Set Theory Background for Probability Defining Sets (A Very Naïve Approach)
Set theory background for probability Defining sets (a very naïve approach) A set is a collection of distinct objects. The objects within a set may be arbitrary, with the order of objects within them having no significance. Here are several examples, demonstrating the above properties: 2,3,5,7,11,13,17,19 (the set of all prime numbers smaller than 20) , , , , , ,′′ The brackets … surround the objects that belong to a certain set. Objects are separated by commas. Note that: 1,2,3 1,3,2 (there is no ordering of objects within a set) 1,2,3,3 1,2,3 (sets contain one copy of each distinct object) Working with sets 1. Membership If an object is a member of a set we write: ∈. If an object is not a member of a set we write: ∉. 2. Subsets Assume that we have a set and another set , such that every element in is also a member of . Then we can write: ⊆. We say that is a subset of . Formally, we can write: ∀∈∈ (any that is a member of is a member of ) No need to worry: we will usually not encounter this formal logic notation. Notice that the sets of , may actually be equal. If they are not, there must be some member of that is not a member of . In this case we can write: ⊂ i.e. is a true subset of , or in logic notation: ∀ ∈ ∈ ∧∃∈∈ (any that is in is in AND there exists a in that is not in ). 3. Set equality Sets , are equal if and only if ⊆ and ⊆.
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