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Chapter 5—Discrete Probability Distributions

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CHAPTER 5—DISCRETE PROBABILITY DISTRIBUTIONS
MULTIPLE CHOICE 1. A numerical description of the outcome of an experiment is called a a. descriptive statistic b. probability function c. variance d. random variable ANS: D PTS: 1 TOP: Discrete Probability Distributions

2. A random variable that can assume only a finite number of values is referred to as a(n) a. infinite sequence b. finite sequence c. discrete random variable d. discrete probability function ANS: C PTS: 1 TOP: Discrete Probability Distributions

3. A probability distribution showing the probability of x successes in n trials, where the probability of success does not change from trial to trial, is termed a a. uniform probability distribution b. binomial probability distribution c. hypergeometric probability distribution d. normal probability distribution ANS: B PTS: 1 TOP: Discrete Probability Distributions

4. Variance is a. a measure of the average, or central value of a random variable b. a measure of the dispersion of a random variable c. the square root of the standard deviation d. the sum of the squared deviation of data elements from the mean ANS: B PTS: 1 TOP: Discrete Probability Distributions

5. A continuous random variable may assume a. any value in an interval or collection of intervals b. only integer values in an interval or collection of intervals c. only fractional values in an interval or collection of intervals d. only the positive integer values in an interval ANS: A PTS: 1 TOP: Discrete Probability Distributions

6. A description of the distribution of the values of a random variable and their associated probabilities is called a a. probability distribution b. random variance c. random variable d. expected value ANS: A PTS: 1 TOP: Discrete Probability Distributions

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