International Business QNM222 Study Guide - Coin Flipping, Probability Distribution, Random Variable
12 Mar 2014
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Random variable: is a function or rule that assigns a number to each outcome of an experiment (ex. Instead of talking about the coin flipping event as {heads, tails} think of it as the number of heads when flipping a coin {1, 0} - numerical events) Probability distribution is a table, formula, or graph that describes the values of a random variable and the probability associated with these values. Probability notation: p( = ), represent the name of the random variable and represent the value of the random variable. more simply we use p(x) Since we"re describing a random variable (discrete or continuous) we have two types of probability distributions: Discrete probability distribution, (ch7) one that takes on a countable number of values (integers: e. g. values on the rolling of dice: 2, 3, , 12) Continuous probability distribution (ch8) one whose values are not discrete, not countable. (real numbers: e. g. time: 3. 5 min, distance: 15. 27 mm, )
