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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, 28 Nov 2012 09:01:51 -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/2012/Nov/28/t13541113636a43t4ekyinro0t.htm/, Retrieved Sat, 20 Apr 2024 14:01:17 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=194150, Retrieved Sat, 20 Apr 2024 14:01:17 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact91

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] [] [2012-11-28 14:01:51] [be23bcf5581d42dc10000203a523c779] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
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
0.79
0.8
0.8
0.8
0.81
0.83
0.83
0.83
0.83
0.82
0.82
0.82

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 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 & 2 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=194150&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]2 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=194150&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=194150&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 time2 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
10.69750.01055289706022170.0299999999999999
20.76750.07350015460713490.19
30.88250.02094364733365140.0600000000000001
40.8766666666666670.04519318800908210.12
50.8141666666666670.02193309385519070.07
60.8150.01445997610962440.0399999999999999

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 0.6975 & 0.0105528970602217 & 0.0299999999999999 \tabularnewline
2 & 0.7675 & 0.0735001546071349 & 0.19 \tabularnewline
3 & 0.8825 & 0.0209436473336514 & 0.0600000000000001 \tabularnewline
4 & 0.876666666666667 & 0.0451931880090821 & 0.12 \tabularnewline
5 & 0.814166666666667 & 0.0219330938551907 & 0.07 \tabularnewline
6 & 0.815 & 0.0144599761096244 & 0.0399999999999999 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=194150&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]0.6975[/C][C]0.0105528970602217[/C][C]0.0299999999999999[/C][/ROW]
[ROW][C]2[/C][C]0.7675[/C][C]0.0735001546071349[/C][C]0.19[/C][/ROW]
[ROW][C]3[/C][C]0.8825[/C][C]0.0209436473336514[/C][C]0.0600000000000001[/C][/ROW]
[ROW][C]4[/C][C]0.876666666666667[/C][C]0.0451931880090821[/C][C]0.12[/C][/ROW]
[ROW][C]5[/C][C]0.814166666666667[/C][C]0.0219330938551907[/C][C]0.07[/C][/ROW]
[ROW][C]6[/C][C]0.815[/C][C]0.0144599761096244[/C][C]0.0399999999999999[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=194150&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=194150&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
10.69750.01055289706022170.0299999999999999
20.76750.07350015460713490.19
30.88250.02094364733365140.0600000000000001
40.8766666666666670.04519318800908210.12
50.8141666666666670.02193309385519070.07
60.8150.01445997610962440.0399999999999999






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha0.0113300688084306
beta0.0244373373882531
S.D.0.172140668925194
T-STAT0.141961440842737
p-value0.893973591620247

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 0.0113300688084306 \tabularnewline
beta & 0.0244373373882531 \tabularnewline
S.D. & 0.172140668925194 \tabularnewline
T-STAT & 0.141961440842737 \tabularnewline
p-value & 0.893973591620247 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=194150&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]0.0113300688084306[/C][/ROW]
[ROW][C]beta[/C][C]0.0244373373882531[/C][/ROW]
[ROW][C]S.D.[/C][C]0.172140668925194[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.141961440842737[/C][/ROW]
[ROW][C]p-value[/C][C]0.893973591620247[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=194150&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=194150&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)
alpha0.0113300688084306
beta0.0244373373882531
S.D.0.172140668925194
T-STAT0.141961440842737
p-value0.893973591620247






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-3.15182850616217
beta2.53141725145371
S.D.3.89622063346735
T-STAT0.649710960850012
p-value0.551303709393968
Lambda-1.53141725145371

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -3.15182850616217 \tabularnewline
beta & 2.53141725145371 \tabularnewline
S.D. & 3.89622063346735 \tabularnewline
T-STAT & 0.649710960850012 \tabularnewline
p-value & 0.551303709393968 \tabularnewline
Lambda & -1.53141725145371 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=194150&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-3.15182850616217[/C][/ROW]
[ROW][C]beta[/C][C]2.53141725145371[/C][/ROW]
[ROW][C]S.D.[/C][C]3.89622063346735[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.649710960850012[/C][/ROW]
[ROW][C]p-value[/C][C]0.551303709393968[/C][/ROW]
[ROW][C]Lambda[/C][C]-1.53141725145371[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=194150&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=194150&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-3.15182850616217
beta2.53141725145371
S.D.3.89622063346735
T-STAT0.649710960850012
p-value0.551303709393968
Lambda-1.53141725145371


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')