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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 computationWed, 07 Dec 2011 12:42:13 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2011/Dec/07/t1323279772o2gpdpqcewbbomt.htm/, Retrieved Thu, 02 May 2024 23:08:45 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=152582, Retrieved Thu, 02 May 2024 23:08:45 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsKDGP2W83
Estimated Impact80

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Standard Deviation-Mean Plot] [T8P2] [2011-12-07 17:42:13] [53dd883843ca194f19e2952e03e3e0b7] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
0.71
0.71
0.71
0.71
0.71
0.71
0.71
0.71
0.71
0.71
0.7
0.7
0.68
0.68
0.69
0.69
0.7
0.7
0.7
0.7
0.7
0.71
0.71
0.71
0.71
0.71
0.71
0.71
0.71
0.71
0.76
0.77
0.78
0.85
0.89
0.9
0.91
0.91
0.91
0.9
0.89
0.88
0.87
0.86
0.87
0.87
0.87
0.85
0.84
0.84
0.84
0.84
0.84
0.82
0.87
0.92
0.92
0.92
0.93
0.94
0.87
0.84
0.83
0.81
0.81
0.81
0.8
0.8
0.8
0.8
0.8
0.8

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=152582&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=152582&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=152582&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
10.7083333333333330.003892494720807620.01
20.69750.01055289706022170.0299999999999999
30.76750.07350015460713490.19
40.88250.02094364733365140.0600000000000001
50.8766666666666670.04519318800908210.12
60.8141666666666670.02193309385519070.07

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 0.708333333333333 & 0.00389249472080762 & 0.01 \tabularnewline
2 & 0.6975 & 0.0105528970602217 & 0.0299999999999999 \tabularnewline
3 & 0.7675 & 0.0735001546071349 & 0.19 \tabularnewline
4 & 0.8825 & 0.0209436473336514 & 0.0600000000000001 \tabularnewline
5 & 0.876666666666667 & 0.0451931880090821 & 0.12 \tabularnewline
6 & 0.814166666666667 & 0.0219330938551907 & 0.07 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=152582&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]0.708333333333333[/C][C]0.00389249472080762[/C][C]0.01[/C][/ROW]
[ROW][C]2[/C][C]0.6975[/C][C]0.0105528970602217[/C][C]0.0299999999999999[/C][/ROW]
[ROW][C]3[/C][C]0.7675[/C][C]0.0735001546071349[/C][C]0.19[/C][/ROW]
[ROW][C]4[/C][C]0.8825[/C][C]0.0209436473336514[/C][C]0.0600000000000001[/C][/ROW]
[ROW][C]5[/C][C]0.876666666666667[/C][C]0.0451931880090821[/C][C]0.12[/C][/ROW]
[ROW][C]6[/C][C]0.814166666666667[/C][C]0.0219330938551907[/C][C]0.07[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=152582&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=152582&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
10.7083333333333330.003892494720807620.01
20.69750.01055289706022170.0299999999999999
30.76750.07350015460713490.19
40.88250.02094364733365140.0600000000000001
50.8766666666666670.04519318800908210.12
60.8141666666666670.02193309385519070.07






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-0.0498517108440952
beta0.100096715024718
S.D.0.152276490845647
T-STAT0.657335314655885
p-value0.546866423524332

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -0.0498517108440952 \tabularnewline
beta & 0.100096715024718 \tabularnewline
S.D. & 0.152276490845647 \tabularnewline
T-STAT & 0.657335314655885 \tabularnewline
p-value & 0.546866423524332 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=152582&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-0.0498517108440952[/C][/ROW]
[ROW][C]beta[/C][C]0.100096715024718[/C][/ROW]
[ROW][C]S.D.[/C][C]0.152276490845647[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.657335314655885[/C][/ROW]
[ROW][C]p-value[/C][C]0.546866423524332[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=152582&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=152582&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)
alpha-0.0498517108440952
beta0.100096715024718
S.D.0.152276490845647
T-STAT0.657335314655885
p-value0.546866423524332






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-2.48324315763233
beta6.00140031797497
S.D.4.13864893363343
T-STAT1.45008683128535
p-value0.220640233001852
Lambda-5.00140031797497

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -2.48324315763233 \tabularnewline
beta & 6.00140031797497 \tabularnewline
S.D. & 4.13864893363343 \tabularnewline
T-STAT & 1.45008683128535 \tabularnewline
p-value & 0.220640233001852 \tabularnewline
Lambda & -5.00140031797497 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=152582&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-2.48324315763233[/C][/ROW]
[ROW][C]beta[/C][C]6.00140031797497[/C][/ROW]
[ROW][C]S.D.[/C][C]4.13864893363343[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.45008683128535[/C][/ROW]
[ROW][C]p-value[/C][C]0.220640233001852[/C][/ROW]
[ROW][C]Lambda[/C][C]-5.00140031797497[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=152582&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=152582&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)
alpha-2.48324315763233
beta6.00140031797497
S.D.4.13864893363343
T-STAT1.45008683128535
p-value0.220640233001852
Lambda-5.00140031797497


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')