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Author's title

Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationTue, 22 Mar 2016 20:46:31 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2016/Mar/22/t1458679669vueobzpi8vpfi4m.htm/, Retrieved Mon, 29 Apr 2024 08:55:58 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=294476, Retrieved Mon, 29 Apr 2024 08:55:58 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact57
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Standard Deviation-Mean Plot] [] [2016-03-22 20:46:31] [76c30f62b7052b57088120e90a652e05] [Current]
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Dataseries X:
99
99
99
100
101
101
100
101
100
101
100
100
102
102
102
102
102
102
103
103
103
103
103
103
104
104
104
106
106
106
106
107
106
106
106
106
106
106
106
105
105
105
105
105
104
104
104
104
103
104
104
103
103
103
103
103
103
104
104
104
104
104
105
105
104
104
104
104
103




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 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 & 1 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=294476&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]1 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=294476&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=294476&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 time1 seconds
R Server'Herman Ole Andreas Wold' @ wold.wessa.net







Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
1100.0833333333330.7929614610987592
2102.50.5222329678670941
3105.5833333333330.9962049198956223
4104.9166666666670.7929614610987592
5103.4166666666670.5149286505444371

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 100.083333333333 & 0.792961461098759 & 2 \tabularnewline
2 & 102.5 & 0.522232967867094 & 1 \tabularnewline
3 & 105.583333333333 & 0.996204919895622 & 3 \tabularnewline
4 & 104.916666666667 & 0.792961461098759 & 2 \tabularnewline
5 & 103.416666666667 & 0.514928650544437 & 1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=294476&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]100.083333333333[/C][C]0.792961461098759[/C][C]2[/C][/ROW]
[ROW][C]2[/C][C]102.5[/C][C]0.522232967867094[/C][C]1[/C][/ROW]
[ROW][C]3[/C][C]105.583333333333[/C][C]0.996204919895622[/C][C]3[/C][/ROW]
[ROW][C]4[/C][C]104.916666666667[/C][C]0.792961461098759[/C][C]2[/C][/ROW]
[ROW][C]5[/C][C]103.416666666667[/C][C]0.514928650544437[/C][C]1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=294476&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=294476&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
1100.0833333333330.7929614610987592
2102.50.5222329678670941
3105.5833333333330.9962049198956223
4104.9166666666670.7929614610987592
5103.4166666666670.5149286505444371







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-2.8326393537832
beta0.0344288213541543
S.D.0.0507907654141706
T-STAT0.677855926631668
p-value0.546461797784911

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -2.8326393537832 \tabularnewline
beta & 0.0344288213541543 \tabularnewline
S.D. & 0.0507907654141706 \tabularnewline
T-STAT & 0.677855926631668 \tabularnewline
p-value & 0.546461797784911 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=294476&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-2.8326393537832[/C][/ROW]
[ROW][C]beta[/C][C]0.0344288213541543[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0507907654141706[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.677855926631668[/C][/ROW]
[ROW][C]p-value[/C][C]0.546461797784911[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=294476&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=294476&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-2.8326393537832
beta0.0344288213541543
S.D.0.0507907654141706
T-STAT0.677855926631668
p-value0.546461797784911







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-20.2401151808107
beta4.28766816594671
S.D.7.52937289956027
T-STAT0.56945886770957
p-value0.608892943170684
Lambda-3.28766816594671

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -20.2401151808107 \tabularnewline
beta & 4.28766816594671 \tabularnewline
S.D. & 7.52937289956027 \tabularnewline
T-STAT & 0.56945886770957 \tabularnewline
p-value & 0.608892943170684 \tabularnewline
Lambda & -3.28766816594671 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=294476&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-20.2401151808107[/C][/ROW]
[ROW][C]beta[/C][C]4.28766816594671[/C][/ROW]
[ROW][C]S.D.[/C][C]7.52937289956027[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.56945886770957[/C][/ROW]
[ROW][C]p-value[/C][C]0.608892943170684[/C][/ROW]
[ROW][C]Lambda[/C][C]-3.28766816594671[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=294476&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=294476&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-20.2401151808107
beta4.28766816594671
S.D.7.52937289956027
T-STAT0.56945886770957
p-value0.608892943170684
Lambda-3.28766816594671



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')