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Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationThu, 05 Dec 2013 05:31:34 -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/t1386239508d2hzewn1wfv8mss.htm/, Retrieved Fri, 29 Mar 2024 06:30:46 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=230903, Retrieved Fri, 29 Mar 2024 06:30:46 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact101
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 10:31:34] [a69cf87a9dee79cf54f729839ea0968e] [Current]
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Dataseries X:
1.58
1.59
1.55
1.52
1.51
1.5
1.56
1.59
1.59
1.59
1.6
1.57
1.55
1.54
1.58
1.57
1.56
1.62
1.59
1.61
1.63
1.74
1.77
1.82
1.78
1.75
1.76
1.72
1.78
1.82
1.91
1.82
1.91
1.81
1.59
1.48
1.47
1.56
1.5
1.47
1.49
1.57
1.57
1.63
1.67
1.61
1.66
1.66
1.72
1.73
1.75
1.74
1.75
1.75
1.71
1.7
1.77
1.81
1.91
1.98
1.96
1.89
1.98
2.02
2.01
1.91
1.94
1.93
1.98
2.01
1.97
1.96
2.11
2.13
2.17
2.17
2.05
1.84
1.87
2.03
2.17
2.17
2.2
2.13




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Gwilym Jenkins' @ jenkins.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 & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=230903&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]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=230903&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=230903&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'Gwilym Jenkins' @ jenkins.wessa.net







Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
11.56250.03493500458643950.1
21.631666666666670.09311120754075190.28
31.760833333333330.1222856814135980.43
41.571666666666670.07553847103337880.2
51.776666666666670.08499554355519130.28
61.963333333333330.04052683360964980.13
72.086666666666670.1195699364262170.36

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 1.5625 & 0.0349350045864395 & 0.1 \tabularnewline
2 & 1.63166666666667 & 0.0931112075407519 & 0.28 \tabularnewline
3 & 1.76083333333333 & 0.122285681413598 & 0.43 \tabularnewline
4 & 1.57166666666667 & 0.0755384710333788 & 0.2 \tabularnewline
5 & 1.77666666666667 & 0.0849955435551913 & 0.28 \tabularnewline
6 & 1.96333333333333 & 0.0405268336096498 & 0.13 \tabularnewline
7 & 2.08666666666667 & 0.119569936426217 & 0.36 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=230903&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]1.5625[/C][C]0.0349350045864395[/C][C]0.1[/C][/ROW]
[ROW][C]2[/C][C]1.63166666666667[/C][C]0.0931112075407519[/C][C]0.28[/C][/ROW]
[ROW][C]3[/C][C]1.76083333333333[/C][C]0.122285681413598[/C][C]0.43[/C][/ROW]
[ROW][C]4[/C][C]1.57166666666667[/C][C]0.0755384710333788[/C][C]0.2[/C][/ROW]
[ROW][C]5[/C][C]1.77666666666667[/C][C]0.0849955435551913[/C][C]0.28[/C][/ROW]
[ROW][C]6[/C][C]1.96333333333333[/C][C]0.0405268336096498[/C][C]0.13[/C][/ROW]
[ROW][C]7[/C][C]2.08666666666667[/C][C]0.119569936426217[/C][C]0.36[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=230903&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=230903&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
11.56250.03493500458643950.1
21.631666666666670.09311120754075190.28
31.760833333333330.1222856814135980.43
41.571666666666670.07553847103337880.2
51.776666666666670.08499554355519130.28
61.963333333333330.04052683360964980.13
72.086666666666670.1195699364262170.36







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-0.0145557511562357
beta0.0544673180997471
S.D.0.0733524947336208
T-STAT0.742542135718013
p-value0.491148883547355

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -0.0145557511562357 \tabularnewline
beta & 0.0544673180997471 \tabularnewline
S.D. & 0.0733524947336208 \tabularnewline
T-STAT & 0.742542135718013 \tabularnewline
p-value & 0.491148883547355 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=230903&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-0.0145557511562357[/C][/ROW]
[ROW][C]beta[/C][C]0.0544673180997471[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0733524947336208[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.742542135718013[/C][/ROW]
[ROW][C]p-value[/C][C]0.491148883547355[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=230903&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=230903&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-0.0145557511562357
beta0.0544673180997471
S.D.0.0733524947336208
T-STAT0.742542135718013
p-value0.491148883547355







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-3.2659706937538
beta1.18165471374388
S.D.1.93384074802549
T-STAT0.61104034287745
p-value0.567881619505731
Lambda-0.18165471374388

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -3.2659706937538 \tabularnewline
beta & 1.18165471374388 \tabularnewline
S.D. & 1.93384074802549 \tabularnewline
T-STAT & 0.61104034287745 \tabularnewline
p-value & 0.567881619505731 \tabularnewline
Lambda & -0.18165471374388 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=230903&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-3.2659706937538[/C][/ROW]
[ROW][C]beta[/C][C]1.18165471374388[/C][/ROW]
[ROW][C]S.D.[/C][C]1.93384074802549[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.61104034287745[/C][/ROW]
[ROW][C]p-value[/C][C]0.567881619505731[/C][/ROW]
[ROW][C]Lambda[/C][C]-0.18165471374388[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=230903&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=230903&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-3.2659706937538
beta1.18165471374388
S.D.1.93384074802549
T-STAT0.61104034287745
p-value0.567881619505731
Lambda-0.18165471374388



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')