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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, 27 Dec 2012 09:47:28 -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/Dec/27/t1356619867gfjrt62q8fbq1qx.htm/, Retrieved Tue, 31 Jan 2023 07:15:31 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=204774, Retrieved Tue, 31 Jan 2023 07:15:31 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact76
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Standard Deviation-Mean Plot] [Standard deviatio...] [2012-12-27 14:47:28] [4633288e60d40b4ed5f0b9573dd4d146] [Current]
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Dataseries X:
132
133,7
127
128,7
127,3
136,7
133,8
137,2
147,4
137,6
123,6
117,4
113,7
106,8
103,3
96,3
96,2
94,7
94,6
95,7
106,7
100,2
94,2
97,6
94,3
98
93,6
86,3
90,7
81,8
87,6
73,8
63,3
59,1
52,9
54,6
52,4
67,5
90,4
126
144,3
167,8
166,2
156
137
129,3
118
114,7
112,8
115,7
103,9
96,9
88,8
93
86,3
82,3
82,4
76,6
72,7
67,5
77,3
73,7
73
78,2
90,7
91,5
86,3
86,8
86,1
77,1
75,7
78,7
71,5
69,6
73,6
78,1
78,3
71,5
68,7
61,2
64,7
64,6
56,3
54,5
49,5
54
59,2
52,4
52,8
47,8
45,2
47,1
42,6
42,1
39,4
39,6




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=204774&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=204774&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=204774&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
1131.8666666666677.7768109067141330
21006.2741895528788919.5
37816.553878974153145.1
4122.46666666666736.777595287777115.4
589.908333333333315.217600953760148.2
681.25833333333336.5967565492215218.5
767.71666666666677.7099502808600123.8
847.64166666666676.1918507048793719.8

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 131.866666666667 & 7.77681090671413 & 30 \tabularnewline
2 & 100 & 6.27418955287889 & 19.5 \tabularnewline
3 & 78 & 16.5538789741531 & 45.1 \tabularnewline
4 & 122.466666666667 & 36.777595287777 & 115.4 \tabularnewline
5 & 89.9083333333333 & 15.2176009537601 & 48.2 \tabularnewline
6 & 81.2583333333333 & 6.59675654922152 & 18.5 \tabularnewline
7 & 67.7166666666667 & 7.70995028086001 & 23.8 \tabularnewline
8 & 47.6416666666667 & 6.19185070487937 & 19.8 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=204774&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]131.866666666667[/C][C]7.77681090671413[/C][C]30[/C][/ROW]
[ROW][C]2[/C][C]100[/C][C]6.27418955287889[/C][C]19.5[/C][/ROW]
[ROW][C]3[/C][C]78[/C][C]16.5538789741531[/C][C]45.1[/C][/ROW]
[ROW][C]4[/C][C]122.466666666667[/C][C]36.777595287777[/C][C]115.4[/C][/ROW]
[ROW][C]5[/C][C]89.9083333333333[/C][C]15.2176009537601[/C][C]48.2[/C][/ROW]
[ROW][C]6[/C][C]81.2583333333333[/C][C]6.59675654922152[/C][C]18.5[/C][/ROW]
[ROW][C]7[/C][C]67.7166666666667[/C][C]7.70995028086001[/C][C]23.8[/C][/ROW]
[ROW][C]8[/C][C]47.6416666666667[/C][C]6.19185070487937[/C][C]19.8[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=204774&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=204774&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
1131.8666666666677.7768109067141330
21006.2741895528788919.5
37816.553878974153145.1
4122.46666666666736.777595287777115.4
589.908333333333315.217600953760148.2
681.25833333333336.5967565492215218.5
767.71666666666677.7099502808600123.8
847.64166666666676.1918507048793719.8







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-2.12723152334244
beta0.167093403285743
S.D.0.138036787632475
T-STAT1.21049907167234
p-value0.271604246112021

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -2.12723152334244 \tabularnewline
beta & 0.167093403285743 \tabularnewline
S.D. & 0.138036787632475 \tabularnewline
T-STAT & 1.21049907167234 \tabularnewline
p-value & 0.271604246112021 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=204774&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-2.12723152334244[/C][/ROW]
[ROW][C]beta[/C][C]0.167093403285743[/C][/ROW]
[ROW][C]S.D.[/C][C]0.138036787632475[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.21049907167234[/C][/ROW]
[ROW][C]p-value[/C][C]0.271604246112021[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=204774&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=204774&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-2.12723152334244
beta0.167093403285743
S.D.0.138036787632475
T-STAT1.21049907167234
p-value0.271604246112021







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-1.3366343342937
beta0.82709667678637
S.D.0.721791239665124
T-STAT1.14589459020049
p-value0.295476453887701
Lambda0.17290332321363

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -1.3366343342937 \tabularnewline
beta & 0.82709667678637 \tabularnewline
S.D. & 0.721791239665124 \tabularnewline
T-STAT & 1.14589459020049 \tabularnewline
p-value & 0.295476453887701 \tabularnewline
Lambda & 0.17290332321363 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=204774&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-1.3366343342937[/C][/ROW]
[ROW][C]beta[/C][C]0.82709667678637[/C][/ROW]
[ROW][C]S.D.[/C][C]0.721791239665124[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.14589459020049[/C][/ROW]
[ROW][C]p-value[/C][C]0.295476453887701[/C][/ROW]
[ROW][C]Lambda[/C][C]0.17290332321363[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=204774&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=204774&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-1.3366343342937
beta0.82709667678637
S.D.0.721791239665124
T-STAT1.14589459020049
p-value0.295476453887701
Lambda0.17290332321363



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')