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Author's title

Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationWed, 16 Mar 2016 14:10:59 +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/16/t1458137511pn2wdi1vwjdm5nk.htm/, Retrieved Tue, 07 May 2024 01:25:15 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=294150, Retrieved Tue, 07 May 2024 01:25:15 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact158
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Standard Deviation-Mean Plot] [Standaard deviati...] [2016-03-16 14:10:59] [8955cd9eab9a69f2891c3fcdee8de955] [Current]
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Dataseries X:
101.68
101.25
101.24
101.11
101.08
101.09
101.09
101.62
101.66
101.96
102.04
102.02
102.02
101.51
101.62
101.83
102.06
102.14
102.14
102.59
102.92
103.31
103.54
103.58
103.58
102.83
102.86
103.03
103.2
103.28
103.28
103.79
103.92
104.26
104.41
104.45
99.92
99.18
99.18
99.35
99.62
99.67
99.72
100.08
100.39
100.77
101.03
101.07
101.29
101.1
101.2
101.15
101.24
101.16
100.81
101.02
101.15
101.06
101.17
101.22
101.84
101.79
101.88
101.9
101.91
101.96
101.26
101.06
100.98
101.12
101.24
101.25




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ jenkins.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 & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=294150&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]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=294150&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=294150&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'Gwilym Jenkins' @ jenkins.wessa.net







Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
1101.4866666666670.3859659272133960.960000000000008
2102.4383333333330.7342012770021012.06999999999999
3103.5741666666670.5858398529746281.62
499.99833333333330.6784049921199951.88999999999999
5101.1308333333330.1258757203343720.480000000000004
6101.5158333333330.3904416691001310.97999999999999

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 101.486666666667 & 0.385965927213396 & 0.960000000000008 \tabularnewline
2 & 102.438333333333 & 0.734201277002101 & 2.06999999999999 \tabularnewline
3 & 103.574166666667 & 0.585839852974628 & 1.62 \tabularnewline
4 & 99.9983333333333 & 0.678404992119995 & 1.88999999999999 \tabularnewline
5 & 101.130833333333 & 0.125875720334372 & 0.480000000000004 \tabularnewline
6 & 101.515833333333 & 0.390441669100131 & 0.97999999999999 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=294150&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]101.486666666667[/C][C]0.385965927213396[/C][C]0.960000000000008[/C][/ROW]
[ROW][C]2[/C][C]102.438333333333[/C][C]0.734201277002101[/C][C]2.06999999999999[/C][/ROW]
[ROW][C]3[/C][C]103.574166666667[/C][C]0.585839852974628[/C][C]1.62[/C][/ROW]
[ROW][C]4[/C][C]99.9983333333333[/C][C]0.678404992119995[/C][C]1.88999999999999[/C][/ROW]
[ROW][C]5[/C][C]101.130833333333[/C][C]0.125875720334372[/C][C]0.480000000000004[/C][/ROW]
[ROW][C]6[/C][C]101.515833333333[/C][C]0.390441669100131[/C][C]0.97999999999999[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=294150&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=294150&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
1101.4866666666670.3859659272133960.960000000000008
2102.4383333333330.7342012770021012.06999999999999
3103.5741666666670.5858398529746281.62
499.99833333333330.6784049921199951.88999999999999
5101.1308333333330.1258757203343720.480000000000004
6101.5158333333330.3904416691001310.97999999999999







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-3.48027128216594
beta0.0389782586329846
S.D.0.0914727889218609
T-STAT0.426118620547157
p-value0.691951114750488

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -3.48027128216594 \tabularnewline
beta & 0.0389782586329846 \tabularnewline
S.D. & 0.0914727889218609 \tabularnewline
T-STAT & 0.426118620547157 \tabularnewline
p-value & 0.691951114750488 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=294150&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-3.48027128216594[/C][/ROW]
[ROW][C]beta[/C][C]0.0389782586329846[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0914727889218609[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.426118620547157[/C][/ROW]
[ROW][C]p-value[/C][C]0.691951114750488[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=294150&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=294150&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-3.48027128216594
beta0.0389782586329846
S.D.0.0914727889218609
T-STAT0.426118620547157
p-value0.691951114750488







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-60.1406406419289
beta12.8247765397562
S.D.26.5474627430667
T-STAT0.483088597350256
p-value0.654283613787759
Lambda-11.8247765397562

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -60.1406406419289 \tabularnewline
beta & 12.8247765397562 \tabularnewline
S.D. & 26.5474627430667 \tabularnewline
T-STAT & 0.483088597350256 \tabularnewline
p-value & 0.654283613787759 \tabularnewline
Lambda & -11.8247765397562 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=294150&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-60.1406406419289[/C][/ROW]
[ROW][C]beta[/C][C]12.8247765397562[/C][/ROW]
[ROW][C]S.D.[/C][C]26.5474627430667[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.483088597350256[/C][/ROW]
[ROW][C]p-value[/C][C]0.654283613787759[/C][/ROW]
[ROW][C]Lambda[/C][C]-11.8247765397562[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=294150&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=294150&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-60.1406406419289
beta12.8247765397562
S.D.26.5474627430667
T-STAT0.483088597350256
p-value0.654283613787759
Lambda-11.8247765397562



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')