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Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationTue, 15 Jan 2013 07:37:51 -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/Jan/15/t1358253481k9p4bvf4e8koz6r.htm/, Retrieved Sat, 27 Apr 2024 22:30:17 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=205446, Retrieved Sat, 27 Apr 2024 22:30:17 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact110
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Standard Deviation-Mean Plot] [] [2013-01-15 12:37:51] [c9eeded7548c00546c4c5f04921b1379] [Current]
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Dataseries X:
102,89
102,64
103,33
103,56
103,6
104,24
105,31
105,4
105,89
105,89
105,54
106,15
106,14
105,85
106,27
106,51
106,82
106,53
107,14
107,39
107,33
107,53
107,42
108,25
108,26
108,93
109,43
109,61
109,74
110,12
110,16
110,44
111,23
112,86
112,77
113,04
112,79
113,87
114,28
115,51
116,76
116,91
116,47
116,94
117,24
116,82
117,48
117,11
117,31
117,77
118,37
117,91
118,12
118,02
117,77
117,85
118,68
118,9
118,6
118,21
118,37
117,43
117,5
116,71
116,98
117,74
117,44
117,85
118,54
118,73
118,68
118,19




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=205446&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=205446&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=205446&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
1104.5366666666671.289822632861763.51000000000001
2106.9316666666670.6962736313382632.40000000000001
3110.5491666666671.593700430007494.78
4116.0151.5427101300814.69
5118.1258333333330.4523365266406581.59
6117.8466666666670.6647533149198832.02000000000001

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 104.536666666667 & 1.28982263286176 & 3.51000000000001 \tabularnewline
2 & 106.931666666667 & 0.696273631338263 & 2.40000000000001 \tabularnewline
3 & 110.549166666667 & 1.59370043000749 & 4.78 \tabularnewline
4 & 116.015 & 1.542710130081 & 4.69 \tabularnewline
5 & 118.125833333333 & 0.452336526640658 & 1.59 \tabularnewline
6 & 117.846666666667 & 0.664753314919883 & 2.02000000000001 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=205446&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]104.536666666667[/C][C]1.28982263286176[/C][C]3.51000000000001[/C][/ROW]
[ROW][C]2[/C][C]106.931666666667[/C][C]0.696273631338263[/C][C]2.40000000000001[/C][/ROW]
[ROW][C]3[/C][C]110.549166666667[/C][C]1.59370043000749[/C][C]4.78[/C][/ROW]
[ROW][C]4[/C][C]116.015[/C][C]1.542710130081[/C][C]4.69[/C][/ROW]
[ROW][C]5[/C][C]118.125833333333[/C][C]0.452336526640658[/C][C]1.59[/C][/ROW]
[ROW][C]6[/C][C]117.846666666667[/C][C]0.664753314919883[/C][C]2.02000000000001[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=205446&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=205446&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
1104.5366666666671.289822632861763.51000000000001
2106.9316666666670.6962736313382632.40000000000001
3110.5491666666671.593700430007494.78
4116.0151.5427101300814.69
5118.1258333333330.4523365266406581.59
6117.8466666666670.6647533149198832.02000000000001







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha4.1344485186354
beta-0.0275474135146821
S.D.0.0400792548004001
T-STAT-0.687323495705492
p-value0.52965718529864

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 4.1344485186354 \tabularnewline
beta & -0.0275474135146821 \tabularnewline
S.D. & 0.0400792548004001 \tabularnewline
T-STAT & -0.687323495705492 \tabularnewline
p-value & 0.52965718529864 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=205446&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]4.1344485186354[/C][/ROW]
[ROW][C]beta[/C][C]-0.0275474135146821[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0400792548004001[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.687323495705492[/C][/ROW]
[ROW][C]p-value[/C][C]0.52965718529864[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=205446&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=205446&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)
alpha4.1344485186354
beta-0.0275474135146821
S.D.0.0400792548004001
T-STAT-0.687323495705492
p-value0.52965718529864







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha18.4698206220444
beta-3.92727679208701
S.D.4.5935405750586
T-STAT-0.854956373610982
p-value0.44076061144466
Lambda4.92727679208701

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 18.4698206220444 \tabularnewline
beta & -3.92727679208701 \tabularnewline
S.D. & 4.5935405750586 \tabularnewline
T-STAT & -0.854956373610982 \tabularnewline
p-value & 0.44076061144466 \tabularnewline
Lambda & 4.92727679208701 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=205446&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]18.4698206220444[/C][/ROW]
[ROW][C]beta[/C][C]-3.92727679208701[/C][/ROW]
[ROW][C]S.D.[/C][C]4.5935405750586[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.854956373610982[/C][/ROW]
[ROW][C]p-value[/C][C]0.44076061144466[/C][/ROW]
[ROW][C]Lambda[/C][C]4.92727679208701[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=205446&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=205446&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)
alpha18.4698206220444
beta-3.92727679208701
S.D.4.5935405750586
T-STAT-0.854956373610982
p-value0.44076061144466
Lambda4.92727679208701



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')