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A probability distribution describes how probability mass is assigned across possible outcomes or values. It formalizes random variables via probability mass, density, or cumulative functions for discrete and continuous cases. Distributions are fundamental to statistics, simulation, inference, probabilistic modeling, risk assessment, and decision analysis in…
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Theoretical construct: explains a term, principle, or mental model.
What you need to understand to reason about a domain.
A probability distribution assigns probabilities or probability densities to the possible values of a random variable.
The concept emerged from formalizing randomness in probability theory and statistics; discrete and continuous distributions became foundations for statistical models and simulation.
Think of a map of uncertainty: it shows how plausible each value is. A discrete distribution assigns weights to individual outcomes; a continuous one describes density across intervals.
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Probability distribution
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