This page lists articles related to probability theory. In particular, it lists many articles corresponding to specific probability distributions. Such articles are marked here by a code of the form (X:Y), which refers to number of random variables involved and the type of the distribution. For example (2:DC) indicates a distribution with two random variables, discrete or continuous. Other codes are just abbreviations for topics. The list of codes can be found in the table of contents.
Core probability: selected topics Probability theory
Basic notions (bsc)
Instructive examples (paradoxes) (iex)
Moments (mnt)
Inequalities (inq)
Markov chains, processes, fields, networks (Mar)
Gaussian random variables, vectors, functions (Gau)
Conditioning (cnd)
Specific distributions (spd)
Empirical measure (emm)
Limit theorems (lmt)
Large deviations (lrd)
Random graphs (rgr)
Random matrices (rmt)
Stochastic calculus (scl)
Malliavin calculus (Mal)
Random dynamical systems (rds) Random dynamical system / scl
Absorbing set Base flow Pullback attractor
Analytic aspects (including measure theoretic) (anl)
Core probability: other articles, by number and type of random variables
A single random variable (1:)
Binary (1:B)
Discrete (1:D)
Continuous (1:C)
Real-valued, arbitrary (1:R)
Random point of a manifold (1:M) Bertrand's paradox / (1:M)
General (random element of an abstract space) (1:G) Pitman–Yor process / (1:G) Random compact set / (1:G) Random element / (1:G)
Two random variables (2:)
Binary (2:B) Coupling / (2:BRG) Craps principle / (2:B)
Discrete (2:D) Kullback–Leibler divergence / (2:DCR) Mutual information / (23F:DC)
Continuous (2:C)
Real-valued, arbitrary (2:R)
General (random element of an abstract space) (2:G) Coupling / (2:BRG) Lévy–Prokhorov metric / (2:G) Wasserstein metric / (2:G)
Three random variables (3:)
Binary (3:B) Pairwise independence / (3:B) (F:R)
Discrete (3:D) Mutual information / (23F:DC)
Continuous (3:C) Mutual information / (23F:DC)
Finitely many random variables (F:)
Binary (F:B)
Discrete (F:D)
Continuous (F:C)
Real-valued, arbitrary (F:R)
General (random element of an abstract space) (F:G) Finite-dimensional distribution / (FU:G) Hitting time / (FU:G) Stopped process / (FU:DG)
A large number of random variables (finite but tending to infinity) (L:)
Binary (L:B) Random walk / (FLS:BD) (U:C)
Discrete (L:D)
Real-valued, arbitrary (L:R)
An infinite sequence of random variables (S:)
Binary (S:B)
Discrete (S:D)
Continuous (S:C)
Real-valued, arbitrary (S:R)
General (random element of an abstract space) (S:G)
Uncountably many random variables (continuous-time processes etc) (U:)
Discrete (U:D)
Continuous (U:C)
Real-valued, arbitrary (U:R)
General (random element of an abstract space) (U:G)
Around the core
General aspects (grl)
Foundations of probability theory (fnd)
Gambling (gmb)
Coincidence (cnc)
Algorithmics (alg)
Bayesian approach (Bay)
Financial mathematics (fnc)
Physics (phs)
Genetics (gnt)
Stochastic process (spr)
Geometric probability (geo)
Empirical findings (emp) Benford's law Pareto principle
Historical (hst)
Miscellany (msc)
Counters of articles
Here k(n) means: n links to k articles. (Some articles are linked more than once.)