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 computationSat, 29 Nov 2008 08:57:02 -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/Nov/29/t1227974267bed21hsd45hpama.htm/, Retrieved Sun, 19 May 2024 09:02:29 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=26323, Retrieved Sun, 19 May 2024 09:02:29 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsQ2
Estimated Impact169

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]
F         [Law of Averages] [Q2] [2008-11-29 15:57:02] [783db4b4a0f63b73ca8b14666b7f4329] [Current]
Feedback Forum
2008-12-08 09:22:58 [Niels Herremans] [reply] 
Als we hier naar de ACF kijken is er een duidelijk dalende trend van de coefficienten. De coefficienten liggen ook ver buiten het betrouwbaarheidsinterval; zijn positief en zijn significant verschillend van 0.
2008-12-08 17:27:44 [Jeroen Michel] [reply] 
Je analyse klopt niet helemaal. De stelling die je maakt weinig te maken met het verloop van de grafiek.

Op de onderstaande grafiek is duidelijk af te lezen dat de sterke correlatie die aanwezig is sterk afneemt (dalend verloop).

Dit aangezien autocorrelatie te maken heeft met het feit dat er een verband bestaat tussen voorgaande data en de huidge data van de tijdreeksen die worden genomen.
2008-12-08 19:44:47 [Michaël De Kuyer] [reply] 
Het gaat om een randomwalk met de volgende formule: Yt = Yt-1 + et. De ACF geeft de samenhang weer van een punt ten opzichte van het vorige punt. De samenhang vermindert naarmate met verder gaat in de tijd. Daardoor vertoont de ACF een dalend verloop.

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 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=26323&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=26323&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=26323&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 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