Chapter__BinomialDistribution - Chapter 5 (5.4) Binomial...

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Chapter 5 (5.4) Binomial Probability Distribution • Random Variables • Binomial Probability Distribution • Expected Value, Variance, and Standard Deviation .40 +- .30 - .20 -I-- .10 o 1 2 3 4 Random Variables • A random variable is a numerical description of the outcome of an experiment. • A random variable can be classified as being either discrete or continuous depending on the numerical values it assumes. • A discrete random variable may assume either a finite number of values or an infinite sequence of values. • A continuous random variable may assume any numerical value in an interval or collection of intervals. Example 1: Suppose there are 10 traffic lights when you drive from your apartment to school. Let X = number of red lights you encounter on a day. What values does X take? Is X a discrete or a continuous random variable? Example 2: Suppose maximum waiting time at a traffic light is 1/2 minutes. X = Total time you wait at all 10 traffic lights. What values does X take?
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Chapter__BinomialDistribution - Chapter 5 (5.4) Binomial...

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