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Author's title

Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationThu, 05 Dec 2013 09:48:18 -0500
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/Dec/05/t1386254926uj073jz9478zbj2.htm/, Retrieved Thu, 28 Mar 2024 14:40:01 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=231137, Retrieved Thu, 28 Mar 2024 14:40:01 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact54
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Standard Deviation-Mean Plot] [] [2013-12-05 14:48:18] [e13de47ca0b629216b947109e84252a5] [Current]
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Dataseries X:
16.68
16.68
16.69
16.61
16.58
16.6
16.6
16.62
16.62
16.6
16.63
16.66
16.66
16.65
16.5
16.39
16.34
16.35
16.35
16.38
16.36
16.38
16.39
16.41
16.41
16.41
16.45
16.41
16.44
16.47
16.47
16.49
16.54
16.62
16.69
16.72
16.72
16.71
16.89
16.93
16.91
16.93
16.93
16.93
16.95
16.93
16.95
16.95
16.95
16.95
16.92
16.91
16.9
16.96
16.96
16.95
16.92
16.87
16.87
16.88
16.88
16.86
16.88
16.88
16.88
16.88
16.88
16.87
16.92
16.94
17.03
17.02
17.02
17.02
16.99
17.03
16.98
16.89
16.89
16.9
16.89
16.96
16.97
16.97




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 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 & 3 seconds \tabularnewline
R Server & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=231137&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]3 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=231137&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=231137&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 time3 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net







Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
116.63083333333330.03728473568568660.110000000000003
216.430.1130567033917850.32
316.510.1093784090377820.309999999999999
416.89416666666670.08543560396136030.239999999999998
516.920.03437758254761640.0899999999999999
616.910.05799686511904260.170000000000002
716.95916666666670.05384461369758740.140000000000001

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 16.6308333333333 & 0.0372847356856866 & 0.110000000000003 \tabularnewline
2 & 16.43 & 0.113056703391785 & 0.32 \tabularnewline
3 & 16.51 & 0.109378409037782 & 0.309999999999999 \tabularnewline
4 & 16.8941666666667 & 0.0854356039613603 & 0.239999999999998 \tabularnewline
5 & 16.92 & 0.0343775825476164 & 0.0899999999999999 \tabularnewline
6 & 16.91 & 0.0579968651190426 & 0.170000000000002 \tabularnewline
7 & 16.9591666666667 & 0.0538446136975874 & 0.140000000000001 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=231137&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]16.6308333333333[/C][C]0.0372847356856866[/C][C]0.110000000000003[/C][/ROW]
[ROW][C]2[/C][C]16.43[/C][C]0.113056703391785[/C][C]0.32[/C][/ROW]
[ROW][C]3[/C][C]16.51[/C][C]0.109378409037782[/C][C]0.309999999999999[/C][/ROW]
[ROW][C]4[/C][C]16.8941666666667[/C][C]0.0854356039613603[/C][C]0.239999999999998[/C][/ROW]
[ROW][C]5[/C][C]16.92[/C][C]0.0343775825476164[/C][C]0.0899999999999999[/C][/ROW]
[ROW][C]6[/C][C]16.91[/C][C]0.0579968651190426[/C][C]0.170000000000002[/C][/ROW]
[ROW][C]7[/C][C]16.9591666666667[/C][C]0.0538446136975874[/C][C]0.140000000000001[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=231137&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=231137&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
116.63083333333330.03728473568568660.110000000000003
216.430.1130567033917850.32
316.510.1093784090377820.309999999999999
416.89416666666670.08543560396136030.239999999999998
516.920.03437758254761640.0899999999999999
616.910.05799686511904260.170000000000002
716.95916666666670.05384461369758740.140000000000001







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha1.69602083644388
beta-0.09706069869585
S.D.0.0497192240704386
T-STAT-1.95217645710523
p-value0.108367758960869

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 1.69602083644388 \tabularnewline
beta & -0.09706069869585 \tabularnewline
S.D. & 0.0497192240704386 \tabularnewline
T-STAT & -1.95217645710523 \tabularnewline
p-value & 0.108367758960869 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=231137&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]1.69602083644388[/C][/ROW]
[ROW][C]beta[/C][C]-0.09706069869585[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0497192240704386[/C][/ROW]
[ROW][C]T-STAT[/C][C]-1.95217645710523[/C][/ROW]
[ROW][C]p-value[/C][C]0.108367758960869[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=231137&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=231137&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)
alpha1.69602083644388
beta-0.09706069869585
S.D.0.0497192240704386
T-STAT-1.95217645710523
p-value0.108367758960869







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha55.5217176520503
beta-20.6773508618295
S.D.13.5328206881611
T-STAT-1.52794094729406
p-value0.187064979940864
Lambda21.6773508618295

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 55.5217176520503 \tabularnewline
beta & -20.6773508618295 \tabularnewline
S.D. & 13.5328206881611 \tabularnewline
T-STAT & -1.52794094729406 \tabularnewline
p-value & 0.187064979940864 \tabularnewline
Lambda & 21.6773508618295 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=231137&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]55.5217176520503[/C][/ROW]
[ROW][C]beta[/C][C]-20.6773508618295[/C][/ROW]
[ROW][C]S.D.[/C][C]13.5328206881611[/C][/ROW]
[ROW][C]T-STAT[/C][C]-1.52794094729406[/C][/ROW]
[ROW][C]p-value[/C][C]0.187064979940864[/C][/ROW]
[ROW][C]Lambda[/C][C]21.6773508618295[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=231137&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=231137&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)
alpha55.5217176520503
beta-20.6773508618295
S.D.13.5328206881611
T-STAT-1.52794094729406
p-value0.187064979940864
Lambda21.6773508618295



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')