Probability theory

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Event Bayes theorem Expectation and variance Moment generating function Joint distribution Probability axioms Probability space Elementary event Complementary event Mutually exclusive events Collectively exhaustive events Probability measure Constant random variable Continuous random variable Complex random variable Random vector Random element Random compact set Conditional expectation Conditional distribution Conditional independence Statistical independence Pairwise independence Exchangeable random variables Independent and identically distributed random variables Law of total probability Law of total expectation Law of total variance Law of total cumulance Law of the unconscious statistician Rule of succession Variance Covariance Covariance function Correlation function Moment Central moment Standardized moment Cumulant Hausdorff moment problem Stieltjes moment problem Probability generating function Cumulant generating function Probability density function Probability mass function Cumulative distribution function Disintegration theorem Borel cantelli lemma Kolmogorov zero one law Hewitt savage zero one law Blumenthal zero one law Kolmogorov extension theorem Kolmogorov continuity theorem De finetti theorem Cox theorem Wald equation Inclusion exclusion principle Coupling Probability interpretations Bayesian probability Frequency probability Classical probability Propensity probability Principle of indifference Principle of maximum entropy Imprecise probability Dempster shafer theory Negative probability Filtration probability theory Total variation distance Hellinger distance Weak convergence of measures Empirical measure Random measure Intensity measure Gibbs measure Gaussian measure Infinite divisibility Indecomposable distribution Stability probability Cramer decomposition theorem Darmois skitovich theorem Kac bernstein theorem Second moment method Method of moments probability Stein lemma Slutsky theorem Algebra of random variables Uncorrelatedness Information entropy Mutual information Typical set Asymptotic equipartition property A posteriori probability A priori probability Accessible random variable Additive stochastic process Automaton probabilistic Brownian functional Brownian local time Complete probability formula Conditional density Conditional extremum Conditional mathematical expectation Conditional stability Conditionally complete lattice Conditionally periodic function Conditionally periodic motion Controlled stochastic process Degeneration probability of Erroneous decoding probability of Feller an introduction to probability theory and its applications Functional of a markov process Generating random variables Gnedenko a course in the theory of probability Half martingale Marginal probability its use in bayesian statistics as the evidence of models and bayes factors Markov andrei andreevich Markov chain class of positive states of a Markov chain class of zero states of a Markov chain decomposable Markov chain generalized Markov chain non decomposable Markov chain periodic Markov chain recurrent Markov criterion Markov form Markov function system Markov moment Markov process stationary Markov quadrature formula Martin boundary in the theory of markov processes Mathematical expectation Number theory probabilistic methods in Probabilistic metric space Probabilistic primality test Probability of large deviations Probability process Probable deviation Quantum probability Quantum stochastic processes Random variables transformations of Semi martingale Stationary stochastic process Statistical analysis of stochastic processes Statistical problems in the theory of stochastic processes Stochastic basis Stochastic boundedness Stochastic continuity Stochastic dependence Stochastic equivalence Stochastic indistinguishability Stochastic integration via the fock space of white noise Stochastic interval Stochastic numerical algorithm Stochastic point process Stochastic process compatible Stochastic process generalized Stochastic process renewable Stochastic process with independent increments Stochastic process with stationary increments Stochastic processes filtering of Stochastic processes interpolation of Stochastic processes prediction of Transition probabilities Wiener hopf equation Wiener it decomposition Independent events

Probability & Statistics GradoExplicación9 min

Por qué los triángulos aleatorios atrapan el centro del círculo una de cada cuatro veces

Coloca tres puntos al azar en un círculo y el triángulo contiene el centro exactamente una de cada cuatro veces. Dos demostraciones: un promedio honesto y luego dos monedas disfrazadas de geometría.