
related topics 
{math, number, function} 
{theory, work, human} 
{rate, high, increase} 
{law, state, case} 
{game, team, player} 
{@card@, make, design} 
{day, year, event} 

Statistical regularity is a notion in statistics and probability theory that random events exhibit regularity when repeated enough times or that enough sufficiently similar random events exhibit regularity. It is an umbrella term that covers the law of large numbers, all central limit theorems and ergodic theorems.
If one throws a die once, it is difficult to predict the outcome, but if we repeat this experiment many times, we will see that the number of times each result occurs divided by the number of throws will eventually stabilize towards a specific value.
Repeating a series of trials will produce similar, but not identical, results for each series: the average, the standard deviation and other distributional characteristics will be around the same for each series of trials.
The notion is used in games of chance, demographic statistics, quality control of a manufacturing process, and in many other parts of our lives.
Observations of this phenomenon provided the initial motivation for the concept of what is now known as frequency probability.
This phenomenon should not be confused with the Gambler's fallacy, it only concerns regularity in the (possibly very) long run. Gambler's fallacy does not apply to statistical regularity because the latter considers the whole rather than individual cases.
See also
References
 LeonGarcia, Albert (1994) Probability and Random Processes for Electrical Engineering (2nd edition), Prentice Hall
 Whitt, Ward (2002) StochasticProcess Limits, An Introduction to StochasticProcess Limits and their Application to Queues, Chapter 1: Experiencing Statistical Regularity, link to selected chapters
Full article ▸


related documents 
Classical logic 
Inductive logic programming 
Logic puzzle 
Turing tarpit 
Ninetyninety rule 
SuperPoulet number 
Semivariance 
Unix billennium 
DARPA Agent Markup Language 
Unavailability 
Wikipedia:Free Online Dictionary of Computing/X  Z 
Gauss–Markov process 
Structure and Interpretation of Computer Programs 
Quickanddirty 
August Ferdinand Möbius 
Mathematical constants (sorted by continued fraction representation) 
Wilhelm Ackermann 
SISAL 
Hack value 
Metaphone 
Vladimir Voevodsky 
Karl Menger 
Facade pattern 
Objectoriented programming language 
Voodoo programming 
National Center for Biotechnology Information 
Full width at half maximum 
Hill system 
Multistage sampling 
Parkinson's law 
