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Description of Statistical Computation

Author's title

Standard Deviation Mean Plot (Economische Activiteit: Registratie van nieuw...

Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationThu, 29 Nov 2007 02:03:03 -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/2007/Nov/29/t1196326391zbrqx49uivoq9qn.htm/, Retrieved Fri, 03 May 2024 07:35:32 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=7290, Retrieved Fri, 03 May 2024 07:35:32 +0000
QR Codes:

Original text written by user:Inducing Stationary in time series Vraag 1
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact241

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] [Standard Deviatio...] [2007-11-29 09:03:03] [0eafefa7b02d47065fceb6c46f54fbf9] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
-11,8
-11,4
-17,7
-17,3
-18,6
-17,9
-21,4
-19,4
-15,5
-7,7
-0,7
-1,6
1,4
0,7
9,5
1,4
4,1
6,6
18,4
16,9
9,2
-4,3
-5,9
-7,7
-5,4
-2,3
-4,8
2,3
-5,2
-10
-17,1
-14,4
-3,9
3,7
6,5
0,9
-4,1
-7
-12,2
-2,5
4,4
13,7
12,3
13,4
2,2
1,7
-7,2
-4,8
-2,9
-2,4
-2,5
-5,3
-7,1
-8

Tables (Output of Computation)





Summary of compuational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135

\begin{tabular}{lllllllll}
\hline
Summary of compuational 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' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=7290&T=0

[TABLE]
[ROW][C]Summary of compuational 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' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=7290&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=7290&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 compuational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
1-13.41666666666676.9083392733095811.1
24.191666666666678.3426024207986329.8
3-4.141666666666677.1076729772489624.2
40.8258.7034084232453531

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & -13.4166666666667 & 6.90833927330958 & 11.1 \tabularnewline
2 & 4.19166666666667 & 8.34260242079863 & 29.8 \tabularnewline
3 & -4.14166666666667 & 7.10767297724896 & 24.2 \tabularnewline
4 & 0.825 & 8.70340842324535 & 31 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=7290&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]-13.4166666666667[/C][C]6.90833927330958[/C][C]11.1[/C][/ROW]
[ROW][C]2[/C][C]4.19166666666667[/C][C]8.34260242079863[/C][C]29.8[/C][/ROW]
[ROW][C]3[/C][C]-4.14166666666667[/C][C]7.10767297724896[/C][C]24.2[/C][/ROW]
[ROW][C]4[/C][C]0.825[/C][C]8.70340842324535[/C][C]31[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=7290&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=7290&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
1-13.41666666666676.9083392733095811.1
24.191666666666678.3426024207986329.8
3-4.141666666666677.1076729772489624.2
40.8258.7034084232453531






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha8.07564362385222
beta0.0989143974064868
S.D.0.0432027719910841
T-STAT2.28953821358731
p-value0.149216459923476

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 8.07564362385222 \tabularnewline
beta & 0.0989143974064868 \tabularnewline
S.D. & 0.0432027719910841 \tabularnewline
T-STAT & 2.28953821358731 \tabularnewline
p-value & 0.149216459923476 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=7290&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]8.07564362385222[/C][/ROW]
[ROW][C]beta[/C][C]0.0989143974064868[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0432027719910841[/C][/ROW]
[ROW][C]T-STAT[/C][C]2.28953821358731[/C][/ROW]
[ROW][C]p-value[/C][C]0.149216459923476[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=7290&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=7290&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)
alpha8.07564362385222
beta0.0989143974064868
S.D.0.0432027719910841
T-STAT2.28953821358731
p-value0.149216459923476






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha2.15870390597386
beta-0.0260475461441665
S.D.NaN
T-STATNaN
p-valueNaN
Lambda1.02604754614417

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 2.15870390597386 \tabularnewline
beta & -0.0260475461441665 \tabularnewline
S.D. & NaN \tabularnewline
T-STAT & NaN \tabularnewline
p-value & NaN \tabularnewline
Lambda & 1.02604754614417 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=7290&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]2.15870390597386[/C][/ROW]
[ROW][C]beta[/C][C]-0.0260475461441665[/C][/ROW]
[ROW][C]S.D.[/C][C]NaN[/C][/ROW]
[ROW][C]T-STAT[/C][C]NaN[/C][/ROW]
[ROW][C]p-value[/C][C]NaN[/C][/ROW]
[ROW][C]Lambda[/C][C]1.02604754614417[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=7290&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=7290&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)
alpha2.15870390597386
beta-0.0260475461441665
S.D.NaN
T-STATNaN
p-valueNaN
Lambda1.02604754614417


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')