1. A numerical description of the outcome of an experiment is called a _____.
A) random variable
2. A random variable that can assume only a finite number of values is referred to as a(n) _____.
A) discrete random variable
3. A continuous random variable may assume _____.
A) any value in an interval or collection of intervals
4. 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
5. The number of customers who enter a store during one day is an example of _____.
A) a discrete random variable
6. 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
7. The weight of an object, measured in grams, is an example of _____.
A) a continuous random variable
8. The weight of an object, measured to the nearest gram, is an example of _____.
A) a discrete random variable
9. A description of how the probabilities are distributed over the values the random variable can assume is called a(n) _____.
A) probability distribution
10.Which of the following is(are) required condition(s) for a discrete probability function?
A) ∑f(x) = 1
11. Which of the following is NOT a required condition for a discrete probability function?
A) ∑f(x) = 0
12. 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.
13. A measure of the average value of a random variable is called a(n) _____.
A) expected value
14. A weighted average of the value of a random variable, where the probability function provides weights, is known as _____.
A) the expected value
15. The expected value of a random variable is the _____.
A) Mean Value
16. The expected value of a discrete random variable _____.
A) is the average value for the random variable over many repeats of the experiment
17. Excel’s _____ function can be used to compute the expected value of a discrete random variable.
A) SUMPRODUCT
18. Variance is _____.
A) a measure of the dispersion of a random variable
19. The variance is a weighted average of the _____.
A) squared deviations from the mean
20. Excel’s _____ function can be used to compute the variance of a discrete random variable.
A) SUMPRODUCT
21. The standard deviation is the _____.
A) positive square root of the variance
22. 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
23. Which of the following is a characteristic of a binomial experiment?
A) The trials are independent.
24. In a binomial experiment, the _____.
A) probability of success does not change from trial to trial
25.Which of the following is NOT a characteristic of an experiment where the binomial probability distribution is applicable?
A) The trials are dependent.
26.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.
27. 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
28.The binomial probability distribution is used with _____.
A) a discrete random variable
29.48. 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
30.49. In a binomial experiment, the probability of success is .06. What is the probability of two successes in seven trials?
A) 0.0554
31.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) 0.0142
32.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) 0.0038
33.Excel’s BINOM.DIST function can be used to compute _____.
A) cumulative binomial probabilities
34.Excel’s BINOM.DIST function has how many inputs?
A) 4
35.When using Excel’s BINOM.DIST function, one should choose TRUE for the fourth input if _____.
A) a cumulative probability is desired
36.The expected value for a binomial probability distribution is _____.
A) E(x) = np
37.The variance for the binomial probability distribution is _____.
A) Var(x) = np(1 − p)
38.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
39.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
40.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
41.The student body of a large university consists of 60% female students. A random sample of 8 students is selected.Refer to Exhibit 5-8. What is the random variable in this experiment?
A) the number of female students out of 8
42.The student body of a large university consists of 60% female students. A random sample of 8 students is selected.Refer to Exhibit 5-8. What is the probability that among the students in the sample exactly two are female? A) 0.0413
43.The student body of a large university consists of 60% female students. A random sample of 8 students is selected.Refer to Exhibit 5-8. What is the probability that among the students in the sample at least 7 are female? A) 0.1064
44.The student body of a large university consists of 60% female students. A random sample of 8 students is selected.Refer to Exhibit 5-8. What is the probability that among the students in the sample at least 6 are male? A) 0.0499
45.Forty percent of all registered voters in a national election are female. A random sample of 5 voters is selected. Refer to Exhibit 5-9. What is the random variable in this experiment? A) the number of female voters out of 5
46.Forty percent of all registered voters in a national election are female. A random sample of 5 voters is selected. Refer to Exhibit 5-9. The probability that the sample contains 2 female voters is _____. A) 0.3456
47.Forty percent of all registered voters in a national election are female. A random sample of 5 voters is selected. Refer to Exhibit 5-9. The probability that there are no females in the sample is _____. A) 0.0778
48.The probability Pete will catch fish when he goes fishing is .8. Pete is going fishing 3 days next week. Refer to Exhibit 5-10. What is the random variable in this experiment? A) the number of days out of 3 that Pete catches fish
49.The probability Pete will catch fish when he goes fishing is .8. Pete is going fishing 3 days next week. Refer to Exhibit 5-10. The probability that Pete will catch fish on exactly 1 day is _____. A) 0.096
50.The probability Pete will catch fish when he goes fishing is .8. Pete is going fishing 3 days next week. Refer to Exhibit 5-10. The probability that Pete will catch fish on 1 or fewer days is _____. A) 0.104
51.The probability Pete will catch fish when he goes fishing is .8. Pete is going fishing 3 days next week. Refer to Exhibit 5-10. The expected number of days Pete will catch fish is _____. A) 2.4
52.The probability Pete will catch fish when he goes fishing is .8. Pete is going fishing 3 days next week. Refer to Exhibit 5-10. The variance of the number of days Pete will catch fish is _____. A) 0.48
53.The random variable x is the number of occurrences of an event over an interval of 10 minutes. It can be assumed the probability of an occurrence is the same in any two time periods of an equal length. It is known that the mean number of occurrences in 10 minutes is 5.3. Refer to Exhibit 5-11. The appropriate probability distribution for the random variable is _____. A) discrete
54.The random variable x is the number of occurrences of an event over an interval of 10 minutes. It can be assumed the probability of an occurrence is the same in any two time periods of an equal length. It is known that the mean number of occurrences in 10 minutes is 5.3. Refer to Exhibit 5-11. The expected value of the random variable x is A) 5.3
55.The random variable x is the number of occurrences of an event over an interval of 10 minutes. It can be assumed the probability of an occurrence is the same in any two time periods of an equal length. It is known that the mean number of occurrences in 10 minutes is 5.3. Refer to Exhibit 5-11. The probability there are 8 occurrences in 10 minutes is _____. A) 0.0771
56.The random variable x is the number of occurrences of an event over an interval of 10 minutes. It can be assumed the probability of an occurrence is the same in any two time periods of an equal length. It is known that the mean number of occurrences in 10 minutes is 5.3. Refer to Exhibit 5-11. The probability there are less than 3 occurrences is _____. A) 0.1016
57.The key difference between binomial and hypergeometric distributions is that with the hypergeometric distribution the _____.
A) probability of success changes from trial to trial
58.Excel’s HYPGEOM.DIST function can be used to compute _____.
A) hypergeometric probabilities
59.Excel’s HYPGEOM.DIST function has how many inputs?
A) 5
60.When using Excel’s HYPGEOM.DIST function, one should choose TRUE for the fifth input if _____.
A) a cumulative probability is desired
61.The binomial probability distribution is most symmetric when _____.
A) p equals 0.5
62.Experimental outcomes that are based on measurement scales such as time, weight, and distance can be described by _____ random variables.
A) continuous
63.Which of the following properties of a binomial experiment is called the stationarity?
A) The probability of success is the same for each trial.
64.The expected value of a random variable is the _____.
A) mean value
65.In a binomial experiment consisting of five trials, the number of different values that x (the number of successes) can assume is _____.
A) 6
67. A binomial probability distribution with p = 0.3 is _____.
A) negatively skewed
68.An example of a bivariate experiment is _____.
A) rolling a pair of dice
69.Bivariate probabilities are often called _____.
A) joint probabilities
70.To compute a binomial probability. we must know all of the following except the _____.
A) number of elements in the population