995[/C][C]0.0556776436283003[/C][C]0.15[/C][/ROW]
[ROW][C]2[/C][C]5.14083333333333[/C][C]0.0446111142558837[/C][C]0.109999999999999[/C][/ROW]
[ROW][C]3[/C][C]5.305[/C][C]0.0890862707512422[/C][C]0.25[/C][/ROW]
[ROW][C]4[/C][C]5.535[/C][C]0.0342451058215223[/C][C]0.119999999999999[/C][/ROW]
[ROW][C]5[/C][C]5.73583333333333[/C][C]0.0789082704886829[/C][C]0.22[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=165074&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=165074&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
14.9950.05567764362830030.15
25.140833333333330.04461111425588370.109999999999999
35.3050.08908627075124220.25
45.5350.03424510582152230.119999999999999
55.735833333333330.07890827048868290.22







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-0.0298074793816143
beta0.0169051900612854
S.D.0.0435729834629402
T-STAT0.38797412336164
p-value0.723926970715922

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -0.0298074793816143 \tabularnewline
beta & 0.0169051900612854 \tabularnewline
S.D. & 0.0435729834629402 \tabularnewline
T-STAT & 0.38797412336164 \tabularnewline
p-value & 0.723926970715922 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=165074&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-0.0298074793816143[/C][/ROW]
[ROW][C]beta[/C][C]0.0169051900612854[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0435729834629402[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.38797412336164[/C][/ROW]
[ROW][C]p-value[/C][C]0.723926970715922[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=165074&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=165074&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-0.0298074793816143
beta0.0169051900612854
S.D.0.0435729834629402
T-STAT0.38797412336164
p-value0.723926970715922







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-4.61890168075773
beta1.04689389910017
S.D.4.06458204008873
T-STAT0.257564957177568
p-value0.813399497271458
Lambda-0.0468938991001684

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -4.61890168075773 \tabularnewline
beta & 1.04689389910017 \tabularnewline
S.D. & 4.06458204008873 \tabularnewline
T-STAT & 0.257564957177568 \tabularnewline
p-value & 0.813399497271458 \tabularnewline
Lambda & -0.0468938991001684 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=165074&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-4.61890168075773[/C][/ROW]
[ROW][C]beta[/C][C]1.04689389910017[/C][/ROW]
[ROW][C]S.D.[/C][C]4.06458204008873[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.257564957177568[/C][/ROW]
[ROW][C]p-value[/C][C]0.813399497271458[/C][/ROW]
[ROW][C]Lambda[/C][C]-0.0468938991001684[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=165074&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=165074&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-4.61890168075773
beta1.04689389910017
S.D.4.06458204008873
T-STAT0.257564957177568
p-value0.813399497271458
Lambda-0.0468938991001684



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')