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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, 21 Nov 2016 14:39:25 +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/Nov/21/t1479739178vrjtlew1iksa7er.htm/, Retrieved Mon, 06 May 2024 15:26:32 +0200
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=, Retrieved Mon, 06 May 2024 15:26:32 +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 
831.5
831
830
828.4
828.1
827.6
828.2
828.2
828.7
830.5
831
831.9
832.2
831.9
830.6
829.7
828.8
826.7
825.8
825.4
825
825.6
824.6
824.5
822.6
822
821.2
820.4
819.4
819.7
818.2
817.7
817.5
817.7
817.5
816.9
820.3
819.7
819.4
818.6
818.2
817.6
817.3
816.7
817
817.6
817.8
817.8
820.9
820.7
820.6
820.8
820.4
820.2
819.8
819.6
819.6
819.8
819.9
820.3
822.9
821.9
820.6
818.9
817.3
815.6
813.8
812.1
810.8
809.6
808.7
807.3

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'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=&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=&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'Gwilym Jenkins' @ jenkins.wessa.net






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
1829.5916666666671.543583983834854.29999999999995
2827.5666666666672.90370713941947.70000000000005
3819.2333333333331.946714403731835.70000000000005
4818.1666666666671.119523708249773.59999999999991
5820.2166666666670.4706539615419711.29999999999995
6814.9583333333335.3754421946365215.6

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 829.591666666667 & 1.54358398383485 & 4.29999999999995 \tabularnewline
2 & 827.566666666667 & 2.9037071394194 & 7.70000000000005 \tabularnewline
3 & 819.233333333333 & 1.94671440373183 & 5.70000000000005 \tabularnewline
4 & 818.166666666667 & 1.11952370824977 & 3.59999999999991 \tabularnewline
5 & 820.216666666667 & 0.470653961541971 & 1.29999999999995 \tabularnewline
6 & 814.958333333333 & 5.37544219463652 & 15.6 \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]829.591666666667[/C][C]1.54358398383485[/C][C]4.29999999999995[/C][/ROW]
[ROW][C]2[/C][C]827.566666666667[/C][C]2.9037071394194[/C][C]7.70000000000005[/C][/ROW]
[ROW][C]3[/C][C]819.233333333333[/C][C]1.94671440373183[/C][C]5.70000000000005[/C][/ROW]
[ROW][C]4[/C][C]818.166666666667[/C][C]1.11952370824977[/C][C]3.59999999999991[/C][/ROW]
[ROW][C]5[/C][C]820.216666666667[/C][C]0.470653961541971[/C][C]1.29999999999995[/C][/ROW]
[ROW][C]6[/C][C]814.958333333333[/C][C]5.37544219463652[/C][C]15.6[/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
1829.5916666666671.543583983834854.29999999999995
2827.5666666666672.90370713941947.70000000000005
3819.2333333333331.946714403731835.70000000000005
4818.1666666666671.119523708249773.59999999999991
5820.2166666666670.4706539615419711.29999999999995
6814.9583333333335.3754421946365215.6






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha80.1091643056651
beta-0.0947912044821714
S.D.0.145347994444511
T-STAT-0.652167268247788
p-value0.549871440973728

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 80.1091643056651 \tabularnewline
beta & -0.0947912044821714 \tabularnewline
S.D. & 0.145347994444511 \tabularnewline
T-STAT & -0.652167268247788 \tabularnewline
p-value & 0.549871440973728 \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]80.1091643056651[/C][/ROW]
[ROW][C]beta[/C][C]-0.0947912044821714[/C][/ROW]
[ROW][C]S.D.[/C][C]0.145347994444511[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.652167268247788[/C][/ROW]
[ROW][C]p-value[/C][C]0.549871440973728[/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)
alpha80.1091643056651
beta-0.0947912044821714
S.D.0.145347994444511
T-STAT-0.652167268247788
p-value0.549871440973728






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha80.9159262667496
beta-11.9770892924079
S.D.59.6839692231853
T-STAT-0.200675146916254
p-value0.850743136013742
Lambda12.9770892924079

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 80.9159262667496 \tabularnewline
beta & -11.9770892924079 \tabularnewline
S.D. & 59.6839692231853 \tabularnewline
T-STAT & -0.200675146916254 \tabularnewline
p-value & 0.850743136013742 \tabularnewline
Lambda & 12.9770892924079 \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]80.9159262667496[/C][/ROW]
[ROW][C]beta[/C][C]-11.9770892924079[/C][/ROW]
[ROW][C]S.D.[/C][C]59.6839692231853[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.200675146916254[/C][/ROW]
[ROW][C]p-value[/C][C]0.850743136013742[/C][/ROW]
[ROW][C]Lambda[/C][C]12.9770892924079[/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)
alpha80.9159262667496
beta-11.9770892924079
S.D.59.6839692231853
T-STAT-0.200675146916254
p-value0.850743136013742
Lambda12.9770892924079


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 <- 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')