Data Analytics Chapter 5

A random experiment is defined as a process that generates

• Ambiguous

• Predetermined outcomes

• Random

• Well defined outcomes

Which of the following best shows the relationship between the probability of an event, A, and its complement, A^C?

• P(A) = P(A^C)

• P(A) = 1 - P(A^C)

• P(A) > P(A^C)

• P(A) < P(A^C)

Which of the following is NOT true about conditional probability?

• P(A) = P(A | B)

• P(A | B) is independent of event B.

• P(A | B) is the probability of event A given that event B has already occurred

• P(A | B) is the probability of event A occurring before event B

Which of the following statements is true about dependent and independent events?

• If P(D | M) is equal to P(D), then events D and M are dependent

• If P(D | M) is NOT equal to P(D), then events D and M are dependent

• If P(D | M) is NOT equal to P(D), then events D and M are independent

• If P(D | M ) is equal to P(D), then events D and M are independent

A probability tree is used in probability theory to compute

• Marginal probabilities and prior probabilities

• Joint probabilities and conditional probability

• Posterior probabilities and marginal probabilities

• Unconditional probabilities and marginal probabilities

Why are probabilities revised in probability analysis

• To calculate unconditional probabilities for specific events

• To incorporate new information into the prior probability estimates for specific events

• To obtain additional information about the events

• To obtain initial probability estimates for specific events

In probability analysis, Bayes' theorem is applicable when events to compute posterior probabilities are

• Mutually exclusive and their union is the entire sample space

• Mutually exclusive and their union is NOT the entire sample space

• NOT mutually exclusive and their union is the entire sample space

• NOT mutually exclusive and their union is NOT the entire sample space

Which of the following best describes a random variable in probability terms?

• A range of numerical values that can be generated by a random experiment

• A set of possible outcome of a random experiment

• A fixed numerical value that describes the outcome of a random experiment

• A quantity whose value is NOT known with certainty and represents the outcome of a random experiment

Financial value, such as amounts, are categorized as

• A discrete random variable

• A continuous random variable

• Neither a discrete nor a continuous random variable

• Both a discrete and a continuous random variable, depending on the context

Which of the following best describes a binomial probability distribution?

• A continuous probability distribution used to describe the results of repeated independent trials

• A discrete probability distribution that can be used to describe many situations in which a fixed number of repeated identical and independent trials has two, and only two

• A discrete probability distribution that can be used to describe many situations in which a fixed number of repeated identical and independent trials has more than two possible outcomes

• A discrete probability distribution used to describe the results of a single trial with two possible outcomes