Mathematic


- In the medical diagnosis, the doctor knows that having a cold causing sneezing.
- Probability that Bob has a cold (unconditionally)    P(H)  = 0.2
- Probability that Bob sneezes when he has a cold (cond.)

P(E|H)  = 0.75

1. All probabilities are between 0 and 1.

0< P(A)< 1

2. True proposition has probability 1.

P(True) = 1

False proposition has probability 0.

P(False) = 0

3. The probability of a disjunction is

P(AvB) = P(A) + P(B) – P(A^B)

The probability that both events A and B will occur.

- In conditional probabilities, if all we know is about B then P(A|B) is true.
- But when additional information C is available, P(A|B) is no longer valid.
- i.e., we need joint probability of P(A|B^C)

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.

A mathematical framework for representing uncertainty about proposition and events.

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.

A measure that subjects to different background knowledge and experience in evidences.

A probability expresses a person’s degree of belief in a proposition or the occurrence of an event.

A probability is measured by a property of a set of similar events such as times of occurring)

- Frequency interpretation
- Subjective interpretation
- Degrees of belief
- Random variables and distributions
- Unconditional & Conditional Probability
- Joint probability
- The axioms of probability
- Bayes’ rule
- Certainty factor

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.”

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