handout day5

Probability and Statistics for Engineering and the Sciences (with Student Suite Online)

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Winter, 2008 Tuesday, Jan. 15 Stat 321 – Lecture 5 Probability Rules (2.2) Special case: In situations where the outcomes of an experiment are equally likely to occur (e.g., tossing a fair coin), the exact probability of an outcome is 1/ N , where N is the total number of outcomes possible (p. 57). If we have a set of outcomes, A, then P(A) = (# of outcomes in A)/ N . Example 1: In 1998 the American Film Institute created a list of the top 100 American films ever made (http://www.afi.com/tvevents/100years/movies.aspx). Suppose that two people gather to watch one of these movies and, to avoid potentially endless debates about a selection, decide to choose a movie at random from the “top 100” list. The following 2 × 2 table classifies each movie according to whether it was seen by Allan and whether it was seen by Beth. The “at random” selection implies that each of the 100 films is equally likely to be chosen, (i.e., each has probability 1/100). Thus, the probabilities of these various events can be calculated by counting how many of the 100 films comprise the event of interest. Let A denote the event that Allan has seen the film, so A = {films that Allan has seen} and B denote the event that Beth has seen the
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This note was uploaded on 01/31/2008 for the course STAT 321 taught by Professor Chance during the Winter '08 term at Cal Poly.

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handout day5 - Winter 2008 Tuesday Jan 15 Stat 321 –...

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