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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, 05 Dec 2013 12:28:44 -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/Dec/05/t13862645490lnemvkrgvj7icr.htm/, Retrieved Thu, 28 Mar 2024 20:20:57 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=231195, Retrieved Thu, 28 Mar 2024 20:20:57 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact70
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Standard Deviation-Mean Plot] [] [2013-12-05 17:28:44] [6864a9b8bb386dbf93fa34bd3826a254] [Current]
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Dataseries X:
6.11
6.13
6.15
6.15
6.16
6.18
6.21
6.22
6.23
6.26
6.28
6.28
6.29
6.32
6.36
6.37
6.38
6.38
6.4
6.41
6.42
6.43
6.44
6.47
6.47
6.48
6.51
6.54
6.56
6.57
6.6
6.62
6.65
6.71
6.76
6.78
6.8
6.83
6.86
6.86
6.87
6.88
6.9
6.92
6.93
6.94
6.96
6.98
6.99
7.01
7.06
7.07
7.08
7.08
7.1
7.11
7.22
7.24
7.25
7.26
7.27
7.3
7.32
7.34
7.35
7.36
7.39
7.41
7.43
7.46
7.47
7.5
7.51
7.52
7.58
7.59
7.63
7.64
7.64
7.66
7.67
7.68
7.69
7.7




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Sir Maurice George Kendall' @ kendall.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 & 3 seconds \tabularnewline
R Server & 'Sir Maurice George Kendall' @ kendall.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=231195&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]3 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Maurice George Kendall' @ kendall.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=231195&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=231195&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 time3 seconds
R Server'Sir Maurice George Kendall' @ kendall.wessa.net







Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
16.196666666666670.05851702678915270.17
26.389166666666670.05071459057282910.18
36.604166666666670.1037004719313650.31
46.894166666666670.05384461369758750.180000000000001
57.12250.09516731677323980.27
67.383333333333330.07215303601415960.23
77.625833333333330.06331139971074210.19

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 6.19666666666667 & 0.0585170267891527 & 0.17 \tabularnewline
2 & 6.38916666666667 & 0.0507145905728291 & 0.18 \tabularnewline
3 & 6.60416666666667 & 0.103700471931365 & 0.31 \tabularnewline
4 & 6.89416666666667 & 0.0538446136975875 & 0.180000000000001 \tabularnewline
5 & 7.1225 & 0.0951673167732398 & 0.27 \tabularnewline
6 & 7.38333333333333 & 0.0721530360141596 & 0.23 \tabularnewline
7 & 7.62583333333333 & 0.0633113997107421 & 0.19 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=231195&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]6.19666666666667[/C][C]0.0585170267891527[/C][C]0.17[/C][/ROW]
[ROW][C]2[/C][C]6.38916666666667[/C][C]0.0507145905728291[/C][C]0.18[/C][/ROW]
[ROW][C]3[/C][C]6.60416666666667[/C][C]0.103700471931365[/C][C]0.31[/C][/ROW]
[ROW][C]4[/C][C]6.89416666666667[/C][C]0.0538446136975875[/C][C]0.180000000000001[/C][/ROW]
[ROW][C]5[/C][C]7.1225[/C][C]0.0951673167732398[/C][C]0.27[/C][/ROW]
[ROW][C]6[/C][C]7.38333333333333[/C][C]0.0721530360141596[/C][C]0.23[/C][/ROW]
[ROW][C]7[/C][C]7.62583333333333[/C][C]0.0633113997107421[/C][C]0.19[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=231195&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=231195&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
16.196666666666670.05851702678915270.17
26.389166666666670.05071459057282910.18
36.604166666666670.1037004719313650.31
46.894166666666670.05384461369758750.180000000000001
57.12250.09516731677323980.27
67.383333333333330.07215303601415960.23
77.625833333333330.06331139971074210.19







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha0.0296703740869195
beta0.00600872818847142
S.D.0.0174514164436295
T-STAT0.344311775945548
p-value0.744620361054614

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 0.0296703740869195 \tabularnewline
beta & 0.00600872818847142 \tabularnewline
S.D. & 0.0174514164436295 \tabularnewline
T-STAT & 0.344311775945548 \tabularnewline
p-value & 0.744620361054614 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=231195&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]0.0296703740869195[/C][/ROW]
[ROW][C]beta[/C][C]0.00600872818847142[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0174514164436295[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.344311775945548[/C][/ROW]
[ROW][C]p-value[/C][C]0.744620361054614[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=231195&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=231195&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)
alpha0.0296703740869195
beta0.00600872818847142
S.D.0.0174514164436295
T-STAT0.344311775945548
p-value0.744620361054614







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-4.23941586145549
beta0.8099652959807
S.D.1.58723876854917
T-STAT0.510298331939723
p-value0.631564800577503
Lambda0.1900347040193

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -4.23941586145549 \tabularnewline
beta & 0.8099652959807 \tabularnewline
S.D. & 1.58723876854917 \tabularnewline
T-STAT & 0.510298331939723 \tabularnewline
p-value & 0.631564800577503 \tabularnewline
Lambda & 0.1900347040193 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=231195&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-4.23941586145549[/C][/ROW]
[ROW][C]beta[/C][C]0.8099652959807[/C][/ROW]
[ROW][C]S.D.[/C][C]1.58723876854917[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.510298331939723[/C][/ROW]
[ROW][C]p-value[/C][C]0.631564800577503[/C][/ROW]
[ROW][C]Lambda[/C][C]0.1900347040193[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=231195&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=231195&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-4.23941586145549
beta0.8099652959807
S.D.1.58723876854917
T-STAT0.510298331939723
p-value0.631564800577503
Lambda0.1900347040193



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')