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Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationMon, 15 Aug 2016 13:26:55 +0100
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/Aug/15/t14712640641caeci2n5ysw9pt.htm/, Retrieved Sat, 27 Apr 2024 23:30:05 +0200
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=, Retrieved Sat, 27 Apr 2024 23:30:05 +0200
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact0

Tree of Dependent Computations

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
540
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690
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710
710
540
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690
510
390
270
530
510
670
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830

Tables (Output of Computation)





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=&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=&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=&T=0

As an alternative you can also use a QR Code:  
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
1580.83333333333372.4202800995479270
2565.83333333333398.761267097926360
3541.666666666667105.987420637231350
4546.666666666667116.098182064957430
5542.5137.187661782882460
6558.333333333333138.09307357611460
7569.166666666667135.20747244905500
8575.833333333333145.255782756634500
9571.666666666667158.448921126212560

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 580.833333333333 & 72.4202800995479 & 270 \tabularnewline
2 & 565.833333333333 & 98.761267097926 & 360 \tabularnewline
3 & 541.666666666667 & 105.987420637231 & 350 \tabularnewline
4 & 546.666666666667 & 116.098182064957 & 430 \tabularnewline
5 & 542.5 & 137.187661782882 & 460 \tabularnewline
6 & 558.333333333333 & 138.09307357611 & 460 \tabularnewline
7 & 569.166666666667 & 135.20747244905 & 500 \tabularnewline
8 & 575.833333333333 & 145.255782756634 & 500 \tabularnewline
9 & 571.666666666667 & 158.448921126212 & 560 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=&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]580.833333333333[/C][C]72.4202800995479[/C][C]270[/C][/ROW]
[ROW][C]2[/C][C]565.833333333333[/C][C]98.761267097926[/C][C]360[/C][/ROW]
[ROW][C]3[/C][C]541.666666666667[/C][C]105.987420637231[/C][C]350[/C][/ROW]
[ROW][C]4[/C][C]546.666666666667[/C][C]116.098182064957[/C][C]430[/C][/ROW]
[ROW][C]5[/C][C]542.5[/C][C]137.187661782882[/C][C]460[/C][/ROW]
[ROW][C]6[/C][C]558.333333333333[/C][C]138.09307357611[/C][C]460[/C][/ROW]
[ROW][C]7[/C][C]569.166666666667[/C][C]135.20747244905[/C][C]500[/C][/ROW]
[ROW][C]8[/C][C]575.833333333333[/C][C]145.255782756634[/C][C]500[/C][/ROW]
[ROW][C]9[/C][C]571.666666666667[/C][C]158.448921126212[/C][C]560[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=&T=1

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
1580.83333333333372.4202800995479270
2565.83333333333398.761267097926360
3541.666666666667105.987420637231350
4546.666666666667116.098182064957430
5542.5137.187661782882460
6558.333333333333138.09307357611460
7569.166666666667135.20747244905500
8575.833333333333145.255782756634500
9571.666666666667158.448921126212560






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha183.371409281724
beta-0.107448317059865
S.D.0.688757001617609
T-STAT-0.156003230177715
p-value0.880434120508981

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 183.371409281724 \tabularnewline
beta & -0.107448317059865 \tabularnewline
S.D. & 0.688757001617609 \tabularnewline
T-STAT & -0.156003230177715 \tabularnewline
p-value & 0.880434120508981 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]183.371409281724[/C][/ROW]
[ROW][C]beta[/C][C]-0.107448317059865[/C][/ROW]
[ROW][C]S.D.[/C][C]0.688757001617609[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.156003230177715[/C][/ROW]
[ROW][C]p-value[/C][C]0.880434120508981[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=&T=2

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha183.371409281724
beta-0.107448317059865
S.D.0.688757001617609
T-STAT-0.156003230177715
p-value0.880434120508981






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha12.9940471607853
beta-1.29633550728143
S.D.3.45582772786263
T-STAT-0.375115778147653
p-value0.718681736243556
Lambda2.29633550728143

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 12.9940471607853 \tabularnewline
beta & -1.29633550728143 \tabularnewline
S.D. & 3.45582772786263 \tabularnewline
T-STAT & -0.375115778147653 \tabularnewline
p-value & 0.718681736243556 \tabularnewline
Lambda & 2.29633550728143 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]12.9940471607853[/C][/ROW]
[ROW][C]beta[/C][C]-1.29633550728143[/C][/ROW]
[ROW][C]S.D.[/C][C]3.45582772786263[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.375115778147653[/C][/ROW]
[ROW][C]p-value[/C][C]0.718681736243556[/C][/ROW]
[ROW][C]Lambda[/C][C]2.29633550728143[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=&T=3

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha12.9940471607853
beta-1.29633550728143
S.D.3.45582772786263
T-STAT-0.375115778147653
p-value0.718681736243556
Lambda2.29633550728143


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 12 ;
Parameters (R input):
par1 = 12 ;
R code (references can be found in the software module):
par1 <- '12'
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')