Mon 21 Jun 2010
P(E|H) = 0.75
Mon 21 Jun 2010
P(E|H) = 0.75
Mon 21 Jun 2010
0< P(A)< 1
P(True) = 1
False proposition has probability 0.
P(False) = 0
P(AvB) = P(A) + P(B) – P(A^B)
Mon 21 Jun 2010
The probability that both events A and B will occur.
Mon 21 Jun 2010
The posterior probability which is the probability of event A will occur if B occurs or if all we know is about event B.
Conditional probability can be defined in terms of unconditional probabilities.
Mon 21 Jun 2010
A random variable is a variable that represents a proposition that can take on values from a set of mutually exclusive values and exhaustive values from the sample space of the random variable.
Mon 21 Jun 2010
A measure that subjects to different background knowledge and experience in evidences.
Mon 21 Jun 2010
A probability expresses a person’s degree of belief in a proposition or the occurrence of an event.
Mon 21 Jun 2010
A probability is measured by a property of a set of similar events such as times of occurring)
Mon 21 Jun 2010
Mon 21 Jun 2010
Decision Theory
= Probability Theory + Utility Theory
Decision theory uses the principle of Maximum Expected Utility (MEU):
“an agent is rational if it chooses the action that yields the highest expected utility, average over all the possible outcomes of the action.”