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Author's title

Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationSat, 17 May 2008 15:16:15 -0600
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2008/May/17/t1211059265o9z5f2i5r6bmet7.htm/, Retrieved Tue, 14 May 2024 01:54:04 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=12706, Retrieved Tue, 14 May 2024 01:54:04 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact187
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Standard Deviation-Mean Plot] [Standard Deviatio...] [2008-05-17 21:16:15] [b64702de7eac3a2282df81a39c87ddc7] [Current]
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Dataseries X:
20.66
20.66
20.67
20.71
20.73
20.73
20.74
20.74
20.75
20.75
20.77
20.78
20.78
20.8
20.84
20.85
20.86
20.86
20.86
20.86
20.9
20.92
20.95
20.95
20.95
20.96
21.1
21.18
21.19
21.19
21.19
21.19
21.19
21.21
21.22
21.22
21.22
21.23
21.41
21.42
21.43
21.44
21.44
21.44
21.48
21.53
21.54
21.54
21.54
21.54
21.54
21.54
21.54
21.54
21.54
21.54
21.57
21.6
21.61
21.6
21.6
21.71
21.75
21.84
21.85
21.92
21.92
21.93
22
22
21.99
22.01
22.01




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001

\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 & 'Herman Ole Andreas Wold' @ 193.190.124.10:1001 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=12706&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]'Herman Ole Andreas Wold' @ 193.190.124.10:1001[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=12706&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=12706&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'Herman Ole Andreas Wold' @ 193.190.124.10:1001







Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
120.72416666666670.04100073909163810.120000000000001
220.86916666666670.05299371031861510.169999999999998
321.14916666666670.09577040094397490.270000000000000
421.42666666666670.1050829398257600.32
521.55833333333330.02855085839605450.0700000000000003
621.87666666666670.1314488032611470.41

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 20.7241666666667 & 0.0410007390916381 & 0.120000000000001 \tabularnewline
2 & 20.8691666666667 & 0.0529937103186151 & 0.169999999999998 \tabularnewline
3 & 21.1491666666667 & 0.0957704009439749 & 0.270000000000000 \tabularnewline
4 & 21.4266666666667 & 0.105082939825760 & 0.32 \tabularnewline
5 & 21.5583333333333 & 0.0285508583960545 & 0.0700000000000003 \tabularnewline
6 & 21.8766666666667 & 0.131448803261147 & 0.41 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=12706&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]20.7241666666667[/C][C]0.0410007390916381[/C][C]0.120000000000001[/C][/ROW]
[ROW][C]2[/C][C]20.8691666666667[/C][C]0.0529937103186151[/C][C]0.169999999999998[/C][/ROW]
[ROW][C]3[/C][C]21.1491666666667[/C][C]0.0957704009439749[/C][C]0.270000000000000[/C][/ROW]
[ROW][C]4[/C][C]21.4266666666667[/C][C]0.105082939825760[/C][C]0.32[/C][/ROW]
[ROW][C]5[/C][C]21.5583333333333[/C][C]0.0285508583960545[/C][C]0.0700000000000003[/C][/ROW]
[ROW][C]6[/C][C]21.8766666666667[/C][C]0.131448803261147[/C][C]0.41[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=12706&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=12706&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
120.72416666666670.04100073909163810.120000000000001
220.86916666666670.05299371031861510.169999999999998
321.14916666666670.09577040094397490.270000000000000
421.42666666666670.1050829398257600.32
521.55833333333330.02855085839605450.0700000000000003
621.87666666666670.1314488032611470.41







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-1.05487353751311
beta0.0531651031007283
S.D.0.0385297609560882
T-STAT1.37984513221662
p-value0.239745021888156

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -1.05487353751311 \tabularnewline
beta & 0.0531651031007283 \tabularnewline
S.D. & 0.0385297609560882 \tabularnewline
T-STAT & 1.37984513221662 \tabularnewline
p-value & 0.239745021888156 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=12706&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-1.05487353751311[/C][/ROW]
[ROW][C]beta[/C][C]0.0531651031007283[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0385297609560882[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.37984513221662[/C][/ROW]
[ROW][C]p-value[/C][C]0.239745021888156[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=12706&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=12706&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-1.05487353751311
beta0.0531651031007283
S.D.0.0385297609560882
T-STAT1.37984513221662
p-value0.239745021888156







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-40.5486142081915
beta12.3746598183344
S.D.13.3123818067933
T-STAT0.929560164208903
p-value0.405216888642434
Lambda-11.3746598183344

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -40.5486142081915 \tabularnewline
beta & 12.3746598183344 \tabularnewline
S.D. & 13.3123818067933 \tabularnewline
T-STAT & 0.929560164208903 \tabularnewline
p-value & 0.405216888642434 \tabularnewline
Lambda & -11.3746598183344 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=12706&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-40.5486142081915[/C][/ROW]
[ROW][C]beta[/C][C]12.3746598183344[/C][/ROW]
[ROW][C]S.D.[/C][C]13.3123818067933[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.929560164208903[/C][/ROW]
[ROW][C]p-value[/C][C]0.405216888642434[/C][/ROW]
[ROW][C]Lambda[/C][C]-11.3746598183344[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=12706&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=12706&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-40.5486142081915
beta12.3746598183344
S.D.13.3123818067933
T-STAT0.929560164208903
p-value0.405216888642434
Lambda-11.3746598183344



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')