1. A binomial probability distribution with p = 0.3 is _____. A. negatively skewed
2. A continuous random variable may assume _____. A. any value in an interval or collection of intervals
3. A description of how the probabilities are distributed over the values the random variable can assume is called a(n) _____. A. probability distribution
4. A local bottling company has determined the number of machine breakdowns per month and their respective probabilities as shown below. A. 1.70
5. A marketing manager instructs his team to make 80 telephone calls to attempt to sell an insurance policy. The random variable in this experiment is the number of sales made. This random variable is a _____ A. discrete random variable
6. A measure of the average value of a random variable is called a(n) _____. A. expected value
7. A numerical description of the outcome of an experiment is called a _____. A. random variable
8. 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. binomial probability distribution
9. A production process produces 2% defective parts. A sample of five parts from the production process is selected. What is the probability that the sample contains exactly two defective parts? A. .0038
10. A property of the Poisson distribution is that the mean equals the _____. A. variance
11. A random variable that can assume only a finite number of values is referred to as a(n) _____. A. discrete random variable
13. A weighted average of the value of a random variable, where the probability function provides weights, is known as _____. A. the expected value
14. An example of a bivariate experiment is _____. A. rolling a pair of dice
15. Assume that you have a binomial experiment with p = 0.4 and a sample size of 50. The variance of this distribution is _____. A. 12
16. Assume that you have a binomial experiment with p = 0.5 and a sample size of 100. The expected value of this distribution is _____. A. 50
17. Bivariate probabilities are often called _____. A. joint probabilities
18. Excel’s _____ function can be used to compute the expected value of a discrete random variable. A. SUMPRODUCT
19. Excel’s _____ function can be used to compute the variance of a discrete random variable. A. SUMPRODUCT
20. Excel’s BINOM.DIST function can be used to compute _____. A. both binomial probabilities and cumulative binomial probabilities
21. Excel’s BINOM.DIST function has how many inputs? A. 4
22. Excel’s HYPGEOM.DIST function can be used to compute _____. A. hypergeometric probabilities
23. Excel’s POISSON.DIST function can be used to compute _____. A. both Poisson probabilities and cumulative Poisson probabilities
24. Exhibit 5-1
The following represents the probability distribution for the daily demand of microcomputers at a local store.
Demand 01234
Probability .1.2.3.2.2
Refer to Exhibit 5-1. The expected daily demand is A. 2.2
25. Exhibit 5-2
The probability distribution for the daily sales at Michael’s Co. is given below.
Daily Sales ($1000s) 40, 50, 60, 70
Probability .1, .4, .3, .2
Refer to Exhibit 5-2. The expected daily sales are _____. A. $56,000
26. Exhibit 5-5
AMR is a computer-consulting firm. The number of new clients that it has obtained each month has ranged from 0 to 6. The number of new clients has the probability distribution that is shown below. A. 3.05
27. Experimental outcomes that are based on measurement scales such as time, weight, and distance can be described by _____ random variables. A. continuous
28. Four percent of the customers of a mortgage company default on their payments. A sample of five customers is selected. What is the probability that exactly two customers in the sample will default on their payments? A. .0142
29. Highway patrol officers measure the speed of automobiles on a highway using radar equipment. The random variable in this experiment is speed, measured in miles per hour. This random variable is a _____. A. continuous random variable
30. If one wanted to find the probability of 10 customer arrivals in an hour at a service station, one would generally use the _____. A. Poisson probability distribution
31. If you are conducting an experiment where the probability of a success is .02 and you are interested in the probability of two successes in 15 trials, the correct probability function to use is the _____. A. binomial probability function
32. In a binomial experiment consisting of five trials, the number of different values that x (the number of successes) can assume is _____. A. 6
33. In a binomial experiment, the _____. A. probability of success does not change from trial to trial
34. In a binomial experiment, the probability of success is .06. What is the probability of two successes in seven trials? A. 0554
35. In the textile industry, a manufacturer is interested in the number of blemishes or flaws occurring in each 100 feet of material. The probability distribution that has the greatest chance of applying to this situation is the _____. A. Poisson distribution
36. Refer to Exhibit 5-1. The probability of having a demand for at least two microcomputers is _____ A. 7
37. Refer to Exhibit 5-2. The probability of having sales of at least $50,000 is _____. A. 90
38. Refer to Exhibit 5-3. What is the probability that in a given game the Lions will score at least 1 goal? A. .95
39. Refer to Exhibit 5-3. What is the probability that in a given game the Lions will score less than 3 goals? A. .55
40. Refer to Exhibit 5-3. What is the probability that in a given game the Lions will score no goals? A. None of the answers is correct.
