Unformatted text preview: that the assumption is probably not correct. Relative Frequency: number of times A occurred P1A2 = number of trials Classical Approach: s P 1 A2 = (equally likely outcomes) n Probability property: 0 … P 1A2 … 1 Complement of Event A: P1A2 = 1  P 1A2 Addition Rule: Disjoint Events: Cannot occur together. If A, B are disjoint: P1A or B2 = P1A2 + P1B2 If A, B are not disjoint: P1A or B2 = P1A2 + P1B2  P1A and B2 Multiplication Rule: Independent Events: No event affects probability of other event. If A, B are independent: P1A and B2 = P1A2 # P1B2 If A, B are dependent: P1A and B2 = P1A2 # P1B ƒ A2 Random Variables
Random Variable: Variable that has a single numerical value, determined by chance, for each outcome. Probability Distribution: Graph, table, or formula that gives the probability for each value of the random variable. Requirements of random variable: 1. g P1x2 = 1 2. 0 … P1x2 … 1 Parameters of random variable: m = g x # P1x2
2 C n1 + Two Means (Independent): 1 x1  x22  E 6 1m1  u22 6 1 x1  x22 + E where E = ta>2 s2...
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 Spring '10
 Serpa
 Statistics, Normal Distribution, Null hypothesis

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