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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 13:44:12 -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/t12282507113d0s4xi9on7n6e8.htm/, Retrieved Sun, 19 May 2024 10:24:35 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=28422, Retrieved Sun, 19 May 2024 10:24:35 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsJonas Scheltjens
Estimated Impact138

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 18:05:16] [b98453cac15ba1066b407e146608df68]
-       [Law of Averages] [Non Stationary Ti...] [2008-12-02 20:36:38] [ff3cbec2dc497cddefec153d0a88b59b]
F           [Law of Averages] [Non Stationary Ti...] [2008-12-02 20:44:12] [f4960a11bac8b7f1cb71c83b5826d5bd] [Current]
Feedback Forum
2008-12-07 09:17:37 [Jolien Van Landeghem] [reply] 
Deze vraag werd goed opgelost.
Er is een dalend verloop in de autocorrelatie en deze wijst op een niet stationaire tijdreeks. Het is inderdaad een positieve tijdreeks : als de vorige waarde positief is, is de huidige waarde dit ook. Je ziet dat de streepjes bovenuit het betrouwbaarheidsinterval komen, wat erop wijst dat ze significant verschillend zijn en het model bijgevolg niet aan het toeval is te wijten. Er is, zoals de student zei, sprake van een stochastische trend. De trend is dus niet deterministisch : er is een voortdurende verandering in het opgooien van kop of munt.
2008-12-07 10:23:34 [Gert-Jan Geudens] [reply] 
Het antwoord van de student is zeer correct en volledig. We zien hier duidelijk een dalend verloop van de autocorrelatiecoëfficiënten. Tevens zijn deze coëfficiënten telkens significant verschillend van nul. Er kan dus geen sprake zijn van toeval.

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Dataset

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'Sir Ronald Aylmer Fisher' @ 193.190.124.24

\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 & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=28422&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]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=28422&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=28422&T=0

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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'Sir Ronald Aylmer Fisher' @ 193.190.124.24


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
bitmap(file='pic1.png')
racf <- acf(b,n/10,main='Autocorrelation',xlab='lags',ylab='ACF')
dev.off()
racf