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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_rwalk.wasp
Title produced by softwareLaw of Averages
Date of computationTue, 02 Dec 2008 05:30:48 -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/t1228221083hc89co978ap8uh1.htm/, Retrieved Sun, 19 May 2024 11:13:28 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=27678, Retrieved Sun, 19 May 2024 11:13:28 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact179

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F     [Law of Averages] [Random Walk Simul...] [2008-11-25 18:31:28] [b98453cac15ba1066b407e146608df68]
F         [Law of Averages] [Q3] [2008-12-02 12:30:48] [d41d8cd98f00b204e9800998ecf8427e] [Current]
Feedback Forum
2008-12-04 13:11:14 [72e979bcc364082694890d2eccc1a66f] [reply] 
Ook hier heeft de student de vraag goed beantwoord.
We moeten inderdaad op zoek gaan naar de kleinste variantie.
2008-12-07 20:14:16 [Stefan Temmerman] [reply] 
De student vindt hier de juiste waarden voor d en D om de juiste differentiatie toe te passen.

Post a new message

Dataset

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=27678&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=27678&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=27678&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






Variance Reduction Matrix
V(Y[t],d=0,D=0)38.6236472945892Range28Trim Var.25.9253105963240
V(Y[t],d=1,D=0)1.00197181511618Range2Trim Var.NA
V(Y[t],d=2,D=0)1.9476861167002Range4Trim Var.0
V(Y[t],d=3,D=0)5.76611280586746Range8Trim Var.2.63588893493576
V(Y[t],d=0,D=1)12.0493486383681Range22Trim Var.6.32529033584177
V(Y[t],d=1,D=1)1.98311658681269Range4Trim Var.0
V(Y[t],d=2,D=1)3.91750880319036Range8Trim Var.2.17123196448391
V(Y[t],d=3,D=1)11.8181818181818Range16Trim Var.6.7019440983568
V(Y[t],d=0,D=2)25.4854135338346Range28Trim Var.12.2878803695391
V(Y[t],d=1,D=2)6.06735065511881Range8Trim Var.2.57753820253820
V(Y[t],d=2,D=2)12.0422119338811Range16Trim Var.6.25249980917487
V(Y[t],d=3,D=2)36.4742896047587Range30Trim Var.21.0125313283208

\begin{tabular}{lllllllll}
\hline
Variance Reduction Matrix \tabularnewline
V(Y[t],d=0,D=0) & 38.6236472945892 & Range & 28 & Trim Var. & 25.9253105963240 \tabularnewline
V(Y[t],d=1,D=0) & 1.00197181511618 & Range & 2 & Trim Var. & NA \tabularnewline
V(Y[t],d=2,D=0) & 1.9476861167002 & Range & 4 & Trim Var. & 0 \tabularnewline
V(Y[t],d=3,D=0) & 5.76611280586746 & Range & 8 & Trim Var. & 2.63588893493576 \tabularnewline
V(Y[t],d=0,D=1) & 12.0493486383681 & Range & 22 & Trim Var. & 6.32529033584177 \tabularnewline
V(Y[t],d=1,D=1) & 1.98311658681269 & Range & 4 & Trim Var. & 0 \tabularnewline
V(Y[t],d=2,D=1) & 3.91750880319036 & Range & 8 & Trim Var. & 2.17123196448391 \tabularnewline
V(Y[t],d=3,D=1) & 11.8181818181818 & Range & 16 & Trim Var. & 6.7019440983568 \tabularnewline
V(Y[t],d=0,D=2) & 25.4854135338346 & Range & 28 & Trim Var. & 12.2878803695391 \tabularnewline
V(Y[t],d=1,D=2) & 6.06735065511881 & Range & 8 & Trim Var. & 2.57753820253820 \tabularnewline
V(Y[t],d=2,D=2) & 12.0422119338811 & Range & 16 & Trim Var. & 6.25249980917487 \tabularnewline
V(Y[t],d=3,D=2) & 36.4742896047587 & Range & 30 & Trim Var. & 21.0125313283208 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=27678&T=1

