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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 computationSun, 30 Nov 2008 12:28:46 -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/30/t1228073397fmgdfs01czsee5d.htm/, Retrieved Sat, 18 May 2024 23:44:56 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=26705, Retrieved Sat, 18 May 2024 23:44:56 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact133

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]
F       [Law of Averages] [Q1 - 1] [2008-11-30 19:20:39] [adb6b6905cde49db36d59ca44433140d]
F         [Law of Averages] [Q1 - 2] [2008-11-30 19:23:20] [adb6b6905cde49db36d59ca44433140d]
F             [Law of Averages] [Q1 - 3] [2008-11-30 19:28:46] [6d5cd2fe15d123a10639b4bf141c23b5] [Current]
Feedback Forum
2008-12-08 18:47:02 [Jeroen Michel] [reply] 
Bij het interpreteren van deze tijdreeksen is het inderdaad belangrijk om te weten dat er bij één worp telkens 50% kans bestaat om kop OF munt te werpen.

De functie die men hier gebruikt (random-walk), zal een voorgaande berekening nemen om daarbij een cijfer op te tellen. Basisvergelijking hiervoor is y(t)=y(t-1) + e(t).

Hoe meer worpen/pogingen men doet, hoe groter de kans wordt dat er een gelijk aantal keer kop of munt wordt gesmeten. Bij de eerste berekeningen is duidelijk af te lezen dat die kans inderdaad groter wordt naarmate men meer worpen doet. Binnen deze berekeningen en toepassingen is er echter geen sprake van seizoenaliteit en is het patroon (trend) dat waar te nemen is toe te wijten aan toeval.

Bij de eerste en laatste berekening is echter te zien dat er een positieve trend is waar te nemen daar berekening 2 een negatieve trend aantoont.

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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 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=26705&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=26705&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=26705&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()