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Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationTue, 21 Dec 2010 17:50:58 +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/2010/Dec/21/t1292953730lee5t04h50yahiu.htm/, Retrieved Sun, 19 May 2024 21:02:26 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=113784, Retrieved Sun, 19 May 2024 21:02:26 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact102
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Explorative Data Analysis] [Run Sequence gebo...] [2008-12-12 13:32:37] [76963dc1903f0f612b6153510a3818cf]
- R  D  [Univariate Explorative Data Analysis] [Run Sequence gebo...] [2008-12-17 12:14:40] [76963dc1903f0f612b6153510a3818cf]
-         [Univariate Explorative Data Analysis] [Run Sequence Plot...] [2008-12-22 18:19:51] [1ce0d16c8f4225c977b42c8fa93bc163]
- RMP       [Univariate Data Series] [Identifying Integ...] [2009-11-22 12:08:06] [b98453cac15ba1066b407e146608df68]
- RMP         [Standard Deviation-Mean Plot] [Births] [2010-11-29 10:52:49] [b98453cac15ba1066b407e146608df68]
-   PD          [Standard Deviation-Mean Plot] [] [2010-12-20 14:28:14] [94f4aa1c01e87d8321fffb341ed4df07]
-    D              [Standard Deviation-Mean Plot] [] [2010-12-21 17:50:58] [d1991ab4912b5ede0ff54c26afa5d84c] [Current]
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Dataseries X:
77,33
75,28
77,43
73,25
68,41
72,87
65,61
69,04
57,84
51,07
47,48
44,01
45,29
43,8
55,48
75,73
101,42
116,07
135,81
132,69
124,05
109,65
102,79
94,09
92,23
90,6
92,6
81,71
76,36
71,44
75,26
70,3
67,68
67,65
61,92
58,34
55,04
62,5
59,44
60,03
64,24
74,33
74,41
69,75
72,03
68,18
63,01
61,71
63,52




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'RServer@AstonUniversity' @ vre.aston.ac.uk

\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 & 'RServer@AstonUniversity' @ vre.aston.ac.uk \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=113784&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]'RServer@AstonUniversity' @ vre.aston.ac.uk[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=113784&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=113784&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'RServer@AstonUniversity' @ vre.aston.ac.uk







Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
164.968333333333311.921570849311433.42
294.739166666666732.635816481654792.01
375.507511.618378955149234.26
465.38916666666676.2689950743659319.37

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 64.9683333333333 & 11.9215708493114 & 33.42 \tabularnewline
2 & 94.7391666666667 & 32.6358164816547 & 92.01 \tabularnewline
3 & 75.5075 & 11.6183789551492 & 34.26 \tabularnewline
4 & 65.3891666666667 & 6.26899507436593 & 19.37 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=113784&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]64.9683333333333[/C][C]11.9215708493114[/C][C]33.42[/C][/ROW]
[ROW][C]2[/C][C]94.7391666666667[/C][C]32.6358164816547[/C][C]92.01[/C][/ROW]
[ROW][C]3[/C][C]75.5075[/C][C]11.6183789551492[/C][C]34.26[/C][/ROW]
[ROW][C]4[/C][C]65.3891666666667[/C][C]6.26899507436593[/C][C]19.37[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=113784&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=113784&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
164.968333333333311.921570849311433.42
294.739166666666732.635816481654792.01
375.507511.618378955149234.26
465.38916666666676.2689950743659319.37







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-43.8110223606806
beta0.790703779787496
S.D.0.190486915396075
T-STAT4.15096112057567
p-value0.0534280660116487

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -43.8110223606806 \tabularnewline
beta & 0.790703779787496 \tabularnewline
S.D. & 0.190486915396075 \tabularnewline
T-STAT & 4.15096112057567 \tabularnewline
p-value & 0.0534280660116487 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=113784&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-43.8110223606806[/C][/ROW]
[ROW][C]beta[/C][C]0.790703779787496[/C][/ROW]
[ROW][C]S.D.[/C][C]0.190486915396075[/C][/ROW]
[ROW][C]T-STAT[/C][C]4.15096112057567[/C][/ROW]
[ROW][C]p-value[/C][C]0.0534280660116487[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=113784&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=113784&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-43.8110223606806
beta0.790703779787496
S.D.0.190486915396075
T-STAT4.15096112057567
p-value0.0534280660116487







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-12.4622394993411
beta3.48823339294201
S.D.1.17772609031929
T-STAT2.96183757973497
p-value0.097591133742607
Lambda-2.48823339294201

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -12.4622394993411 \tabularnewline
beta & 3.48823339294201 \tabularnewline
S.D. & 1.17772609031929 \tabularnewline
T-STAT & 2.96183757973497 \tabularnewline
p-value & 0.097591133742607 \tabularnewline
Lambda & -2.48823339294201 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=113784&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-12.4622394993411[/C][/ROW]
[ROW][C]beta[/C][C]3.48823339294201[/C][/ROW]
[ROW][C]S.D.[/C][C]1.17772609031929[/C][/ROW]
[ROW][C]T-STAT[/C][C]2.96183757973497[/C][/ROW]
[ROW][C]p-value[/C][C]0.097591133742607[/C][/ROW]
[ROW][C]Lambda[/C][C]-2.48823339294201[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=113784&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=113784&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-12.4622394993411
beta3.48823339294201
S.D.1.17772609031929
T-STAT2.96183757973497
p-value0.097591133742607
Lambda-2.48823339294201



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')