[TABLE]
[ROW][C]Variance Reduction Matrix[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=0)[/C][C]38.6236472945892[/C][C]Range[/C][C]28[/C][C]Trim Var.[/C][C]25.9253105963240[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=0)[/C][C]1.00197181511618[/C][C]Range[/C][C]2[/C][C]Trim Var.[/C][C]NA[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=0)[/C][C]1.9476861167002[/C][C]Range[/C][C]4[/C][C]Trim Var.[/C][C]0[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=0)[/C][C]5.76611280586746[/C][C]Range[/C][C]8[/C][C]Trim Var.[/C][C]2.63588893493576[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=1)[/C][C]12.0493486383681[/C][C]Range[/C][C]22[/C][C]Trim Var.[/C][C]6.32529033584177[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=1)[/C][C]1.98311658681269[/C][C]Range[/C][C]4[/C][C]Trim Var.[/C][C]0[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=1)[/C][C]3.91750880319036[/C][C]Range[/C][C]8[/C][C]Trim Var.[/C][C]2.17123196448391[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=1)[/C][C]11.8181818181818[/C][C]Range[/C][C]16[/C][C]Trim Var.[/C][C]6.7019440983568[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=2)[/C][C]25.4854135338346[/C][C]Range[/C][C]28[/C][C]Trim Var.[/C][C]12.2878803695391[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=2)[/C][C]6.06735065511881[/C][C]Range[/C][C]8[/C][C]Trim Var.[/C][C]2.57753820253820[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=2)[/C][C]12.0422119338811[/C][C]Range[/C][C]16[/C][C]Trim Var.[/C][C]6.25249980917487[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=2)[/C][C]36.4742896047587[/C][C]Range[/C][C]30[/C][C]Trim Var.[/C][C]21.0125313283208[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=27678&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=27678&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:

Variance Reduction Matrix
V(Y[t],d=0,D=0)38.6236472945892Range28Trim Var.25.9253105963240
V(Y[t],d=1,D=0)1.00197181511618Range2Trim Var.NA
V(Y[t],d=2,D=0)1.9476861167002Range4Trim Var.0
V(Y[t],d=3,D=0)5.76611280586746Range8Trim Var.2.63588893493576
V(Y[t],d=0,D=1)12.0493486383681Range22Trim Var.6.32529033584177
V(Y[t],d=1,D=1)1.98311658681269Range4Trim Var.0
V(Y[t],d=2,D=1)3.91750880319036Range8Trim Var.2.17123196448391
V(Y[t],d=3,D=1)11.8181818181818Range16Trim Var.6.7019440983568
V(Y[t],d=0,D=2)25.4854135338346Range28Trim Var.12.2878803695391
V(Y[t],d=1,D=2)6.06735065511881Range8Trim Var.2.57753820253820
V(Y[t],d=2,D=2)12.0422119338811Range16Trim Var.6.25249980917487
V(Y[t],d=3,D=2)36.4742896047587Range30Trim Var.21.0125313283208


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 500 ; par2 = 0.5 ;
Parameters (R input):
par1 = 500 ; par2 = 0.5 ;
R code (references can be found in the software module):
n <- as.numeric(par1)
p <- as.numeric(par2)
heads=rbinom(n-1,1,p)
a=2*(heads)-1
b=diffinv(a,xi=0)
c=1:n
pheads=(diffinv(heads,xi=.5))/c
bitmap(file='test1.png')
op=par(mfrow=c(2,1))
plot(c,b,type='n',main='Law of Averages',xlab='Toss Number',ylab='Excess of Heads',lwd=2,cex.lab=1.5,cex.main=2)
lines(c,b,col='red')
lines(c,rep(0,n),col='black')
plot(c,pheads,type='n',xlab='Toss Number',ylab='Proportion of Heads',lwd=2,cex.lab=1.5)
lines(c,pheads,col='blue')
lines(c,rep(.5,n),col='black')
par(op)
dev.off()
b
par1 <- as.numeric(12)
x <- as.array(b)
n <- length(x)
sx <- sort(x)
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Variance Reduction Matrix',6,TRUE)
a<-table.row.end(a)
for (bigd in 0:2) {
for (smalld in 0:3) {
mylabel <- 'V(Y[t],d='
mylabel <- paste(mylabel,as.character(smalld),sep='')
mylabel <- paste(mylabel,',D=',sep='')
mylabel <- paste(mylabel,as.character(bigd),sep='')
mylabel <- paste(mylabel,')',sep='')
a<-table.row.start(a)
a<-table.element(a,mylabel,header=TRUE)
myx <- x
if (smalld > 0) myx <- diff(x,lag=1,differences=smalld)
if (bigd > 0) myx <- diff(myx,lag=par1,differences=bigd)
a<-table.element(a,var(myx))
a<-table.element(a,'Range',header=TRUE)
a<-table.element(a,max(myx)-min(myx))
a<-table.element(a,'Trim Var.',header=TRUE)
smyx <- sort(myx)
sn <- length(smyx)
a<-table.element(a,var(smyx[smyx>quantile(smyx,0.05) & smyxa<-table.row.end(a)
}
}
a<-table.end(a)
table.save(a,file='mytable.tab')