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The Binomial Distribution The Binomial Distribution Section 5.2 ©McGraw-Hill Education. Objectives 1. Determine whether a random variable is binomial 2. Determine the probability distribution of a binomial random variable 3. Compute binomial probabilities 4. Compute the mean and variance of a binomial random variable ©McGraw-Hill Education. Objective 1 Objective 1 Determine whether a random variable is binomial ©McGraw-Hill Education. Binomial Distribution • Suppose that your favorite fast food chain is giving away a coupon with every purchase of a meal. Twenty percent of the coupons entitle you to a free hamburger, and the rest of them say “better luck next time.” Ten of you order lunch at this restaurant. Suppose we want to know the probability that three of you win a free hamburger? In general, if we let be the number of people out of ten that win a free hamburger. What is the probability distribution of ? In this section, we will learn that has a distribution called the binomial distribution, which is one of the most useful probability distributions. ©McGraw-Hill Education. Conditions for a Binomial Distribution In the problem just described, each time we examine a coupon, we call it a • “trial,” so there are 10 trials. When a coupon is good for a free hamburger, we will call it a “success.” The random variable represents the number of successes in 10 trials. A random variable that represents the number of successes in a series of trials A random variable that represents the number of successes in a series of trials • has a probability distribution called the binomial distribution. The conditions has a probability distribution called the binomial distribution. The conditions are: are: • A fixed number of trials are conducted. • A fixed number of trials are conducted. • There are two possible outcomes for each trial. One is labeled “success” and • There are two possible outcomes for each trial. One is labeled “success” and the other is labeled “failure.” the other is labeled “failure.” • The probability of success is the same on each trial. • The probability of success is the same on each trial. • The trials are independent. This means that the outcome of one trial does • The trials are independent. This means that the outcome of one trial does not affect the outcomes of the other trials. not affect the outcomes of the other trials. • The random variable represents the number of successes that occur. • The random variable represents the number of successes that occur. Notation: = number of trials, = probability of a success Notation: = number of trials, = probability of a success ©McGraw-Hill Education.
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