Axiomatic Approach to Probability

Axiomatic Approach to Probability

Data Science and A.I. Lecture Series

 

Axiomatic Approach to Probability

Definition:

  • Let \( S \) be a sample space for a random experiment.
  • Let \( A \) be an event that is a subset of \( S \).
  • \( P(A) \) is called a probability function if it satisfies the following axioms:

Axioms of Probability

  • Non-Negativity: \( P(A) \geq 0 \) for all \( A \subseteq S \).
  • Normalization: \( P(S) = 1 \).
  • Additivity: If \( A_1, A_2, \dots \) are mutually disjoint events, then:\[
    P(A_1 \cup A_2 \cup \cdots) = P(A_1) + P(A_2) + \cdots
    \]

Implications of the Axioms

  • The probability of an impossible event is zero: \( P(\emptyset) = 0 \).
  • For any event \( A \), the probability of its complement is:\[
    P(A^c) = 1 – P(A).
    \]
  • If \( A \subseteq B \), then \( P(A) \leq P(B) \).

Set-Theoretic Interpretations of Events

  • At least one of the events \( A \) or \( B \) occurs: \( A \cup B \).
  • Both events \( A \) and \( B \) occur: \( A \cap B \).
  • Neither \( A \) nor \( B \) occurs: \( A^c \cap B^c \).
  • Event \( A \) occurs and \( B \) does not occur: \( A \cap B^c \).
  • Exactly one of the events \( A \) or \( B \) occurs: \( (A \cap B^c) \cup (A^c \cap B) \).
  • Not more than one of the events \( A \) or \( B \) occurs: \( (A^c \cap B^c) \cup (A \cap B^c) \cup (A^c \cap B) \).

Some Results Using Probability Function

  • Probability of the impossible event is zero: \( P(\emptyset) = 0 \).
  • Probability of the complementary event: For any event \( A \), \( P(A^c) = 1 – P(A) \).
  • Addition Rule for Two Events:\[
    P(A \cup B) = P(A) + P(B) – P(A \cap B).
    \]
  • Conditional Probability:\[
    P(A | B) = \frac{P(A \cap B)}{P(B)} \quad \text{if } P(B) > 0.
    \]
  • Independence of Events: Two events \( A \) and \( B \) are independent if:\[
    P(A \cap B) = P(A) \cdot P(B).
    \]

Process to Prove Results Using Probability Function

  • To prove \( P(\emptyset) = 0 \):
    • By the Additivity Axiom, \( P(S \cup \emptyset) = P(S) + P(\emptyset) \).
    • Since \( S \cup \emptyset = S \) and \( P(S) = 1 \), we get \( 1 = 1 + P(\emptyset) \).
    • Thus, \( P(\emptyset) = 0 \).
  • To prove \( P(A^c) = 1 – P(A) \):
    • We know that \( A \cup A^c = S \) and \( A \cap A^c = \emptyset \).
    • By the Additivity Axiom, \( P(A \cup A^c) = P(A) + P(A^c) \).
    • Since \( P(A \cup A^c) = P(S) = 1 \), we get \( 1 = P(A) + P(A^c) \).
    • Thus, \( P(A^c) = 1 – P(A) \).
  • To prove \( P(A \cup B) = P(A) + P(B) – P(A \cap B) \):
    • By the definition of union, \( A \cup B = A + B – (A \cap B) \).
    • Using the Additivity Axiom, \( P(A \cup B) = P(A) + P(B) – P(A \cap B) \).

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