Transcription of Chapter 5 An Introduction to Discrete Probability
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Chapter 5 An Introduction to Discrete Probability
Chapter 5An Introduction to Discrete Sample Space, Outcomes, Events, ProbabilityRoughly speaking, Probability theory deals with experiments whose outcome arenot predictable with certainty. We often call such are subject to chance. Using a mathematical theory of Probability , we may beable to calculate the likelihood of some the Introduction to his classical book [1] (first published in 1888), JosephBertrand (1822 1900) writes (translated from French to English): How dare we talk about the laws of chance (in French: le hasard)? Isn t chancethe antithesis of any law? In rejecting this definition, I will not propose anyalternative.
Because events are subsets of the sample space W, they can be combined using the set operations, union, intersection, and complementation. If the sample space W is finite, the definition for the probability Pr(A) of an event A W given in Definition 5.1 shows that if A,B are two disjoint events (this means that A\B= 0),/ then Pr(A[B)=Pr(A)+Pr(B).
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