ch5-6_Vnotes

ch5-6_Vnotes - x MGMT 305 Business Statistics f(x)...

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μ x x f f ( ( x x ) ) Π9 δ Ε  ≡ ♠ Ν ζ Ξ ƒ Α + ξ MGMT 305 Business Statistics Probability Distributions Outline: §5.4: Binomial Probability Distribution §6.2: Normal Probability Distribution Binomial Probability Distribution: • Random Variables • Binomial Probability Distribution • Expected Value, Variance, and Standard Deviation . 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. 1
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Properties of a Binomial Experiment: 1. The experiment consists of a sequence of n identical trials. 2. Two outcomes, success and failure , are possible on each trial. 3. The probability of a success, denoted by p , does not change from trial to trial. 4. The trials are independent. Binomial Probability Function: where: f ( x ) = the probability of x successes in n trials n = the number of trials p = the probability of success on any one trial 2
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Example 1: Consider a binomial experiment with n=10 and p=.30. (a) Use the binomial probability function to find f (2). (b)
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ch5-6_Vnotes - x MGMT 305 Business Statistics f(x)...

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