Sta2014Review2 - Random variables, discrete and continuous...

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Statistics 2014, Spring 2010 Exam 2 Review Topics Chapter 5 – Probability Random experiment. Sample space Events: Simple event; Compound event. Assigning probabilities to events: Classical approach: equally likely outcomes Relative frequency (empirical) approach Interpreting a probability, using the relative frequency (empirical) approach Mutually exclusive events Complement of an event – Complement Rule Union of events Intersection of events Basic Laws of Probability: (Kolmogorov’s Axioms): 1) For any event A, 0 P(A) 1. 2) P(S) = 1. In other words, the outcome of the random experiment is certain to be in the sample space. 3) If two events A and B are mutually exclusive, then . Equally likely outcomes due to random selection Addition Rule for Non-Mutually Exclusive Events Conditional Probability Independent events Multiplication Rule for independent events Chapter 6 – Discrete Probability Distributions
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Unformatted text preview: Random variables, discrete and continuous Probability distribution Required Properties of a Discrete Probability Distribution Expectation, or mean, of a probability distribution of a discrete random variable X. How to interpret the mean, using the relative frequency (empirical) approach. Variance of a discrete random variable X Conditions for a binomial experiment Binomial probability distribution; binomial random variable X Finding binomial probabilities using the TI-83 Mean, variance and standard deviation for the Binomial Distribution. Chapter 7 The Normal Probability Distribution Characteristics of normal distributions The Empirical Rule: Standard Normal Distribution Finding normal probabilities using the TI-83 calculator Inverting the process: finding values of x (or z) corresponding to a particular probability...
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