Wikipedia:WikiProject Probability/Learn
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A Guide to Learning Probability from the Wikipedia
The Wikipedia is not a textbook; it is a reference, but does not have an overtly pedagogical intent (despite the etymological links between encyclopedia and pedagogy!). But, in order to be truly useful, the Wikipedia does need to be accessible to those without much knowledge in the field they are reading about, while retaining the detail to be useful, and trustworthy, to those who already have such knowledge. Wiki's satisfy this apparent double-bind admirably, but again, this is an encyclopedia, not a textbook.
I hope anyone and everyone interested in probability will join me in organising this guide to learning probability from the Wikipedia. It is NOT intended to be a list in the style of the list of mathematics topics, but an annotated table of contents, ordered in some more-or-less linear fashion, which could (at least hypothetically) serve as an entry point for the interested student to learn probability theory from the Wikipedia. I hope, too, that it will identify holes in the subject matter covered by the Wikipedia, and help us improve it. Finally, I hope that one day it might form the basis for a Wikibook.
Please feel free to add your contributions to the list below, and your comments to the talk page.
Currently this guide has over 120 links to articles on probability theory, stochastic processes and related topics.
* Just because a page linked from here doesn't exist yet, doesn't mean that it should exist! Some of these topics should probably (!) be incorporated into an existing page, and some should be combined with others to form new pages. Perhaps some deserve their own, new page.
Contents |
[edit] Introduction
- Probability and randomness.
[edit] Basic probability
(Related topics: set theory, simple theorems in the algebra of sets)
[edit] Events
[edit] Elementary probability
[edit] Conditional probability
[edit] Independence
[edit] Probability theory
(Related topics: measure theory)
[edit] Measure-theoretic probability
[edit] Independence
[edit] Random variables
[edit] Discrete and continuous random variables
- Discrete random variables: Probability mass functions
- Continuous random variables: Probability density functions
- Normalizing constants
- Cumulative distribution functions
- Joint*, marginal and conditional distributions
[edit] Expectation
- Expectation (or mean), variance and covariance
- General moments about the mean
- Correlated and uncorrelated random variables
- Conditional expectation:
- Fatou's lemma and the monotone and dominated convergence theorems
- Markov's inequality and Chebyshev's inequality
[edit] Independence
[edit] Some common distributions
- Discrete:
- constant (see also degenerate distribution),
- Bernoulli and binomial,
- negative binomial,
- (discrete) uniform,
- geometric,
- Poisson, and
- hypergeometric.
- Continuous:
- (continuous) uniform,
- exponential,
- gamma,
- beta,
- normal (or Gaussian) and multivariate normal,
- χ-squared (or chi-squared),
- F-distribution,
- Student's t-distribution, and
- Cauchy.
[edit] Some other distributions
- Cantor
- Fisher-Tippett (or Gumbel)
- Pareto
- Benford's law
[edit] Functions of random variables
- Sums of random variables*
- General functions of random variables*
- Borel's paradox
[edit] Generating functions
(Related topics: integral transforms)
[edit] Common generating functions
- Probability-generating functions
- Moment-generating functions
- Laplace transforms and Laplace-Stieltjes transforms
- Characteristic functions
[edit] Applications
- A proof of the central limit theorem*
- Random sums of random variables*
[edit] Convergence of random variables
(Related topics: convergence)
[edit] Modes of convergence
- Convergence in distribution and convergence in probability,
- Convergence in mean, mean square and rth mean
- Almost sure convergence
- Skorokhod's representation theorem*
[edit] Applications
[edit] Stochastic processes
[edit] Some common stochastic processes
- Random walk
- Poisson process
- Compound Poisson process
- Wiener process
- Geometric Brownian motion
- Fractional Brownian motion
- Brownian bridge
- Ornstein-Uhlenbeck process
- Gamma process
[edit] Markov processes
- Markov property
- Branching process
- Markov chain
- Population processes
- Applications to queueing theory
[edit] Stochastic differential equations
[edit] Time series
- Moving-average* and autoregressive* processes
- Correlation function and autocorrelation