Linked from

The 85 pages that link to Random variable, each with the reason it gives.

• Strong law of large numbersNarrower topic: The theorem applies to sequences of random variables and their averages.

• Bernoulli distributionNarrower topic: The Bernoulli distribution describes the values of a random variable with two possible outcomes.

• Frequentist statisticsRelated: Sample statistics are treated as random variables before the data are observed.

• Bernoulli trialNarrower topic: Coding success as one and failure as zero turns a trial into a random variable.

• Mathematical modelRelated: Probabilistic models use random variables to represent uncertain quantities.

• Pseudorandom number generatorNarrower topic: Generators commonly encode samples intended to behave like draws from specified random variables.

• Correlation functionNarrower topic: Field values are treated as random variables when their statistical dependence is measured.

• Filtration (probability theory)Related: Events about a random variable belong to a stage when its value is known there.

• Independent random variablesNarrower topic: Independence describes relationships among the distributions of random variables.

• Econometric modelRelated: Random variables represent uncertainty in economic outcomes and model disturbances.

• Hypergeometric distributionNarrower topic: The number of sampled successes is the random quantity whose distribution is modeled.

• Concentration inequalityNarrower topic: The quantity whose unusually large deviations an inequality bounds.

• Linearity of expectationNarrower topic: The rule combines expectations of random variables, which need not be independent.

• Parameter (statistics)Related: Parameters often describe the distribution governing a random variable.

• Mathematical statisticsBroader topic: It represents sample measurements as quantities governed by probability distributions.

• Population parameterCompared with: A parameter is fixed in the model, whereas sample-derived statistics can be random.

• Constant (mathematics)Compared with: Its value varies across outcomes, unlike a constant on the same probability space.

• Continuous mapping theoremNarrower topic: The theorem transforms random variables and studies the limits of their distributions.

• Random vectorNarrower topic: A random vector generalizes a scalar random variable to multiple coordinates.

• Slutsky's theoremNarrower topic: The theorem concerns sequences of these objects and their limiting distributions.

• Kolmogorov extension theoremRelated: Coordinate projections under the resulting measure become the process's random variables.

• Law of total expectationNarrower topic: The identity concerns the average of a random variable over its possible outcomes.

• Law of total varianceNarrower topic: The identity applies to a random variable with finite second moment.

• Kolmogorov's zero–one lawNarrower topic: The law starts with a sequence of these measurable functions.

• Outcome (probability)Related: It converts outcomes into values that can be analyzed numerically.

• Skorokhod representation theoremNarrower topic: The conclusion realizes each measure as the law of a random variable.

• Bertrand's ballot theoremRelated: The running difference between candidates’ counts can be tracked as a random walk.

• 68–95–99.7 ruleNarrower topic: The rule describes probabilities for values of a random variable with a normal distribution.

• Bienaymé's identityNarrower topic: Bienaymé's identity applies to sums of random variables.

• Correlation function measurementNarrower topic: Correlation functions describe dependence among random variables indexed across observations or positions.

• Cramér's decomposition theoremNarrower topic: The theorem concerns sums of random variables rather than arbitrary numerical decompositions.

• Detection theoryNarrower topic: Noisy observations and detector outputs are modeled as random variables.

• Disordered systemsNarrower topic: Random variables provide a basic language for describing disorder.

• Infinite monkey theoremNarrower topic: Character choices can be modeled as random variables.

• Information and communication theoryRelated: Source symbols and noisy channel outputs are often represented as random variables.