223 statistics 851 fall 2013 prof michael kozdron

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Unformatted text preview: n encountered in elementary probability courses, namely if X is a continuous random variable with density fX , then ￿∞ E(X ) = xfX (x) dx. −∞ It turns out that verifying this formula is somewhat more involved than the discrete formula. As such, we need to take a brief detour into some general function theory. Some General Function Theory Suppose that f : X → Y is a function. We are implicitly assuming that f is defined for all x ∈ X. We call X the domain of f and call Y the codomain of f . The range of f is the set f (X) = {y ∈ Y : f (x) = y for some x ∈ X}. Note that f (X) ⊆ Y. If f (X) = Y, then we say that f is onto Y. Let B ⊆ Y. We define f −1 (B ) by f −1 (B ) = {x ∈ X : f (x) = y for some y ∈ B } = {f ∈ B } = {x : f (x) ∈ B }. We call X a topological space if there is a notion of open subsets of X. The Borel σ -algebra on X, written B (X), is the σ -algebra generated by the open sets of X. 22–2 Let X and Y be topological spaces. A function f : X → Y is called...
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