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Probability Distributions and the Binomial Distribution BUSA 2100, Sections 5.1 - 5.4 Random Variables A random variable is a quantity that changes values from one occurrence to another, in no particular pattern. Example 1: Let X = number of heads on 3 tosses of a coin; X = 0, 1, 2, 3 . Example 2: Let Y = number of papers sold daily in a newspaper rack; Y = 0, 1, 2, 3, 4, 5 . Discrete and Continuous Random Variables A discrete random variable can have only a small number of specific possible values (usually whole numbers). It tells “how many.” The random variables in Examples 1, 2 are discrete. A continuous random variable can have an undetermined large finite number of values. It tells “how much.” Continuous Random Variables Example 3: Let W = amount of time in minutes that a family watches TV in a month. This is a continuous random variable. Example 4: Weight and distance are also continuous random variables. Probability Distributions A probability distribution (for a discrete random variable) is a list of all possible outcomes together with their associated probabilities. State probability distribution for 3 coins. Expected Value What is the “average” value for X for the probability X P(X) distribution 60 .1 shown at 70 .2 the right? 80 .3 90 .4 The median is 75; the simple average is 75; is there a more accurate answer? Expected Value, Page 2 . Republican/Democrat Ex. Ex. 1A: A large group of people consists of 40% Republicans and 60% Democrats. If a sample of 5 is chosen, what is the probability of getting 2 Republicans and 3 Democrats, in that order? Rep/Dem Example, Page 2 Ex. 1B: What is the prob. of choosing 2 Repub. and 3 Democrats in any order? Rep/Dem Example, Page 3 To avoid listing the number of ways that 2 R’s and 3 D’s can be arranged, we can use combinations to determine how many ways we can choose which two of the 5 selections will be Republicans. The Republican/Democrat problem is an example of the binomial distribution. Intro. to Binomial Distribution Binomial problems have 2 characteristics (requirements). (1) Most important characteristic: Each selection must have exactly two possible outcomes. Examples: (2) Each selection is independent of the other selections. Binomial Notation & Formula Do each item for Rep./Dem. problem. n = number of selections Define “success”. p = probability of success on one selection r = number of successes Binomial Problems, Page 1 Example 1: A large lot of manufactured items contains 10% defectives. In a random sample of 6 items, what is the probability that exactly 2 are defective? Binomial Problems, Page 2 Example 2: Thirty percent of customers that enter an appliance store make purchases. What is the prob. that 4 of the next 10 customers will buy something? Binomial Problems, Page 3 For convenience we will use a binomial table, looking up n, p, r, in that order. Example 3A: A large lot of manufactured items contains 20% defectives. In a random sample of 8 items, what is the probability that 5 or more items are defective? Binomial Problems, Page 4 Ex. 3B: P(2 or fewer) = Binomial Problems, Page 5 Example 4: Sixty percent of the workers in a plant belong to a union. A random sample of 12 is chosen. Find the probability that exactly 4 belong to a union. Binomial Problems, Page 6 . Binomial Problems, Page 7 Example 5: At Blaylock Company, in the past, 25% of new employees were not hired for a permanent position after a six-months probationary period. Among 7 new employees, what is the prob. that 5 or more will be hired permanently? Binomial Problems, Page 8 It is essential that the values of p and r are consistent with the way that success is defined.