1) Deterministic techniques assume that no uncertainty exists in model parameters.
2) Probabilistic techniques assume that no uncertainty exists in model parameters.
3) Objective probabilities that can be stated prior to the occurrence of an event are classical or a priori.
4) Objective probabilities that are stated after the outcomes of an event have been observed are relative frequencies.
5) Relative frequency is the more widely used definition of objective probability.
6) Subjective probability is an estimate based on personal belief, experience, or knowledge of a situation.
7) An experiment is an activity that results in one of several possible outcomes.
8) The events in an experiment are mutually exclusive if only one can occur at a time.
9) In a given experiment, the probabilities of all mutually exclusive events sum to one.
10) A set of events is collectively exhaustive when it includes all the events that can occur in an experiment.
11) A marginal probability is the probability of a single event occurring.
12) A Venn diagram visually displays mutually exclusive and non-mutually exclusive events.
13) A joint probability is the probability that two or more events that are mutually exclusive can occur simultaneously.
14) A conditional probability is the probability that an event occurs given that another event has already occurred.
15) Conditional probabilities are shown in Venn diagrams.
16) Probability trees are used only to compute conditional probabilities.
17) A succession of events that does not affect other events is independent.
18) A binomial probability distribution indicates the probability of r successes in n trials.
19) The chi-square test is a statistical test to determine if data that are squared exhibit bias.
20) A continuous random variable may assume only integer values within a given interval.
21) Seventy two percent of all observations fall within 1 standard deviation of the mean if the data is normally distributed.
22) Another name for the mean of a probability distribution is its expected value.
23) An inspector correctly identifies defective products 90% of the time. For the next 10 products, the probability that he makes fewer than 2 incorrect inspections is 0.736.
24) In Bayesian analysis, additional information is used to alter the conditional probability of the occurrence of an event.
25) Objective probabilities that can be stated prior to the occurrence of an event are __________.
Answer: classical or a priori
26) __________ probability is an estimate based on a personal belief, experience, and knowledge of a situation.
27) The events in an experiment are __________ if only one can occur at a time.
28) A __________ organizes numerical data to describe the events of an experiment.
29) A __________ is the probability of occurrence of a single event.
30) __________ can enable one to improve marginal probabilities of the occurrence of an event by gathering additional information.
31) A succession of events that do not affect each other are __________.
32) A __________ probability is the probability that an event will occur given that another event has already occurred.
33) In a binomial distribution process, there are __________ possible outcomes.
34) One of the properties of the __________ distribution is that the probability of success remains constant over time.
35) Altered marginal probability of an event based on additional information is a __________ probability.
36) The __________ of a random variable is computed by multiplying each possible value of the variable by its probability and summing these products.