41. Refer to Exhibit 5-4. The probability of at least 3 breakdowns in a month is _____. A. None of the answers is correct.
42. Refer to Exhibit 5-4. The probability of no breakdowns in a month is _____. A. None of the answers is correct.
43. Refer to Exhibit 5-5. The standard deviation is _____. A. 1.431
44. Refer to Exhibit 5-5. The variance is _____. A. 2.0475
45. The _____ probability function is based in part on the counting rule for combinations. A. hypergeometric
46. The binomial probability distribution is most symmetric when _____. A. p equals 0.5
47. The binomial probability distribution is used with _____. A. a discrete random variable
48. The expected value for a binomial probability distribution is _____. A. E(x) = np
49. The expected value of a discrete random variable _____. A. is the average value for the random variable over many repeats of the experiment
50. The expected value of a random variable is the _____. A. mean value
51. The expected value of a random variable is the _____. A. None of the answers is correct.
52. The function used to compute the probability of x successes in n trials, when the trials are dependent, is the _____ A. hypergeometric probability function
53. The key difference between binomial and hypergeometric distributions is that with the hypergeometric distribution the _____. A. probability of success changes from trial to trial
54. The number of customers The number of customers
a. a continuous random variable
b. a discrete random variable
c. either a continuous or a discrete random variable, depending on the number of the customers d. either a continuous or a discrete random variable, depending on the gender of the customers A. a discrete random variable
55. The number of electrical outages in a city varies from day to day. Assume that the number of electrical outages (x) in the city has the following probability distribution. A. 0.26 and .577
56. The Poisson probability distribution is a _____. a. continuous probability distribution A. discrete probability distribution
57. The probability distribution for the number of goals the Lions soccer team makes per game is given below.
Number of Goals 0, 1, 2, 3, 4
Probability .05, .15, .35, .30, .15
Refer to Exhibit 5-3. The expected number of goals per game is _____ A. 2.35
58. The standard deviation is the _____. A. positive square root of the variance
59. The standard deviation of a binomial distribution is _____. A. None of the answers is correct.
60. The variance for the binomial probability distribution is _____. A. Var(x) = np(1 − p)
61. The variance is a weighted average of the _____. A. squared deviations from the mean
62. The weight of an object, measured in grams, is an example of _____. A. a continuous random variable
63. The weight of an object, measured to the nearest gram, is an example of _____. A. a discrete random variable
64. To compute a binomial probability. we must know all of the following except the _____. A. number of elements in the population
65. To compute the probability that in a random sample of n elements, selected without replacement, we will obtain x successes, we would use the _____. A. hypergeometric probability distribution
66. Twenty percent of the students in a class of 100 are planning to go to graduate school. The standard deviation of this binomial distribution is _____. A. 4
67. Variance is _____. a. a measure of the average, or central value of a random variable A. measure of the dispersion of a random variable
68. When dealing with the number of occurrences of an event over a specified interval of time or space and when the occurrence or nonoccurrence in any interval is independent of the occurrence or nonoccurrence in any other interval, the appropriate probability distribution is a _____. A. Poisson distribution
69. When sampling without replacement, the probability of obtaining a certain sample is best given by a _____. A. hypergeometric distribution
70. When using Excel’s BINOM.DIST function, one should choose TRUE for the fourth input if _____. A. a cumulative probability is desired
71. When using Excel’s POISSON.DIST function, one should choose TRUE for the third input if _____. A. a cumulative probability is desired
72. Which of the following is a characteristic of a binomial experiment? A. The trials are independent.
73. Which of the following is NOT a characteristic of an experiment where the binomial probability distribution is applicable? A. The trials are dependent
74. Which of the following is NOT a property of a binomial experiment? A. The probabilities of the two outcomes can change from one trial to the next.
75. Which of the following is NOT a required condition for a discrete probability function? A. ∑f(x) = 0
76. Which of the following is(are) required condition(s) for a discrete probability function? A. None of the answers is correct.
77. Which of the following properties of a binomial experiment is called the stationarity? A. The probability of success is the same for each trial.
78. Which of the following statements about a discrete random variable and its probability distribution is true? A. Values of f(x) must be greater than or equal to zero.
79. x is a random variable with the probability function: f(x) = x/6 for x = 1, 2, or 3. The expected value of x is _____. A. 2.333
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