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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationTue, 02 Dec 2008 14:11:58 -0700
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/Dec/02/t122825262504oqqff09opulwf.htm/, Retrieved Fri, 17 May 2024 01:42:39 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=28464, Retrieved Fri, 17 May 2024 01:42:39 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact160

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Spectral Analysis] [Q6 - 3e methode -...] [2008-12-02 20:05:14] [7a664918911e34206ce9d0436dd7c1c8]
- RMPD  [Variance Reduction Matrix] [Q8 - eerste reeks...] [2008-12-02 21:03:48] [7a664918911e34206ce9d0436dd7c1c8]
- RM        [Standard Deviation-Mean Plot] [Q8 - eerste reeks...] [2008-12-02 21:11:58] [98255691c21504803b38711776845ae0] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
-1
4
9
18
13
9
5
9
9
17
7
4
8
1
4
2
1
5
15
11
4
11
2
3
7
6
4
5
3
2
1
1
0
9
3
4
-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' @ 72.249.127.135

\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' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=28464&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' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=28464&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=28464&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' @ 72.249.127.135






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
18.583333333333335.4682277889198419
25.583333333333334.6015478291812214
33.752.667140109487389

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 8.58333333333333 & 5.46822778891984 & 19 \tabularnewline
2 & 5.58333333333333 & 4.60154782918122 & 14 \tabularnewline
3 & 3.75 & 2.66714010948738 & 9 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=28464&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]8.58333333333333[/C][C]5.46822778891984[/C][C]19[/C][/ROW]
[ROW][C]2[/C][C]5.58333333333333[/C][C]4.60154782918122[/C][C]14[/C][/ROW]
[ROW][C]3[/C][C]3.75[/C][C]2.66714010948738[/C][C]9[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=28464&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=28464&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
18.583333333333335.4682277889198419
25.583333333333334.6015478291812214
33.752.667140109487389






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha0.954593036396024
beta0.551058788003742
S.D.0.204337759825558
T-STAT2.69680351039464
p-value0.226058357511644

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 0.954593036396024 \tabularnewline
beta & 0.551058788003742 \tabularnewline
S.D. & 0.204337759825558 \tabularnewline
T-STAT & 2.69680351039464 \tabularnewline
p-value & 0.226058357511644 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=28464&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]0.954593036396024[/C][/ROW]
[ROW][C]beta[/C][C]0.551058788003742[/C][/ROW]
[ROW][C]S.D.[/C][C]0.204337759825558[/C][/ROW]
[ROW][C]T-STAT[/C][C]2.69680351039464[/C][/ROW]
[ROW][C]p-value[/C][C]0.226058357511644[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=28464&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=28464&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)
alpha0.954593036396024
beta0.551058788003742
S.D.0.204337759825558
T-STAT2.69680351039464
p-value0.226058357511644






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-0.087435989778488
beta0.860787632742824
S.D.0.279152014314969
T-STAT3.08358023084724
p-value0.19964214969321
Lambda0.139212367257176

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -0.087435989778488 \tabularnewline
beta & 0.860787632742824 \tabularnewline
S.D. & 0.279152014314969 \tabularnewline
T-STAT & 3.08358023084724 \tabularnewline
p-value & 0.19964214969321 \tabularnewline
Lambda & 0.139212367257176 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=28464&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-0.087435989778488[/C][/ROW]
[ROW][C]beta[/C][C]0.860787632742824[/C][/ROW]
[ROW][C]S.D.[/C][C]0.279152014314969[/C][/ROW]
[ROW][C]T-STAT[/C][C]3.08358023084724[/C][/ROW]
[ROW][C]p-value[/C][C]0.19964214969321[/C][/ROW]
[ROW][C]Lambda[/C][C]0.139212367257176[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=28464&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=28464&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-0.087435989778488
beta0.860787632742824
S.D.0.279152014314969
T-STAT3.08358023084724
p-value0.19964214969321
Lambda0.139212367257176


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')