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Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationSat, 19 Mar 2016 15:35:05 +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/19/t1458401740pceh75nd48esw0p.htm/, Retrieved Tue, 07 May 2024 10:39:13 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=294331, Retrieved Tue, 07 May 2024 10:39:13 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact95
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Standard Deviation-Mean Plot] [] [2016-03-19 15:35:05] [60c466f2753cef60360c0cd0685abd02] [Current]
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Dataseries X:
93.91
94.27
94.55
94.66
94.78
94.91
95.2
95.48
95.56
95.75
95.91
96.16
96.32
96.58
97.08
97.22
97.49
97.62
97.83
98.12
98.29
98.47
98.64
98.67
98.82
99.17
99.38
99.53
99.54
99.76
100.02
100.22
100.55
100.94
100.99
101.07
101.19
101.94
102.25
102.49
102.58
102.74
103.01
103.19
103.44
103.62
103.74
103.82
103.96
104.7
105.13
105.26
105.44
105.73
105.83
105.97
106.13
106.49
106.74
106.82




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=294331&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=294331&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=294331&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
195.0950.6946221994724912.25
297.69416666666670.7852325461385022.35000000000001
399.99916666666670.757729363215382.25
4102.8341666666670.796040866165842.63
5105.6833333333330.8445583389433712.86

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 95.095 & 0.694622199472491 & 2.25 \tabularnewline
2 & 97.6941666666667 & 0.785232546138502 & 2.35000000000001 \tabularnewline
3 & 99.9991666666667 & 0.75772936321538 & 2.25 \tabularnewline
4 & 102.834166666667 & 0.79604086616584 & 2.63 \tabularnewline
5 & 105.683333333333 & 0.844558338943371 & 2.86 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=294331&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]95.095[/C][C]0.694622199472491[/C][C]2.25[/C][/ROW]
[ROW][C]2[/C][C]97.6941666666667[/C][C]0.785232546138502[/C][C]2.35000000000001[/C][/ROW]
[ROW][C]3[/C][C]99.9991666666667[/C][C]0.75772936321538[/C][C]2.25[/C][/ROW]
[ROW][C]4[/C][C]102.834166666667[/C][C]0.79604086616584[/C][C]2.63[/C][/ROW]
[ROW][C]5[/C][C]105.683333333333[/C][C]0.844558338943371[/C][C]2.86[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=294331&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=294331&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
195.0950.6946221994724912.25
297.69416666666670.7852325461385022.35000000000001
399.99916666666670.757729363215382.25
4102.8341666666670.796040866165842.63
5105.6833333333330.8445583389433712.86







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-0.416493169821177
beta0.0118902449696372
S.D.0.00335009899736603
T-STAT3.54922197194345
p-value0.0381118483516187

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -0.416493169821177 \tabularnewline
beta & 0.0118902449696372 \tabularnewline
S.D. & 0.00335009899736603 \tabularnewline
T-STAT & 3.54922197194345 \tabularnewline
p-value & 0.0381118483516187 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=294331&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-0.416493169821177[/C][/ROW]
[ROW][C]beta[/C][C]0.0118902449696372[/C][/ROW]
[ROW][C]S.D.[/C][C]0.00335009899736603[/C][/ROW]
[ROW][C]T-STAT[/C][C]3.54922197194345[/C][/ROW]
[ROW][C]p-value[/C][C]0.0381118483516187[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=294331&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=294331&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-0.416493169821177
beta0.0118902449696372
S.D.0.00335009899736603
T-STAT3.54922197194345
p-value0.0381118483516187







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-7.41736720773259
beta1.55439577332212
S.D.0.446112578021859
T-STAT3.48431281676608
p-value0.0399305390668978
Lambda-0.55439577332212

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -7.41736720773259 \tabularnewline
beta & 1.55439577332212 \tabularnewline
S.D. & 0.446112578021859 \tabularnewline
T-STAT & 3.48431281676608 \tabularnewline
p-value & 0.0399305390668978 \tabularnewline
Lambda & -0.55439577332212 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=294331&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-7.41736720773259[/C][/ROW]
[ROW][C]beta[/C][C]1.55439577332212[/C][/ROW]
[ROW][C]S.D.[/C][C]0.446112578021859[/C][/ROW]
[ROW][C]T-STAT[/C][C]3.48431281676608[/C][/ROW]
[ROW][C]p-value[/C][C]0.0399305390668978[/C][/ROW]
[ROW][C]Lambda[/C][C]-0.55439577332212[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=294331&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=294331&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-7.41736720773259
beta1.55439577332212
S.D.0.446112578021859
T-STAT3.48431281676608
p-value0.0399305390668978
Lambda-0.55439577332212



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')