Chapter 2 Flashcards
(23 cards)
A numerical statement about the likelihood that an event will occur
Probability
What are the two basic rules of probability?
- The probability, P, of any event or state of nature occurring is greater than or equal to 0 or less than or equal to 1
- The sum of the simple probabilities for all possible outcomes of an activity must equal 1
A probability of 0 indicates what?
That an event is never expected to occur
A probability of 1 indicates what?
That an event is always expected to occur
A method of determining probability value based on historical data or logic
Objective Approach
A method of determining probability values based on experience or judgement
Subjective Approach
What are the two ways to determine probability.
Objective approach or subjective approach
An objective way of determining probabilities based on observing frequencies over a number of trials
Relative Frequency Approach
An objective way of assessing probabilities based on logic
Classical or Logical Method
When logic and past history are not available or appropriate, probability values can be assessed ____.
Subjectively
Only one of the events can occur on any one trial
Mutually Exclusive Events
The list of outcomes includes every possible outcome
Collectively Exhaustive
The set of all outcomes that are common to both events.
Intersection
Probability of the intersection, which implies that both events are occurring at the same time or jointly.
Joint Probability
The set of all outcomes that are contained in either of these two events
Union
What is the general rule or additive rule formula?
P(A or B) = P(A) + P(B) – P(A and B)
The probability of an event occurring given that another event has already happend
Conditional Probability Written P(A|B)
What is the conditional probability formula?
P(A|B) = P(AB) / P(B)
The occurrence of one event has no impact on the occurrence of the other event.
Independent Events
What is the intersection formula if events a and b are independent?
P(A and B) = P(A)P(B)
a probability value that results from new or revised information and prior probabilities
Revised or Posterior Probability
j
Prior Probability
What is Baye’s Theorem?
P(A|B) = P(B|A)P(A) / P(B|A)P(A) + P(B|a)P(a) where a is the complement of the event a
