FreeStatistics.org

Free Statistics

of Irreproducible Research!

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 computationMon, 01 Dec 2008 13:28:11 -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/01/t1228163313h60yhvxwkro8mau.htm/, Retrieved Sun, 05 May 2024 13:44:08 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=27339, Retrieved Sun, 05 May 2024 13:44:08 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact197

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 17:50:19] [b98453cac15ba1066b407e146608df68]
-       [Law of Averages] [Q1 Non Stationary...] [2008-11-29 13:26:33] [7173087adebe3e3a714c80ea2417b3eb]
F           [Law of Averages] [Q1 Non Stationary...] [2008-12-01 20:28:11] [35348cd8592af0baf5f138bd59921307] [Current]
Feedback Forum
2008-12-03 15:30:25 [Ken Van den Heuvel] [reply] 
De tijdsreeksen baseren zich op het gooien van munten. Er zijn dus 2 mogelijkheden, kop of munt met ieder 50% kans op gegooid te worden.

De random-walk gebruikt telkens de vorige berekening en telt daarbij een getal op dat gemiddeld nul is (gezien de kans op kop en munt hetzelfde is) => y(t) = y(t-1) + e(t).
Moesten we oneindig veel simulaties kunnen doen, dan zou het aantal kop en munt effectief gelijk moeten zijn. Bij een beperkt aantal simulaties zien we echter dat dit niet zo is.

Bijgevolg geven de plots van worpen een soort van lange termijn trend aan. Deze trend ontstaat door het hierboven vermelde fenomeen en is dus louter aan het toeval toe te wijzen (de verschillende resultaten van de reproducties staven dit).

Omwille van het willekeurig karakter van e(t) ontstaat er dan ook geen seizoenaliteit.

We concluderen dus dat deze tijdreeksen wel een trend vertonen maar geen seizoenaliteit.

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=27339&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=27339&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=27339&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


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()