1. A numerical description of the outcome of an experiment is called a
a. descriptive statistic
b. probability function
c. variance
d. random variable
ANSWER: d
POINTS: 1
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
ANSWER: c
POINTS: 1
3. 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
ANSWER: a
POINTS: 1
4. An experiment consists of making 80 telephone calls in order to sell a particular insurance
,policy. The random variable in this experiment is the number of sales made. This random variable
is a
a. discrete random variable
b. continuous random variable
c. complex random variable
d. None of the answers is correct.
ANSWER: a
POINTS: 1
5. The number of customers that enter a store during one day is an example of
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
ANSWER: b
POINTS: 1
6. An experiment consists of measuring the speed of automobiles on a highway by the use of
radar equipment. The random variable in this experiment is speed, measured in miles per hour.
This random variable is a
a. discrete random variable
b. continuous random variable
c. complex random variable
d. None of the answers is correct.
ANSWER: b
POINTS: 1
,7. The weight of an object, measured in grams, is an example of
a. a continuous random variable
b. a discrete random variable
c. either a continuous or a discrete random variable, depending on the weight of the
object
d. either a continuous or a discrete random variable depending on the units of
measurement
ANSWER: a
POINTS: 1
8. The weight of an object, measured to the nearest gram, is an example of
a. a continuous random variable
b. a discrete random variable
c. either a continuous or a discrete random variable, depending on the weight of the
object
d. either a continuous or a discrete random variable depending on the units of
measurement
ANSWER: b
POINTS: 1
9. A description of how the probabilities are distributed over the values the random variable can
assume is called a
a. probability distribution
b. probability function
c. random variable
d. expected value
ANSWER: a
POINTS: 1
10. Which of the following is(are) required condition(s) for a discrete probability function?
, a. ∑f(x) = 0
b. f(x) ≥ 1 for all values of x
c. f(x) < 0
d. None of the answers is correct.
ANSWER: d
POINTS: 1
11. Which of the following is not a required condition for a discrete probability function?
a. f(x) ≥ 0 for all values of x
b. ∑f(x) = 1
c. ∑f(x) = 0
d. All of the answers are correct.
ANSWER: c
POINTS: 1
12. Which of the following statements about a discrete random variable and its probability
distribution are true?
a. Values of the random variable can never be negative.
b. Negative values of f(x) are allowed as long as ∑f(x) = 1.
c. Values of f(x) must be greater than or equal to zero.
d. The values of f(x) increase to a maximum point and then decrease.
ANSWER: c
POINTS: 1
13. A measure of the average value of a random variable is called a(n)
a. variance