By Frank Ayres Jr.

ISBN-10: 9684229178

ISBN-13: 9789684229174

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Thus, given a sequence of increasing or decreasing sets, the limit of the sequence can be defined in a natural way: the union of the sets of the sequence or the intersection of the sets of the sequence, respectively. Say that we have a sigma-field F and an increasing sequence of sets Fn ; n = 1, 2, . . of sets in the sigma-field. Since the limit of the sequence is defined as a union and since the union of a countable number of events must be an event, then the limit must be an event. For example, if we are told that the sets [1, 2 − 1/n) are all events, then the limit [1, 2) must also be an event.

0]. Observe again that this is the smallest possible event space for any given sample space because no other event space can have fewer elements. 9] Given a sample space Ω, then the collection of all subsets of Ω is a sigma-field. This is true since any countable sequence of set-theoretic operations on subsets of Ω must yield another subset of Ω and hence must be in the collection of all possible subsets. The collection of all subsets of a space is called the power set of the space. Observe that this is the largest possible event space for the given sample space, because it contains every possible subset of the sample space.

13) r∈F or, equivalently, P (F ) = where now p(r) = 1/2 for each r ∈ Ω. The function p is called a probability mass function or pmf because it is summed over points to find total probability, just as point masses are summed to find total mass in physics. Be cautioned that P is defined for sets and p is defined only for points in the sample space. This can be confusing when dealing with one-point or singleton sets, for example P ({0}) = p(0) P ({1}) = p(1). This may seem too much work for such a little example, but keep in mind that the goal is a formulation that will work for far more complicated and interesting examples.

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Algebra moderna by Frank Ayres Jr.


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