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Author's title

Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationFri, 30 Nov 2012 10:21:11 -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/2012/Nov/30/t1354288910gwr3woach8tx5jd.htm/, Retrieved Fri, 03 May 2024 22:30:04 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=195108, Retrieved Fri, 03 May 2024 22:30:04 +0000
QR Codes:

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] [spreidings- en ge...] [2012-11-30 15:21:11] [81048bae71988e8f0b979655b8024c85] [Current]
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Dataseries X:
2.08
2.09
2.36
2.99
2.75
1.58
1.69
1.3
1.97
1.84
1.96
1.86
2.75
2.62
2.41
3.61
2.03
1.45
1.4
1.3
1.58
2.1
2.27
2.54
2.55
2.05
2.32
2.6
2.1
1.61
1.55
1.12
1.39
2.18
1.94
2.27
2.41
2.2
2.58
2.9
2.12
1.34
1.07
0.86
1
1.54
1.29
1.44
2.6
2.77
3.31
3.2
2.07
1.42
1.43
1.28
1.59
1.68
2.01
2.52
2.74
3.06
2.69
2.32
1.67
1.04
0.98
0.86
0.97
1.3
1.82




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Herman Ole Andreas Wold' @ wold.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 & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=195108&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]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=195108&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=195108&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'Herman Ole Andreas Wold' @ wold.wessa.net







Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
12.039166666666670.474676125629281.69
22.171666666666670.6780833058680692.31
31.973333333333330.4650382845106481.48
41.729166666666670.682115137352972.04
52.156666666666670.7096776903936212.03

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 2.03916666666667 & 0.47467612562928 & 1.69 \tabularnewline
2 & 2.17166666666667 & 0.678083305868069 & 2.31 \tabularnewline
3 & 1.97333333333333 & 0.465038284510648 & 1.48 \tabularnewline
4 & 1.72916666666667 & 0.68211513735297 & 2.04 \tabularnewline
5 & 2.15666666666667 & 0.709677690393621 & 2.03 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=195108&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]2.03916666666667[/C][C]0.47467612562928[/C][C]1.69[/C][/ROW]
[ROW][C]2[/C][C]2.17166666666667[/C][C]0.678083305868069[/C][C]2.31[/C][/ROW]
[ROW][C]3[/C][C]1.97333333333333[/C][C]0.465038284510648[/C][C]1.48[/C][/ROW]
[ROW][C]4[/C][C]1.72916666666667[/C][C]0.68211513735297[/C][C]2.04[/C][/ROW]
[ROW][C]5[/C][C]2.15666666666667[/C][C]0.709677690393621[/C][C]2.03[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=195108&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=195108&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
12.039166666666670.474676125629281.69
22.171666666666670.6780833058680692.31
31.973333333333330.4650382845106481.48
41.729166666666670.682115137352972.04
52.156666666666670.7096776903936212.03







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha0.493822681349731
beta0.0536720096331612
S.D.0.389025847985032
T-STAT0.1379651504165
p-value0.89900765443675

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 0.493822681349731 \tabularnewline
beta & 0.0536720096331612 \tabularnewline
S.D. & 0.389025847985032 \tabularnewline
T-STAT & 0.1379651504165 \tabularnewline
p-value & 0.89900765443675 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=195108&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]0.493822681349731[/C][/ROW]
[ROW][C]beta[/C][C]0.0536720096331612[/C][/ROW]
[ROW][C]S.D.[/C][C]0.389025847985032[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.1379651504165[/C][/ROW]
[ROW][C]p-value[/C][C]0.89900765443675[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=195108&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=195108&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)
alpha0.493822681349731
beta0.0536720096331612
S.D.0.389025847985032
T-STAT0.1379651504165
p-value0.89900765443675







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-0.590383735354361
beta0.0939086338396435
S.D.1.31895918526171
T-STAT0.0711990445868195
p-value0.947720083273195
Lambda0.906091366160356

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -0.590383735354361 \tabularnewline
beta & 0.0939086338396435 \tabularnewline
S.D. & 1.31895918526171 \tabularnewline
T-STAT & 0.0711990445868195 \tabularnewline
p-value & 0.947720083273195 \tabularnewline
Lambda & 0.906091366160356 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=195108&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-0.590383735354361[/C][/ROW]
[ROW][C]beta[/C][C]0.0939086338396435[/C][/ROW]
[ROW][C]S.D.[/C][C]1.31895918526171[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.0711990445868195[/C][/ROW]
[ROW][C]p-value[/C][C]0.947720083273195[/C][/ROW]
[ROW][C]Lambda[/C][C]0.906091366160356[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=195108&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=195108&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-0.590383735354361
beta0.0939086338396435
S.D.1.31895918526171
T-STAT0.0711990445868195
p-value0.947720083273195
Lambda0.906091366160356



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')