[{"n": "Stochastic process", "u": "/e/probability-and-stochastic-processes/stochastic-process/", "s": "The mathematical study of random phenomena over time or space."}, {"n": "Wiener process", "u": "/e/probability-and-stochastic-processes/wiener-process/", "s": "A continuous-time stochastic process with independent Gaussian increments."}, {"n": "Chi-squared test", "u": "/e/probability-and-stochastic-processes/chi-squared-test/", "s": "Statistical test for independence in contingency tables."}, {"n": "Student's t-distribution", "u": "/e/probability-and-stochastic-processes/student-s-t-distribution/", "s": "A bell-shaped distribution with heavier tails than normal."}, {"n": "Student's t-test", "u": "/e/probability-and-stochastic-processes/student-s-t-test/", "s": "A statistical hypothesis test using Student's t-distribution to compare means."}, {"n": "Type I and type II errors", "u": "/e/probability-and-stochastic-processes/type-i-and-type-ii-errors/", "s": "Two fundamental errors in statistical hypothesis testing."}, {"n": "Bayesian inference", "u": "/e/probability-and-stochastic-processes/bayesian-inference/", "s": "Statistical method using Bayes' theorem to update hypothesis probabilities."}, {"n": "Markov chain", "u": "/e/probability-and-stochastic-processes/markov-chain/", "s": "A stochastic process where the future depends only on the present."}, {"n": "Monte Carlo method", "u": "/e/probability-and-stochastic-processes/monte-carlo-method/", "s": "Computational algorithms using repeated random sampling for numerical results."}, {"n": "Random variable", "u": "/e/probability-and-stochastic-processes/random-variable/", "s": "A measurable function from sample space to measurable space."}, {"n": "Variance", "u": "/e/probability-and-stochastic-processes/variance/", "s": "Variance measures how far numbers spread from their average."}, {"n": "Correlation", "u": "/e/probability-and-stochastic-processes/correlation/", "s": "Correlation measures linear relationships but does not imply causation."}, {"n": "Covariance", "u": "/e/probability-and-stochastic-processes/covariance/", "s": "Measure of joint variability between two random variables."}, {"n": "Probability density function", "u": "/e/probability-and-stochastic-processes/probability-density-function/", "s": "A function giving relative probability per unit length for continuous variables."}, {"n": "Cumulative distribution function", "u": "/e/probability-and-stochastic-processes/cumulative-distribution-function/", "s": "Function giving probability that a variable is ≤ a value."}, {"n": "Central limit theorem", "u": "/e/probability-and-stochastic-processes/central-limit-theorem/", "s": "A theorem on the convergence of sample means to normality."}, {"n": "Law of large numbers", "u": "/e/probability-and-stochastic-processes/law-of-large-numbers/", "s": "Averages of many trials converge to the expected value."}, {"n": "Entropy (information theory)", "u": "/e/probability-and-stochastic-processes/entropy-information-theory/", "s": "Measure of average uncertainty in a random variable's outcomes."}, {"n": "Likelihood function", "u": "/e/probability-and-stochastic-processes/likelihood-function/", "s": "Measures relative merit of models for given data."}, {"n": "Maximum likelihood estimation", "u": "/e/probability-and-stochastic-processes/maximum-likelihood-estimation/", "s": "A method maximizing likelihood to estimate distribution parameters."}]