Glossary
- Sample Space (Ω) :
-
The complete set of mutually disjoint outcomes of a random experiment
- Event :
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A subset of the sample space
- Set of Events :
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(\({\mathcal E}\)) A set of subsets of the sample space that is algebraically closed under both complements and countable unions
- Probability Measure :
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(ℙ) A function that assigns a probability (a number between 0 and 1) to every event contained in \({\mathcal E}\)
- Random Variable (r.v.) :
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A mapping X: Ω → \({\mathcal R}\) ⊆ ℝ that assigns a numerical value to every element within the sample space
- Probability Mass Function (p.m.f.) :
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A function that assigns a probability to the event that a random variable assumes a given value, e.g., p X (x) = ℙ({ω ∈ Ω : X (ω) = x })
- Statistical Independence :
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The property that the probability of every joint event equals the product of the corresponding probabilities of the individual events
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Snapp, R.R. (2014). Probabilistic Analysis. In: Alhajj, R., Rokne, J. (eds) Encyclopedia of Social Network Analysis and Mining. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-6170-8_155
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