DATA 11-15
Let A and B be the events of the FDA approving and rejecting a new drug to treat hypertension, respectively. The events A and B are:
mutually exclusive
P(Ā) = 1 - P(A) is the:
rule of complements
If A and B are mutually exclusive events with P(A) = 0.30 and P(B) = 0.40, then the probability that either A or B occur is:
0.70
The probability of an event and the probability of its complement always sum to:
1
If two events are collectively exhaustive, what is the probability that one or the other occurs?
1.00
If A and B are any two events with P(A) = .8 and P(B|A) = .4, then the joint probability of A and B is:
32
There are two types of random variables, they are
discrete and continuous
Conditional probability is the probability that an event will occur, with no other events taken into consideration.
false
If A and B are independent events with P(A) = 0.40 and P(B) = 0.50, then P(A/B) is 0.50.
false
If A and B are two independent events with P(A) = 0.20 and P(B) = 0.60, then P(Aand B) = 0.80.
false
If events A and B have nonzero probabilities, then they can be both independent and mutually exclusive.
false
The number of cars produced by GM during a given quarter is a continuous random variable.
false
If P(A) = P(A|B), then events A and B are said to be:
independent
Probabilities that can be estimated from long-run relative frequencies of events are called:
objective probabilities
A function that associates a numerical value with each possible outcome of an uncertain event is called a:
random variable
Probabilities that cannot be estimated from long-run relative frequencies of events are called:
subjective probabilities
A random variable is a function that associates a numerical value with each possible outcome of a random phenomenon.
true
Suppose A and B are mutually exclusive events where P(A) = 0.2 and P(B) = 0.5, then P(A or B) = 0.70.
true
The number of car insurance policy holders is an example of a discrete random variable.
true
The number of people entering a shopping mall on a given day is an example of a discrete random variable.
true
The temperature of the room in which you are writing this test is a continuous random variable.
true
The time students spend in a computer lab during one day is an example of a continuous random variable.
true
Two events are said to be independent when knowledge of one event is of no value when assessing the probability of the other.
true
Two or more events are said to be exhaustive if one of them must occur.
true
If events A and B are mutually exclusive, then the probability of both events occurring simultaneously is equal to:
0.0
Which of the following statements is true?
The sum of all probabilities for a random variable must be equal to 1.
If two events are independent, what is the probability that they both occur?
This cannot be determined from the information given.
